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WP28: valid-worker-only variants, robust baselines under failed local fits, pseudo-true target for misspecified designs, benchmark launcher fixes, Lean docs

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Simon-Pierre Boucher committed (Oct 29, 2026) parent 6162f9a Browse files

82 changed files +19,269 −448

82 changed files
modified experiments/EXPERIMENT_MANIFEST.csv +15 −0
@@ -32,6 +32,13 @@ exp_p1_N262144_K32768,63bdb07,3.14.4,2.4.4,,6502579563820440675,262144,32768,8,1
32 32 exp_p1_N262144_K4096,63bdb07,3.14.4,2.4.4,,4842079901205516085,262144,4096,64,1,"{""theta0"": 1.0}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,2000,xargs -P / nohup,1,MacBookPro-de-simon-pierre-2.local arm64,macOS,62.5,0,in-memory (no network),completed,629ce95b7b2ac6ca3ec1302ce77a3b223bce374fafbe69b52d09eb8dc3c59c33
33 33 exp_p1_N262144_K512,2718842,3.14.4,2.4.4,,6815573501771189831,262144,512,512,1,"{""theta0"": 1.0}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,2000,xargs -P / nohup,1,MacBookPro-de-simon-pierre-2.local arm64,macOS,15.3,0,in-memory (no network),completed,59885e79e3e6349fe1a2c92854426090fd9c6c82d8422f4680b8698896c319ec
34 34 exp_p1_N262144_K8192,63bdb07,3.14.4,2.4.4,,4526677405690696884,262144,8192,32,1,"{""theta0"": 1.0}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,2000,xargs -P / nohup,1,MacBookPro-de-simon-pierre-2.local arm64,macOS,113.9,0,in-memory (no network),completed,409e9543f73b6a17ca87fb52d8567d82cbc172ba8befe77569f1044787ab1d2d
35 +exp_p1_N4194304_K131072,6162f9a,3.14.4,2.4.4,,5869945858902268034,4194304,131072,32,1,"{""theta0"": 1.0}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,500,xargs -P / nohup,1,MacBookPro-de-simon-pierre-2.local arm64,macOS,416.9,0,in-memory (no network),completed,589fdb83275b1e4f9bc4e6f75f9407d6e5a1ad14696f05b90e88768204dbab11
36 +exp_p1_N4194304_K16384,6162f9a,3.14.4,2.4.4,,918683220796581743,4194304,16384,256,1,"{""theta0"": 1.0}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,500,xargs -P / nohup,1,MacBookPro-de-simon-pierre-2.local arm64,macOS,69.6,0,in-memory (no network),completed,23e43562aadd2d1bf19821a521b47de98608784a6a78ad2d2c5f82ecfbc1e68d
37 +exp_p1_N4194304_K262144,6162f9a,3.14.4,2.4.4,,7511302434615467187,4194304,262144,16,1,"{""theta0"": 1.0}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,500,xargs -P / nohup,1,MacBookPro-de-simon-pierre-2.local arm64,macOS,835.3,0,in-memory (no network),completed,ae644139d3076db198eb993e241d930f5b6cfea5eb842b99515ef49d44c349eb
38 +exp_p1_N4194304_K32768,6162f9a,3.14.4,2.4.4,,5246855797948617312,4194304,32768,128,1,"{""theta0"": 1.0}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,500,xargs -P / nohup,1,MacBookPro-de-simon-pierre-2.local arm64,macOS,118.7,0,in-memory (no network),completed,066920fc2744fbe904781135d9372433985d510d44b4fdb59bcaf44be51ef739
39 +exp_p1_N4194304_K4096,6162f9a,3.14.4,2.4.4,,8901210737275983155,4194304,4096,1024,1,"{""theta0"": 1.0}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,500,xargs -P / nohup,1,MacBookPro-de-simon-pierre-2.local arm64,macOS,32.4,0,in-memory (no network),completed,8eaa08d5e9033a713ed658b592bb0072598d38aed8538199bce271239e4d04b5
40 +exp_p1_N4194304_K65536,6162f9a,3.14.4,2.4.4,,1422845102444572070,4194304,65536,64,1,"{""theta0"": 1.0}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,500,xargs -P / nohup,1,MacBookPro-de-simon-pierre-2.local arm64,macOS,218.4,0,in-memory (no network),completed,226033f3f652727eca2a2dfcfc6aa96c75ddc20cb9aa7c25e8248c30f7264393
41 +exp_p1_N4194304_K8192,6162f9a,3.14.4,2.4.4,,5952293673679115060,4194304,8192,512,1,"{""theta0"": 1.0}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,500,xargs -P / nohup,1,MacBookPro-de-simon-pierre-2.local arm64,macOS,45.4,0,in-memory (no network),completed,13d596154f680810d28880d90f028af26f6224cbfa87967ea75554bbca5cdd00
35 42 exp_p1_N65536_K1024,7a86c23,3.14.4,2.4.4,,3718237952087232854,65536,1024,64,1,"{""theta0"": 1.0}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,2000,xargs -P / nohup,1,MacBookPro-de-simon-pierre-2.local arm64,macOS,15.3,0,in-memory (no network),completed,46077d73a20c1aac90e8d8687a688380e805c630c7b735bf134c66681df77732
36 43 exp_p1_N65536_K128,7a86c23,3.14.4,2.4.4,,5161033798656750738,65536,128,512,1,"{""theta0"": 1.0}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,2000,xargs -P / nohup,1,MacBookPro-de-simon-pierre-2.local arm64,macOS,4.1,0,in-memory (no network),completed,47f73dc6dbf3f2e2a68cb6e86664c25eb178cce79da1ed569fb627bb185d4f6c
37 44 exp_p1_N65536_K2048,7a86c23,3.14.4,2.4.4,,6516373625071197227,65536,2048,32,1,"{""theta0"": 1.0}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,2000,xargs -P / nohup,1,MacBookPro-de-simon-pierre-2.local arm64,macOS,27.2,0,in-memory (no network),completed,3cfe02dcd5ee7128c165d176346c0dce3103e95b4c372f1ee87d5c8443304363
@@ -54,6 +61,7 @@ logit_illcond_p8_N65536_K256,,3.9.6,2.0.2,,653361399314549916,65536,256,256,8,"{
54 61 logit_illcond_p8_N65536_K512,,3.9.6,2.0.2,,5773920174557957997,65536,512,128,8,"{""cond"": 100.0}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,500,xargs -P / nohup,1,m4mm arm64,macOS,427.6,0,in-memory (no network),completed,e38228f52b6233f5f414dcf775b8a15bb50169b098a5c4e2737c72ed16c7689a
55 62 logit_misspec_p3_N1048576_K16384,,3.9.6,2.0.2,,7563420772212710497,1048576,16384,64,3,"{""kind"": ""misspecified"", ""omitted"": 0.5}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,M4M64c arm64,macOS,9276.7,0,in-memory (no network),completed,c9308a96ae7ba8a5f6e0cc13e611141a885e863290ccc605fd26af52f20e6ba8
56 63 logit_misspec_p3_N1048576_K2048,,3.14.5,2.5.4,,2687421392954700525,1048576,2048,512,3,"{""kind"": ""misspecified"", ""omitted"": 0.5}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,MacStudnpierre2 arm64,macOS,3556.9,0,in-memory (no network),completed,0c90a99e0987d14f83dad7b3af9f6d0b19daaa466f7c745644412aebafdb2df9
64 +logit_misspec_p3_N1048576_K32768,,3.9.6,2.0.2,,3556832066521034766,1048576,32768,32,3,"{""kind"": ""misspecified"", ""omitted"": 0.5}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,M5M36 arm64,macOS,16583.9,0,in-memory (no network),completed,825b2b810b72ac6b650a21b22480f005dfbdc85568d0b4ec717485ba530c5c98
57 65 logit_misspec_p3_N1048576_K4096,,3.14.4,2.5.4,,6092926862139708464,1048576,4096,256,3,"{""kind"": ""misspecified"", ""omitted"": 0.5}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,m3u96b arm64,macOS,3912.0,0,in-memory (no network),completed,55e4949a1ec2d131d5084b25a401ee51e9c520279ca0a2d1bab27367fa40cac8
58 66 logit_misspec_p3_N1048576_K8192,,3.14.5,2.5.4,,31876339817681152,1048576,8192,128,3,"{""kind"": ""misspecified"", ""omitted"": 0.5}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,MacStudnpierre2 arm64,macOS,5439.8,0,in-memory (no network),completed,047035bf87f687a1a8c931909d01103acf9289c2ff7ba8cac06c14508c229adb
59 67 logit_misspec_p3_N262144_K1024,,3.14.4,2.5.4,,5430299985042827137,262144,1024,256,3,"{""kind"": ""misspecified"", ""omitted"": 0.5}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,MacStudnpierre4 arm64,macOS,807.5,0,in-memory (no network),completed,4ba4f64a30ce7d9379a36dcbd72dd956184887372ca115da268192acb6106b90
@@ -61,12 +69,16 @@ logit_misspec_p3_N262144_K2048,,3.14.4,2.5.4,,3365958059589350090,262144,2048,12
61 69 logit_misspec_p3_N262144_K4096,,3.9.6,2.0.2,,7074448613771151296,262144,4096,64,3,"{""kind"": ""misspecified"", ""omitted"": 0.5}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,MacStudonpierre arm64,macOS,2898.2,0,in-memory (no network),completed,486c0d237a7934e4b020a4c518d0e0e476691bfa4f4b91aa1de4e714e85e8579
62 70 logit_misspec_p3_N262144_K512,,3.9.6,2.0.2,,4080476778475930787,262144,512,512,3,"{""kind"": ""misspecified"", ""omitted"": 0.5}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,MacBookonpierre arm64,macOS,938.8,0,in-memory (no network),completed,618da4fe4c95f9cfa37b9e5db38c5719c8096141e70a893523d49acbb00e9c25
63 71 logit_misspec_p3_N262144_K8192,,3.9.6,2.0.2,,4860399401084713574,262144,8192,32,3,"{""kind"": ""misspecified"", ""omitted"": 0.5}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,M4M64c arm64,macOS,3976.4,0,in-memory (no network),completed,747d085e4a92f4ece110fc931102892f7c25c09cc101913164791bf24352b6bf
72 +logit_misspec_p3_N65536_K1024,,3.9.6,2.0.2,,5927146201951817713,65536,1024,64,3,"{""kind"": ""misspecified"", ""omitted"": 0.5}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,M5M36 arm64,macOS,455.5,0,in-memory (no network),completed,0a024777482db1db789a4331b76c3a1b839a6cf57922087d0e89d00ea7e1b62c
64 73 logit_misspec_p3_N65536_K128,,3.9.6,2.0.2,,1189149877376627910,65536,128,512,3,"{""kind"": ""misspecified"", ""omitted"": 0.5}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,MacStudonpierre arm64,macOS,261.1,0,in-memory (no network),completed,d5549965eb18106d51676e09521787a845070e08dbdceda307a18283dfd7c769
65 74 logit_misspec_p3_N65536_K2048,,3.9.6,2.0.2,,9108325309212204322,65536,2048,32,3,"{""kind"": ""misspecified"", ""omitted"": 0.5}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,MacStudnpierre7 arm64,macOS,1250.8,0,in-memory (no network),completed,44bd58b165a41d4592f4180d4aa02e2ba7f580613bad5965131b03eeaff24e0e
66 75 logit_misspec_p3_N65536_K256,,3.14.4,2.5.4,,5271711696808027188,65536,256,256,3,"{""kind"": ""misspecified"", ""omitted"": 0.5}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,m3u96b arm64,macOS,223.5,0,in-memory (no network),completed,35b8202e739a00d69b2aa97804232b289b236676f3c7e1de6860190125d2484b
67 76 logit_misspec_p3_N65536_K512,,3.14.5,2.5.4,,3578458641162309222,65536,512,128,3,"{""kind"": ""misspecified"", ""omitted"": 0.5}",estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,MacStudnpierre2 arm64,macOS,283.3,0,in-memory (no network),completed,c29ffec0dbff1a6717c394274a6da063592ec08ce27125dd8cdad93c01dcb07b
68 77 logit_p20_p20_N1048576_K1024,,3.14.4,2.5.4,,6566023737295273270,1048576,1024,1024,20,{},estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,500,xargs -P / nohup,1,MacStudnpierre6 arm64,macOS,10956.8,0,in-memory (no network),completed,0d1def0937b0015d36d47e0e6dc4e738f6988854d790689dec6202e53b30759d
78 +logit_p20_p20_N1048576_K2048,,3.9.6,2.0.2,,8820668351971355137,1048576,2048,512,20,{},estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,500,xargs -P / nohup,1,MacStudonpierre arm64,macOS,19126.7,0,in-memory (no network),completed,53b809ed90ba10d83c2640c6ea9981c1607e47b38d448f0f41b509f4e1de273a
79 +logit_p20_p20_N1048576_K4096,,3.14.4,2.5.4,,4772145725761853017,1048576,4096,256,20,{},estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,500,xargs -P / nohup,1,m3u96b arm64,macOS,23767.6,0,in-memory (no network),completed,ffdc568261ba94bf57df4d782695e78e8c95876004183cfd4986849f3d53a870
69 80 logit_p20_p20_N1048576_K512,,3.14.4,2.5.4,,606147641735452015,1048576,512,2048,20,{},estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,500,xargs -P / nohup,1,MacStudnpierre4 arm64,macOS,10487.1,0,in-memory (no network),completed,02851f9b607635a181ba320a70396de0a7241c3abb013e4f6a1131dfd2f682c2
81 +logit_p20_p20_N1048576_K8192,,3.14.5,2.5.4,,7482660823573765396,1048576,8192,128,20,{},estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,500,xargs -P / nohup,1,MacStudnpierre2 arm64,macOS,36402.2,0,in-memory (no network),completed,f5d59567fd5bbda6cac5552119303715110a9f98c8bc1536dbad8c96f3628418
70 82 logit_p20_p20_N262144_K1024,,3.9.6,2.0.2,,7318019597999661126,262144,1024,256,20,{},estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,500,xargs -P / nohup,1,Macmininpierre5 arm64,macOS,7345.6,0,in-memory (no network),completed,7cee42d684dcb18a218f5462605c51a00dd85456f46bc82242f53028301d8064
71 83 logit_p20_p20_N262144_K128,,3.14.5,2.5.4,,8337658769267575056,262144,128,2048,20,{},estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,500,xargs -P / nohup,1,MacStudnpierre2 arm64,macOS,2984.6,0,in-memory (no network),completed,27111fbc0dc688ca19ccf5c32dff68d526adfd55caa52f813df90a3cb7afc3fc
72 84 logit_p20_p20_N262144_K2048,,3.9.6,2.0.2,,2694841364195809102,262144,2048,128,20,{},estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,500,xargs -P / nohup,1,M5M36 arm64,macOS,9484.4,0,in-memory (no network),completed,b5ff141a4572e0235f7574b04e8ea832b6faf49dd5354645b370936eb702ccd5
@@ -75,6 +87,7 @@ logit_p20_p20_N262144_K512,,3.9.6,2.0.2,,4893709743684942704,262144,512,512,20,{
75 87 logit_p3_N1048576_K1024,,3.9.6,2.0.2,,3470184715554602196,1048576,1024,1024,3,{},estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,simonpierresMBP arm64,macOS,2874.2,0,in-memory (no network),completed,6aa5edb446d7592fb05de5e66dd96e5c6aa7839eb8df3bbc834408a15fe9c21a
76 88 logit_p3_N1048576_K16384,,3.9.6,2.0.2,,91415039088362818,1048576,16384,64,3,{},estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,M4M64c arm64,macOS,9706.1,0,in-memory (no network),completed,2e8e32d94b123a0f2357fd7066e5a5bf4ba2639b921ff6edc74edd31a4177bf6
77 89 logit_p3_N1048576_K2048,,3.9.6,2.0.2,,3680751446492255465,1048576,2048,512,3,{},estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,simonpirresMBP2 arm64,macOS,3013.3,0,in-memory (no network),completed,3db8f58563813eb8bdddc07e01bc710e748a3044e6196ef99b921bd51a020e74
90 +logit_p3_N1048576_K32768,,3.9.6,2.0.2,,21189898402569255,1048576,32768,32,3,{},estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,M5M36 arm64,macOS,16941.4,0,in-memory (no network),completed,5d2fbda3dcaaf8fa075c30d3ab583eb3a0aa4678d8b30faef867b81858c76434
78 91 logit_p3_N1048576_K4096,,3.14.4,2.5.4,,5736190541017903225,1048576,4096,256,3,{},estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,m3u96b arm64,macOS,3951.5,0,in-memory (no network),completed,bd0c345dfd6f77a66fa5677658dcdd16293430f5eed86dfe8b3c4611b15d0b48
79 92 logit_p3_N1048576_K8192,,3.14.5,2.5.4,,1417976703486372763,1048576,8192,128,3,{},estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,MacStudnpierre2 arm64,macOS,5928.4,0,in-memory (no network),completed,702902760657b9c7e5fad4395daade6c414229b66b82cb05de4196a3b5b22b57
80 93 logit_p3_N16384_K128,,3.9.6,2.0.2,,6268040442768731135,16384,128,128,3,{},estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,m4mm arm64,macOS,62.9,0,in-memory (no network),completed,681ab11f79f630f55726c74b664a14e1c0adb9da4942748d8ce3b1f6f6e8c8a7
@@ -96,8 +109,10 @@ logit_p3_N65536_K256,,3.9.6,2.0.2,,8317538664952218626,65536,256,256,3,{},estima
96 109 logit_p3_N65536_K512,,3.9.6,2.0.2,,6302214093706708655,65536,512,128,3,{},estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,m6mb arm64,macOS,229.9,0,in-memory (no network),completed,3392a34b85885c465e5ddc5a292d1bb63518b629594015fd70a57336a412a6e6
97 110 logit_p3_N65536_K64,,3.14.4,2.5.4,,6021038287837971332,65536,64,1024,3,{},estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,MacStudnpierre6 arm64,macOS,165.1,0,in-memory (no network),completed,a8f336272c233ccb70c8a75454ed30d1288f67b638b69dd2dd27e88a8e0f415d
98 111 logit_p8_N1048576_K1024,,3.9.6,2.0.2,,6698972530427685325,1048576,1024,1024,8,{},estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,MacStudnpierre7 arm64,macOS,8288.1,0,in-memory (no network),completed,9b1b30ffb1802c39c2251fe8e3352ea05c9877177a5a83d4635b86af7e849a6c
112 +logit_p8_N1048576_K16384,,3.9.6,2.0.2,,3073381346928451233,1048576,16384,64,8,{},estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,M4M64c arm64,macOS,27423.9,0,in-memory (no network),completed,d53f0891b61d353876e78110ab1bd4dce8910ec48e65054defe771d0873ae5e7
99 113 logit_p8_N1048576_K2048,,3.9.6,2.0.2,,6354247005063002822,1048576,2048,512,8,{},estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,simonpierresMBP arm64,macOS,7431.4,0,in-memory (no network),completed,26648ea3c37f4f0ec48a15aa883ed7d54c33aa5755893c7d718d23aeaa7bce41
100 114 logit_p8_N1048576_K4096,,3.9.6,2.0.2,,5229261129462349956,1048576,4096,256,8,{},estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,simonpirresMBP2 arm64,macOS,8607.3,0,in-memory (no network),completed,a18df7441e42ab1fcd2a2787b8b46d7a4aed55c2a01eb0ac9c2736608c6fd4a1
115 +logit_p8_N1048576_K8192,,3.9.6,2.0.2,,4723022365370056307,1048576,8192,128,8,{},estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,M5M36 arm64,macOS,15247.2,0,in-memory (no network),completed,70f240acf900b615965a13ac9e8e99cedf470172589d8c45b2adfb417765d940
101 116 logit_p8_N16384_K128,,3.9.6,2.0.2,,1929461084092776376,16384,128,128,8,{},estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,m5ma arm64,macOS,200.3,0,in-memory (no network),completed,8393646d69c24f743b9b9d6291abab9b6bcd195d86edf4f726e39ab53aba2fc8
102 117 logit_p8_N16384_K16,,3.14.4,2.5.4,,9066105959199088908,16384,16,1024,8,{},estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,m3u96b arm64,macOS,102.2,0,in-memory (no network),completed,8605fd6f5641f8c51ea71fab45bfe5b6c34c442e61aeee28f198e7b7908bf6d4
103 118 logit_p8_N16384_K256,,3.9.6,2.0.2,,734206799928427210,16384,256,64,8,{},estimate_all,"batched Newton, step halving, tol 1e-9 (central 1e-12)",1e-9,1000,xargs -P / nohup,1,m6mb arm64,macOS,326.8,0,in-memory (no network),completed,14616115ddd2478c8d422e0629d875036a9220bf08bb40e1d6e928494f8ba6c0
modified experiments/make_tables.py +8 −6
@@ -7,11 +7,11 @@ import numpy as np, pandas as pd
7 7 ROOT = pathlib.Path(__file__).resolve().parents[1]
8 8 PROC, RAW, TAB = ROOT / "results" / "processed", ROOT / "results" / "raw", ROOT / "paper" / "tables"
9 9 TAB.mkdir(parents=True, exist_ok=True)
10 −LAB = {"r1_q0": "(1,0) plain average", "r1_q1": "(1,1) average + 1 Newton", "r1_q2": "(1,2) average + 2 Newton", "r2_q0": "(2,0) half-block jackknife",
10 +LAB = {"v1_q0": "(1,0) valid workers only", "v1_q1": "(1,1) valid workers only", "v2_q0": "(2,0) valid workers only", "v2_q1": "(2,1) valid workers only", "v3_q1": "(3,1) valid workers only", "r1_q0": "(1,0) plain average", "r1_q1": "(1,1) average + 1 Newton", "r1_q2": "(1,2) average + 2 Newton", "r2_q0": "(2,0) half-block jackknife",
11 11 "r2_q1": "(2,1) half-block + 1 Newton", "r2_q2": "(2,2) half-block + 2 Newton", "r3_q0": "(3,0) quarter-block", "r3_q1": "(3,1) quarter-block + 1 Newton",
12 12 "r3_q2": "(3,2) quarter-block + 2 Newton", "cs_q0": "analytic Cox--Snell, $q=0$", "cs_q1": "analytic Cox--Snell + 1 Newton", "csl1": "CSL, 1 round", "csl2": "CSL, 2 rounds",
13 13 "aee": "AEE (Lin--Xi)", "stale_r1_q1": "(1,1) stale Hessian", "stale_r2_q1": "(2,1) stale Hessian", "stale_r1_q2": "(1,2) stale Hessian", "central": "centralized MLE"}
14 −MAIN = ["r1_q0", "r1_q1", "r1_q2", "r2_q0", "r2_q1", "r2_q2", "r3_q0", "r3_q1", "cs_q1", "csl1", "csl2", "aee", "stale_r2_q1", "central"]
14 +MAIN = ["r1_q0", "r1_q1", "r1_q2", "r2_q0", "r2_q1", "r2_q2", "r3_q0", "r3_q1", "v2_q1", "v3_q1", "cs_q1", "csl1", "csl2", "aee", "stale_r2_q1", "central"]
15 15
16 16
17 17 def fmt(x, d=3):
@@ -36,7 +36,7 @@ def table_cell(s, label, p, N, ms, fname, caption, ests=MAIN):
36 36 lines = [r"\begin{table}[p]", r"\centering\scriptsize", r"\begin{threeparttable}", f"\\caption{{{caption}}}\\label{{tab:{fname[:-4]}}}",
37 37 r"\begin{tabular}{@{}l" + "r" * (3 * len(ms)) + "@{}}", r"\toprule",
38 38 "Estimator & " + " & ".join(f"\\multicolumn{{3}}{{c}}{{$m = {m}$, $K = {int(N//m):,}$}}" for m in ms) + r" \\",
39 − " & " + " & ".join("gap & RMSE & cov" for _ in ms) + r" \\", r"\midrule"]
39 + " & " + " & ".join("gap & median & cov" for _ in ms) + r" \\", r"\midrule"]
40 40 for e in ests:
41 41 row = [LAB.get(e, e)]
42 42 for m in ms:
@@ -44,11 +44,11 @@ def table_cell(s, label, p, N, ms, fname, caption, ests=MAIN):
44 44 if dd.empty:
45 45 row += ["--", "--", "--"]; continue
46 46 dd = dd.iloc[0]
47 − row += [fmt(dd["rms_gap"]), fmt(dd["rmse"]), (f"{dd['cov95']:.3f}" if "cov95" in dd and np.isfinite(dd["cov95"]) else "--")]
47 + row += [fmt(dd["rms_gap"]), fmt(dd["median_gap"]), (f"{dd['cov95']:.3f}" if "cov95" in dd and np.isfinite(dd["cov95"]) else "--")]
48 48 lines.append(" & ".join(row) + r" \\")
49 49 reps = int(d.reps.iloc[0]); cf = d.drop_duplicates("m")[["m", "central_fail", "valid_frac_r2", "valid_frac_r3"]].sort_values("m") if "valid_frac_r3" in d else None
50 50 lines += [r"\bottomrule", r"\end{tabular}", r"\begin{tablenotes}\footnotesize",
51 − f"\\item {reps} paired replications per column. gap $=$ root mean square of $\\sqrt N\\,\\lVert\\tilde\\theta - \\widehat\\theta_N\\rVert$; RMSE $=$ root mean square of $\\sqrt N\\,\\lVert\\tilde\\theta - \\theta_0\\rVert$; cov $=$ empirical coverage of nominal 95\\% Wald intervals (observed information at the estimate; `--' when not computed). Monte Carlo standard errors of the gaps and RMSEs are in \\texttt{{results/processed/summary.csv}}; coverage standard error $\\approx {np.sqrt(0.95*0.05/reps):.3f}$."]
51 + f"\\item {reps} paired replications per column. gap $=$ root mean square of $\\sqrt N\\,\\lVert\\tilde\\theta - \\widehat\\theta_N\\rVert$ over all replications (including those with failed local fits); median $=$ its median; cov $=$ empirical coverage of nominal 95\\% Wald intervals (observed information at the estimate; `--' when not computed). Monte Carlo standard errors of the gaps and RMSEs are in \\texttt{{results/processed/summary.csv}}; coverage standard error $\\approx {np.sqrt(0.95*0.05/reps):.3f}$."]
52 52 if cf is not None:
53 53 lines.append("\\item Fraction of workers with all local fits valid (orders 2 / 3): " + "; ".join(f"$m={int(r.m)}$: {r.valid_frac_r2:.3f} / {r.valid_frac_r3:.3f}" for r in cf.itertuples()) + ".")
54 54 lines += [r"\end{tablenotes}", r"\end{threeparttable}", r"\end{table}"]
@@ -62,6 +62,8 @@ def table_rates(s, fname="mc_rates.tex"):
62 62 N = d.N.max()
63 63 for e in ["r1_q0", "r1_q1", "r1_q2", "r2_q0", "r2_q1", "r3_q0", "r3_q1", "cs_q1"]:
64 64 dd = d[(d.N == N) & (d.estimator == e) & (d.rms_gap > 1e-9)].sort_values("m")
65 + if "valid_frac_r3" in dd:
66 + dd = dd[(dd.valid_frac_r3 >= 0.999) & (dd.valid_frac_r2 >= 0.999)] # failure-free cells only
65 67 if len(dd) >= 3:
66 68 slope = np.polyfit(np.log(dd.m), np.log(dd.rms_gap), 1)[0]
67 69 rows.append((label, p, N, e, slope, len(dd)))
@@ -196,7 +198,7 @@ def main():
196 198 if not s.empty:
197 199 for (label, p), d in s.groupby(["label", "p"]):
198 200 N = d.N.max()
199 − made[(label, p)] = table_cell(s, label, p, N, sorted(d.m.unique()), f"mc_{label}_p{p}.tex", f"Monte Carlo, {label.replace('_', ' ')} design, $p = {p}$, $N = {N:,}$: scaled gap to $\\widehat\\theta_N$, scaled RMSE and 95\\% coverage by local sample size $m$.")
201 + made[(label, p)] = table_cell(s, label, p, N, sorted(d.m.unique()), f"mc_{label}_p{p}.tex", f"Monte Carlo, {label.replace('_', ' ')} design, $p = {p}$, $N = {N:,}$: scaled gap to $\\widehat\\theta_N$ (root mean square and median) and 95\\% coverage by local sample size $m$.")
200 202 table_rates(s)
201 203 table_boundary(); table_ablation("exponential", "abl_exponential.tex"); table_ablation("logistic", "abl_logistic.tex"); table_skew(); table_bench()
202 204 n = manifest()
modified experiments/process_results.py +3 −0
@@ -44,6 +44,9 @@ def summarize_cell(df):
44 44 p = int(df["p"].iloc[0]); N = int(df["N"].iloc[0]); sN = np.sqrt(N)
45 45 th0 = df[[f"theta0_{j}" for j in range(p)]].to_numpy()
46 46 cen = df[[f"central_{j}" for j in range(p)]].to_numpy()
47 + if any(k in str(df["label"].iloc[0]) for k in ("misspec", "contam")):
48 + # pseudo-true value: the mean of the centralized pseudo-MLE over replications (its O(1/N) bias is negligible at the N used)
49 + th0 = np.broadcast_to(cen.mean(axis=0), th0.shape)
47 50 rows = []
48 51 B = len(df)
49 52 for e in estimators(df):
modified experiments/run_benchmarks.py +4 −3
@@ -15,7 +15,7 @@ PY = "~/wp28/venv/bin/python"
15 15 def launch_coordinator(host_alias, port, K, model, p, N, splits, q, hmode, seed, bits):
16 16 code = (f"import sys,json; sys.path.insert(0,'{'~/wp28/repo/src'}'); import os; sys.path[0]=os.path.expanduser(sys.path[0]); "
17 17 f"from pamle.protocol import coordinator_run; "
18 − f"r=coordinator_run({port},{K},'{model}',{p},{N},{tuple(splits)},{q},'{hmode}',{seed},{bits},log=lambda *a: None); print(json.dumps(r))")
18 + f"r=coordinator_run({port},{K},'{model}',{p},{N},{tuple(splits)},{q},'{hmode}',{seed},{bits},log=lambda *a: None); print(json.dumps(r, default=lambda o: o.item() if hasattr(o, 'item') else str(o)))")
19 19 cmd = f"{PY} -c {shlex.quote(code)}"
20 20 return subprocess.Popen(["ssh", "-o", "ConnectTimeout=10", host_alias, cmd], stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)
21 21
@@ -24,9 +24,10 @@ def launch_workers(assign, coord_ip, port):
24 24 procs = []
25 25 wid = 0
26 26 for alias, n in assign:
27 − cmds = " ".join(f"(cd ~/wp28/repo/src && {PY} -m pamle.worker --connect {coord_ip}:{port} --id {wid + i} > /dev/null 2>&1 &)" for i in range(n))
27 + # workers are children of the ssh shell and `wait` keeps the session (and the workers) alive until they exit
28 + cmds = "cd ~/wp28/repo/src && " + " ".join(f"{PY} -m pamle.worker --connect {coord_ip}:{port} --id {wid + i} > /tmp/wp28_worker_{wid + i}.log 2>&1 &" for i in range(n)) + " wait"
28 29 wid += n
29 − procs.append(subprocess.Popen(["ssh", "-o", "ConnectTimeout=10", alias, cmds + "; wait"], stdout=subprocess.DEVNULL, stderr=subprocess.PIPE, text=True))
30 + procs.append(subprocess.Popen(["ssh", "-o", "ConnectTimeout=10", alias, cmds], stdout=subprocess.DEVNULL, stderr=subprocess.PIPE, text=True))
30 31 return procs
31 32
32 33
modified paper/tables/abl_exponential.tex +90 −90
@@ -6,128 +6,128 @@
6 6 \toprule
7 7 Pattern & curvature & $q$ & $m = 24$ & $m = 96$ \\
8 8 \midrule
9 −(1) & exact & 0 & 109.037 & 26.408 \\
10 −(1) & exact & 1 & 4.740 & 0.278 \\
9 +(1) & exact & 0 & 109.045 & 26.408 \\
10 +(1) & exact & 1 & 4.741 & 0.278 \\
11 11 (1) & exact & 2 & 0.009 & 3.08e-5 \\
12 12 (1) & exact & 3 & 3.20e-8 & 4.80e-13 \\
13 −(1) & stale & 1 & 8.721 & 0.545 \\
13 +(1) & stale & 1 & 8.723 & 0.545 \\
14 14 (1) & stale & 2 & 0.378 & 0.006 \\
15 15 (1) & stale & 3 & 0.015 & 5.91e-5 \\
16 −(1) & single & 1 & 4.740 & 0.278 \\
16 +(1) & single & 1 & 4.741 & 0.278 \\
17 17 (1) & single & 2 & 0.009 & 3.08e-5 \\
18 18 (1) & single & 3 & 3.20e-8 & 4.79e-13 \\
19 −(1,2) & exact & 0 & 9.972 & 0.601 \\
20 −(1,2) & exact & 1 & 0.040 & 1.77e-4 \\
21 −(1,2) & exact & 2 & 6.42e-7 & 2.22e-11 \\
22 −(1,2) & exact & 3 & 3.08e-13 & 3.14e-13 \\
23 −(1,2) & stale & 1 & 0.360 & 0.006 \\
19 +(1,2) & exact & 0 & 9.932 & 0.601 \\
20 +(1,2) & exact & 1 & 0.039 & 1.77e-4 \\
21 +(1,2) & exact & 2 & 6.32e-7 & 2.22e-11 \\
22 +(1,2) & exact & 3 & 2.86e-13 & 3.14e-13 \\
23 +(1,2) & stale & 1 & 0.359 & 0.006 \\
24 24 (1,2) & stale & 2 & 0.014 & 6.18e-5 \\
25 −(1,2) & stale & 3 & 5.74e-4 & 6.35e-7 \\
26 −(1,2) & single & 1 & 0.040 & 1.77e-4 \\
27 −(1,2) & single & 2 & 6.42e-7 & 2.22e-11 \\
28 −(1,2) & single & 3 & 3.08e-13 & 3.14e-13 \\
29 −(1,3) & exact & 0 & 15.613 & 0.870 \\
25 +(1,2) & stale & 3 & 5.72e-4 & 6.35e-7 \\
26 +(1,2) & single & 1 & 0.039 & 1.77e-4 \\
27 +(1,2) & single & 2 & 6.32e-7 & 2.22e-11 \\
28 +(1,2) & single & 3 & 2.86e-13 & 3.14e-13 \\
29 +(1,3) & exact & 0 & 15.578 & 0.870 \\
30 30 (1,3) & exact & 1 & 0.097 & 3.28e-4 \\
31 −(1,3) & exact & 2 & 3.79e-6 & 5.65e-11 \\
32 −(1,3) & exact & 3 & 2.95e-13 & 3.11e-13 \\
33 −(1,2,4) & exact & 0 & 2.032 & 0.312 \\
31 +(1,3) & exact & 2 & 3.76e-6 & 5.65e-11 \\
32 +(1,3) & exact & 3 & 2.89e-13 & 3.11e-13 \\
33 +(1,2,4) & exact & 0 & 2.100 & 0.312 \\
34 34 (1,2,4) & exact & 1 & 0.002 & 6.55e-5 \\
35 −(1,2,4) & exact & 2 & 2.82e-9 & 5.44e-12 \\
36 −(1,2,4) & exact & 3 & 3.18e-13 & 3.14e-13 \\
37 −(1,2,4) & stale & 1 & 0.083 & 0.003 \\
35 +(1,2,4) & exact & 2 & 3.07e-9 & 5.44e-12 \\
36 +(1,2,4) & exact & 3 & 2.93e-13 & 3.14e-13 \\
37 +(1,2,4) & stale & 1 & 0.086 & 0.003 \\
38 38 (1,2,4) & stale & 2 & 0.003 & 3.32e-5 \\
39 −(1,2,4) & stale & 3 & 1.33e-4 & 3.43e-7 \\
39 +(1,2,4) & stale & 3 & 1.38e-4 & 3.43e-7 \\
40 40 (1,2,4) & single & 1 & 0.002 & 6.55e-5 \\
41 −(1,2,4) & single & 2 & 2.82e-9 & 5.44e-12 \\
42 −(1,2,4) & single & 3 & 3.18e-13 & 3.14e-13 \\
43 −(1,2,3) & exact & 0 & 1.647 & 0.429 \\
41 +(1,2,4) & single & 2 & 3.07e-9 & 5.44e-12 \\
42 +(1,2,4) & single & 3 & 2.93e-13 & 3.14e-13 \\
43 +(1,2,3) & exact & 0 & 1.697 & 0.429 \\
44 44 (1,2,3) & exact & 1 & 0.002 & 1.30e-4 \\
45 −(1,2,3) & exact & 2 & 3.09e-9 & 2.25e-11 \\
46 −(1,2,3) & exact & 3 & 3.08e-13 & 3.10e-13 \\
47 −(1,2,4,8) & exact & 0 & 1.395 & 0.380 \\
48 −(1,2,4,8) & exact & 1 & 0.001 & 9.80e-5 \\
49 −(1,2,4,8) & exact & 2 & 1.01e-9 & 1.20e-11 \\
50 −(1,2,4,8) & exact & 3 & 3.11e-13 & 3.13e-13 \\
51 −(1,2,3,4) & exact & 0 & 2.247 & 0.957 \\
52 −(1,2,3,4) & exact & 1 & 0.003 & 6.46e-4 \\
53 −(1,2,3,4) & exact & 2 & 1.11e-8 & 6.13e-10 \\
54 −(1,2,3,4) & exact & 3 & 3.04e-13 & 3.10e-13 \\
45 +(1,2,3) & exact & 2 & 3.23e-9 & 2.25e-11 \\
46 +(1,2,3) & exact & 3 & 3.03e-13 & 3.10e-13 \\
47 +(1,2,4,8) & exact & 0 & 1.302 & 0.380 \\
48 +(1,2,4,8) & exact & 1 & 9.81e-4 & 9.80e-5 \\
49 +(1,2,4,8) & exact & 2 & 8.24e-10 & 1.20e-11 \\
50 +(1,2,4,8) & exact & 3 & 2.93e-13 & 3.13e-13 \\
51 +(1,2,3,4) & exact & 0 & 2.411 & 0.957 \\
52 +(1,2,3,4) & exact & 1 & 0.004 & 6.46e-4 \\
53 +(1,2,3,4) & exact & 2 & 1.96e-8 & 6.13e-10 \\
54 +(1,2,3,4) & exact & 3 & 3.01e-13 & 3.10e-13 \\
55 55 \midrule
56 56 (1) & $b$-bit Hessian, $b=2$ & 1 & 4.546 & 0.277 \\
57 −(1) & $b$-bit Hessian, $b=3$ & 1 & 10.382 & 0.277 \\
58 −(1) & $b$-bit Hessian, $b=4$ & 1 & 2.422 & 0.277 \\
59 −(1) & $b$-bit Hessian, $b=6$ & 1 & 4.311 & 0.140 \\
60 −(1) & $b$-bit Hessian, $b=8$ & 1 & 4.779 & 0.266 \\
61 −(1) & $b$-bit Hessian, $b=12$ & 1 & 4.740 & 0.278 \\
62 −(1) & $b$-bit Hessian, $b=16$ & 1 & 4.740 & 0.278 \\
63 −(1) & $b$-bit Hessian, $b=24$ & 1 & 4.740 & 0.278 \\
64 −(1) & $b$-bit Hessian, $b=52$ & 1 & 4.740 & 0.278 \\
65 −(1) & $b$-bit score, $b=2$ & 1 & 18.990 & 3.612 \\
66 −(1) & $b$-bit score, $b=3$ & 1 & 2.371 & 1.401 \\
67 −(1) & $b$-bit score, $b=4$ & 1 & 8.324 & 1.115 \\
68 −(1) & $b$-bit score, $b=6$ & 1 & 5.381 & 0.380 \\
69 −(1) & $b$-bit score, $b=8$ & 1 & 4.742 & 0.283 \\
70 −(1) & $b$-bit score, $b=12$ & 1 & 4.738 & 0.278 \\
71 −(1) & $b$-bit score, $b=16$ & 1 & 4.740 & 0.278 \\
72 −(1) & $b$-bit score, $b=24$ & 1 & 4.740 & 0.278 \\
73 −(1) & $b$-bit score, $b=52$ & 1 & 4.740 & 0.278 \\
74 −(1) & $b$-bit both, $b=2$ & 1 & 8.546 & 2.990 \\
75 −(1) & $b$-bit both, $b=3$ & 1 & 2.959 & 1.919 \\
76 −(1) & $b$-bit both, $b=4$ & 1 & 5.936 & 0.561 \\
77 −(1) & $b$-bit both, $b=6$ & 1 & 4.952 & 0.268 \\
78 −(1) & $b$-bit both, $b=8$ & 1 & 4.780 & 0.271 \\
79 −(1) & $b$-bit both, $b=12$ & 1 & 4.738 & 0.278 \\
80 −(1) & $b$-bit both, $b=16$ & 1 & 4.740 & 0.278 \\
81 −(1) & $b$-bit both, $b=24$ & 1 & 4.740 & 0.278 \\
82 −(1) & $b$-bit both, $b=52$ & 1 & 4.740 & 0.278 \\
57 +(1) & $b$-bit Hessian, $b=3$ & 1 & 10.384 & 0.277 \\
58 +(1) & $b$-bit Hessian, $b=4$ & 1 & 2.423 & 0.277 \\
59 +(1) & $b$-bit Hessian, $b=6$ & 1 & 4.312 & 0.140 \\
60 +(1) & $b$-bit Hessian, $b=8$ & 1 & 4.778 & 0.266 \\
61 +(1) & $b$-bit Hessian, $b=12$ & 1 & 4.741 & 0.278 \\
62 +(1) & $b$-bit Hessian, $b=16$ & 1 & 4.741 & 0.278 \\
63 +(1) & $b$-bit Hessian, $b=24$ & 1 & 4.741 & 0.278 \\
64 +(1) & $b$-bit Hessian, $b=52$ & 1 & 4.741 & 0.278 \\
65 +(1) & $b$-bit score, $b=2$ & 1 & 18.981 & 3.612 \\
66 +(1) & $b$-bit score, $b=3$ & 1 & 2.378 & 1.401 \\
67 +(1) & $b$-bit score, $b=4$ & 1 & 8.316 & 1.115 \\
68 +(1) & $b$-bit score, $b=6$ & 1 & 5.450 & 0.380 \\
69 +(1) & $b$-bit score, $b=8$ & 1 & 4.729 & 0.283 \\
70 +(1) & $b$-bit score, $b=12$ & 1 & 4.740 & 0.278 \\
71 +(1) & $b$-bit score, $b=16$ & 1 & 4.741 & 0.278 \\
72 +(1) & $b$-bit score, $b=24$ & 1 & 4.741 & 0.278 \\
73 +(1) & $b$-bit score, $b=52$ & 1 & 4.741 & 0.278 \\
74 +(1) & $b$-bit both, $b=2$ & 1 & 8.538 & 2.990 \\
75 +(1) & $b$-bit both, $b=3$ & 1 & 2.952 & 1.919 \\
76 +(1) & $b$-bit both, $b=4$ & 1 & 5.928 & 0.561 \\
77 +(1) & $b$-bit both, $b=6$ & 1 & 5.020 & 0.268 \\
78 +(1) & $b$-bit both, $b=8$ & 1 & 4.767 & 0.271 \\
79 +(1) & $b$-bit both, $b=12$ & 1 & 4.740 & 0.278 \\
80 +(1) & $b$-bit both, $b=16$ & 1 & 4.741 & 0.278 \\
81 +(1) & $b$-bit both, $b=24$ & 1 & 4.741 & 0.278 \\
82 +(1) & $b$-bit both, $b=52$ & 1 & 4.741 & 0.278 \\
83 83 (1,2) & $b$-bit Hessian, $b=2$ & 1 & 0.040 & 5.01e-4 \\
84 84 (1,2) & $b$-bit Hessian, $b=3$ & 1 & 0.040 & 5.01e-4 \\
85 85 (1,2) & $b$-bit Hessian, $b=4$ & 1 & 0.040 & 5.01e-4 \\
86 86 (1,2) & $b$-bit Hessian, $b=6$ & 1 & 0.040 & 5.01e-4 \\
87 87 (1,2) & $b$-bit Hessian, $b=8$ & 1 & 0.039 & 5.01e-4 \\
88 88 (1,2) & $b$-bit Hessian, $b=12$ & 1 & 0.040 & 1.89e-4 \\
89 −(1,2) & $b$-bit Hessian, $b=16$ & 1 & 0.040 & 1.77e-4 \\
90 −(1,2) & $b$-bit Hessian, $b=24$ & 1 & 0.040 & 1.77e-4 \\
91 −(1,2) & $b$-bit Hessian, $b=52$ & 1 & 0.040 & 1.77e-4 \\
92 −(1,2) & $b$-bit score, $b=2$ & 1 & 0.521 & 0.064 \\
93 −(1,2) & $b$-bit score, $b=3$ & 1 & 0.498 & 0.032 \\
94 −(1,2) & $b$-bit score, $b=4$ & 1 & 0.314 & 0.016 \\
95 −(1,2) & $b$-bit score, $b=6$ & 1 & 0.084 & 0.004 \\
96 −(1,2) & $b$-bit score, $b=8$ & 1 & 0.045 & 0.001 \\
89 +(1,2) & $b$-bit Hessian, $b=16$ & 1 & 0.039 & 1.77e-4 \\
90 +(1,2) & $b$-bit Hessian, $b=24$ & 1 & 0.039 & 1.77e-4 \\
91 +(1,2) & $b$-bit Hessian, $b=52$ & 1 & 0.039 & 1.77e-4 \\
92 +(1,2) & $b$-bit score, $b=2$ & 1 & 0.503 & 0.064 \\
93 +(1,2) & $b$-bit score, $b=3$ & 1 & 0.471 & 0.032 \\
94 +(1,2) & $b$-bit score, $b=4$ & 1 & 0.311 & 0.016 \\
95 +(1,2) & $b$-bit score, $b=6$ & 1 & 0.088 & 0.004 \\
96 +(1,2) & $b$-bit score, $b=8$ & 1 & 0.042 & 0.001 \\
97 97 (1,2) & $b$-bit score, $b=12$ & 1 & 0.040 & 1.91e-4 \\
98 −(1,2) & $b$-bit score, $b=16$ & 1 & 0.040 & 1.77e-4 \\
99 −(1,2) & $b$-bit score, $b=24$ & 1 & 0.040 & 1.77e-4 \\
100 −(1,2) & $b$-bit score, $b=52$ & 1 & 0.040 & 1.77e-4 \\
101 −(1,2) & $b$-bit both, $b=2$ & 1 & 0.489 & 0.064 \\
102 −(1,2) & $b$-bit both, $b=3$ & 1 & 0.456 & 0.032 \\
103 −(1,2) & $b$-bit both, $b=4$ & 1 & 0.323 & 0.016 \\
104 −(1,2) & $b$-bit both, $b=6$ & 1 & 0.084 & 0.004 \\
105 −(1,2) & $b$-bit both, $b=8$ & 1 & 0.044 & 0.001 \\
98 +(1,2) & $b$-bit score, $b=16$ & 1 & 0.039 & 1.77e-4 \\
99 +(1,2) & $b$-bit score, $b=24$ & 1 & 0.039 & 1.77e-4 \\
100 +(1,2) & $b$-bit score, $b=52$ & 1 & 0.039 & 1.77e-4 \\
101 +(1,2) & $b$-bit both, $b=2$ & 1 & 0.473 & 0.064 \\
102 +(1,2) & $b$-bit both, $b=3$ & 1 & 0.430 & 0.032 \\
103 +(1,2) & $b$-bit both, $b=4$ & 1 & 0.312 & 0.016 \\
104 +(1,2) & $b$-bit both, $b=6$ & 1 & 0.081 & 0.004 \\
105 +(1,2) & $b$-bit both, $b=8$ & 1 & 0.041 & 0.001 \\
106 106 (1,2) & $b$-bit both, $b=12$ & 1 & 0.040 & 2.01e-4 \\
107 −(1,2) & $b$-bit both, $b=16$ & 1 & 0.040 & 1.77e-4 \\
108 −(1,2) & $b$-bit both, $b=24$ & 1 & 0.040 & 1.77e-4 \\
109 −(1,2) & $b$-bit both, $b=52$ & 1 & 0.040 & 1.77e-4 \\
110 −(1,2,4) & $b$-bit Hessian, $b=2$ & 1 & 0.002 & 2.57e-4 \\
111 −(1,2,4) & $b$-bit Hessian, $b=3$ & 1 & 0.002 & 2.57e-4 \\
112 −(1,2,4) & $b$-bit Hessian, $b=4$ & 1 & 0.002 & 2.57e-4 \\
113 −(1,2,4) & $b$-bit Hessian, $b=6$ & 1 & 0.002 & 2.57e-4 \\
107 +(1,2) & $b$-bit both, $b=16$ & 1 & 0.039 & 1.77e-4 \\
108 +(1,2) & $b$-bit both, $b=24$ & 1 & 0.039 & 1.77e-4 \\
109 +(1,2) & $b$-bit both, $b=52$ & 1 & 0.039 & 1.77e-4 \\
110 +(1,2,4) & $b$-bit Hessian, $b=2$ & 1 & 0.003 & 2.57e-4 \\
111 +(1,2,4) & $b$-bit Hessian, $b=3$ & 1 & 0.003 & 2.57e-4 \\
112 +(1,2,4) & $b$-bit Hessian, $b=4$ & 1 & 0.003 & 2.57e-4 \\
113 +(1,2,4) & $b$-bit Hessian, $b=6$ & 1 & 0.003 & 2.57e-4 \\
114 114 (1,2,4) & $b$-bit Hessian, $b=8$ & 1 & 0.004 & 2.54e-4 \\
115 115 (1,2,4) & $b$-bit Hessian, $b=12$ & 1 & 0.002 & 7.28e-5 \\
116 116 (1,2,4) & $b$-bit Hessian, $b=16$ & 1 & 0.002 & 6.58e-5 \\
117 117 (1,2,4) & $b$-bit Hessian, $b=24$ & 1 & 0.002 & 6.55e-5 \\
118 118 (1,2,4) & $b$-bit Hessian, $b=52$ & 1 & 0.002 & 6.55e-5 \\
119 −(1,2,4) & $b$-bit score, $b=2$ & 1 & 0.194 & 0.033 \\
120 −(1,2,4) & $b$-bit score, $b=3$ & 1 & 0.107 & 0.016 \\
121 −(1,2,4) & $b$-bit score, $b=4$ & 1 & 0.048 & 0.009 \\
119 +(1,2,4) & $b$-bit score, $b=2$ & 1 & 0.213 & 0.033 \\
120 +(1,2,4) & $b$-bit score, $b=3$ & 1 & 0.106 & 0.016 \\
121 +(1,2,4) & $b$-bit score, $b=4$ & 1 & 0.055 & 0.009 \\
122 122 (1,2,4) & $b$-bit score, $b=6$ & 1 & 0.014 & 0.002 \\
123 123 (1,2,4) & $b$-bit score, $b=8$ & 1 & 0.004 & 5.51e-4 \\
124 124 (1,2,4) & $b$-bit score, $b=12$ & 1 & 0.002 & 6.97e-5 \\
125 125 (1,2,4) & $b$-bit score, $b=16$ & 1 & 0.002 & 6.55e-5 \\
126 126 (1,2,4) & $b$-bit score, $b=24$ & 1 & 0.002 & 6.55e-5 \\
127 127 (1,2,4) & $b$-bit score, $b=52$ & 1 & 0.002 & 6.55e-5 \\
128 −(1,2,4) & $b$-bit both, $b=2$ & 1 & 0.194 & 0.033 \\
129 −(1,2,4) & $b$-bit both, $b=3$ & 1 & 0.107 & 0.016 \\
130 −(1,2,4) & $b$-bit both, $b=4$ & 1 & 0.048 & 0.009 \\
128 +(1,2,4) & $b$-bit both, $b=2$ & 1 & 0.214 & 0.033 \\
129 +(1,2,4) & $b$-bit both, $b=3$ & 1 & 0.106 & 0.016 \\
130 +(1,2,4) & $b$-bit both, $b=4$ & 1 & 0.055 & 0.009 \\
131 131 (1,2,4) & $b$-bit both, $b=6$ & 1 & 0.014 & 0.002 \\
132 132 (1,2,4) & $b$-bit both, $b=8$ & 1 & 0.005 & 6.03e-4 \\
133 133 (1,2,4) & $b$-bit both, $b=12$ & 1 & 0.002 & 7.66e-5 \\
@@ -137,7 +137,7 @@ Pattern & curvature & $q$ & $m = 24$ & $m = 96$ \\
137 137 \bottomrule
138 138 \end{tabular}
139 139 \begin{tablenotes}\footnotesize
140 −\item 1000 paired replications per column; $K = N/m$. Rows are omitted when the pattern does not divide $m$. Source: \texttt{results/processed/ablation\_exponential\_summary.csv}.
140 +\item 300--1000 paired replications per column (exact count per cell in the processed CSV); $K = N/m$. Rows are omitted when the pattern does not divide $m$. Source: \texttt{results/processed/ablation\_exponential\_summary.csv}.
141 141 \end{tablenotes}
142 142 \end{threeparttable}
143 143 \end{table}
modified paper/tables/abl_logistic.tex +130 −130
@@ -1,143 +1,143 @@
1 1 \begin{table}[p]
2 2 \centering\scriptsize
3 3 \begin{threeparttable}
4 −\caption{Ablation (logistic, $N = 196,608$): RMS of $\sqrt N\,\lVert\tilde\theta - \widehat\theta_N\rVert$ by split pattern, order $r$, Newton rounds $q$ and curvature used (exact / stale averaged local / single machine); quantized exact curvature with $b$ mantissa bits for $q = 1$.}\label{tab:abl_logistic}
4 +\caption{Ablation (logistic, $N = 786,432$): RMS of $\sqrt N\,\lVert\tilde\theta - \widehat\theta_N\rVert$ by split pattern, order $r$, Newton rounds $q$ and curvature used (exact / stale averaged local / single machine); quantized exact curvature with $b$ mantissa bits for $q = 1$.}\label{tab:abl_logistic}
5 5 \begin{tabular}{@{}llrrr@{}}
6 6 \toprule
7 −Pattern & curvature & $q$ & $m = 96$ & $m = 192$ \\
7 +Pattern & curvature & $q$ & $m = 192$ & $m = 768$ \\
8 8 \midrule
9 −(1) & exact & 0 & 57.779 & 26.208 \\
10 −(1) & exact & 1 & 3.396 & 0.680 \\
11 −(1) & exact & 2 & 0.011 & 4.48e-4 \\
12 −(1) & exact & 3 & 1.21e-7 & 1.99e-10 \\
13 −(1) & stale & 1 & 1.319 & 0.310 \\
14 −(1) & stale & 2 & 0.111 & 0.012 \\
15 −(1) & stale & 3 & 0.009 & 4.86e-4 \\
16 −(1) & single & 1 & 17.164 & 4.707 \\
17 −(1) & single & 2 & 11.647 & 1.777 \\
18 −(1) & single & 3 & 11.038 & 0.816 \\
19 −(1,2) & exact & 0 & 3271.882 & 5.903 \\
20 −(1,2) & exact & 1 & 2.84e+7 & 0.034 \\
21 −(1,2) & exact & 2 & 3.78e+29 & 1.32e-6 \\
22 −(1,2) & exact & 3 & 3.78e+29 & 6.34e-14 \\
23 −(1,2) & stale & 1 & 3146.098 & 0.268 \\
24 −(1,2) & stale & 2 & 3040.887 & 0.011 \\
25 −(1,2) & stale & 3 & 2939.939 & 4.70e-4 \\
26 −(1,2) & single & 1 & 1.98e+9 & 1.089 \\
27 −(1,2) & single & 2 & 3.02e+24 & 0.419 \\
28 −(1,2) & single & 3 & 2.31e+38 & 0.190 \\
29 −(1,3) & exact & 0 & 7569.958 & 11.668 \\
30 −(1,3) & exact & 1 & 1.56e+8 & 0.373 \\
31 −(1,3) & exact & 2 & 5.99e+46 & 0.002 \\
32 −(1,3) & exact & 3 & 3.63e+151 & 6.37e-8 \\
33 −(1,2,4) & exact & 0 & 2.55e+4 & 165.492 \\
34 −(1,2,4) & exact & 1 & 2.81e+9 & 708.579 \\
35 −(1,2,4) & exact & 2 & 4.00e+17 & 2.84e+5 \\
36 −(1,2,4) & exact & 3 & 4.12e+100 & 1.01e+13 \\
37 −(1,2,4) & stale & 1 & 2.52e+4 & 87.316 \\
38 −(1,2,4) & stale & 2 & 2.49e+4 & 53.541 \\
39 −(1,2,4) & stale & 3 & 2.46e+4 & 29.429 \\
40 −(1,2,4) & single & 1 & 1.55e+26 & 657.174 \\
41 −(1,2,4) & single & 2 & 4.16e+139 & 4.48e+5 \\
42 −(1,2,4) & single & 3 & 4.18e+139 & 4.78e+21 \\
43 −(1,2,3) & exact & 0 & 1.76e+4 & 12.815 \\
44 −(1,2,3) & exact & 1 & 9.80e+8 & 1.688 \\
45 −(1,2,3) & exact & 2 & 1.20e+23 & 0.043 \\
46 −(1,2,3) & exact & 3 & 3.78e+143 & 3.45e-5 \\
47 −(1,2,4,8) & exact & 0 & 5.00e+4 & 3158.571 \\
48 −(1,2,4,8) & exact & 1 & 2.43e+10 & 1.05e+7 \\
49 −(1,2,4,8) & exact & 2 & 4.24e+58 & 4.53e+24 \\
50 −(1,2,4,8) & exact & 3 & 4.24e+58 & 8.65e+43 \\
51 −(1,2,3,4) & exact & 0 & 8.61e+4 & 494.098 \\
52 −(1,2,3,4) & exact & 1 & 1.42e+11 & 2.60e+4 \\
53 −(1,2,3,4) & exact & 2 & 3.11e+32 & 7.27e+9 \\
54 −(1,2,3,4) & exact & 3 & 3.97e+140 & 4.44e+11 \\
9 +(1) & exact & 0 & 52.268 & 12.296 \\
10 +(1) & exact & 1 & 1.350 & 0.073 \\
11 +(1) & exact & 2 & 8.80e-4 & 2.61e-6 \\
12 +(1) & exact & 3 & 3.75e-10 & 1.27e-13 \\
13 +(1) & stale & 1 & 0.615 & 0.036 \\
14 +(1) & stale & 2 & 0.024 & 3.32e-4 \\
15 +(1) & stale & 3 & 9.10e-4 & 3.14e-6 \\
16 +(1) & single & 1 & 9.113 & 1.013 \\
17 +(1) & single & 2 & 3.342 & 0.167 \\
18 +(1) & single & 3 & 1.538 & 0.030 \\
19 +(1,2) & exact & 0 & 11.228 & 1.167 \\
20 +(1,2) & exact & 1 & 0.061 & 5.63e-4 \\
21 +(1,2) & exact & 2 & 1.91e-6 & 2.41e-10 \\
22 +(1,2) & exact & 3 & 1.30e-13 & 1.27e-13 \\
23 +(1,2) & stale & 1 & 0.490 & 0.014 \\
24 +(1,2) & stale & 2 & 0.019 & 1.62e-4 \\
25 +(1,2) & stale & 3 & 7.41e-4 & 1.98e-6 \\
26 +(1,2) & single & 1 & 1.900 & 0.121 \\
27 +(1,2) & single & 2 & 0.710 & 0.020 \\
28 +(1,2) & single & 3 & 0.336 & 0.004 \\
29 +(1,3) & exact & 0 & 23.360 & 1.201 \\
30 +(1,3) & exact & 1 & 0.735 & 6.83e-4 \\
31 +(1,3) & exact & 2 & 0.004 & 3.61e-10 \\
32 +(1,3) & exact & 3 & 1.39e-7 & 1.27e-13 \\
33 +(1,2,4) & exact & 0 & 267.576 & 1.511 \\
34 +(1,2,4) & exact & 1 & 1410.845 & 8.22e-4 \\
35 +(1,2,4) & exact & 2 & 5.77e+5 & 5.37e-10 \\
36 +(1,2,4) & exact & 3 & 1.55e+13 & 1.27e-13 \\
37 +(1,2,4) & stale & 1 & 167.463 & 0.018 \\
38 +(1,2,4) & stale & 2 & 112.549 & 2.21e-4 \\
39 +(1,2,4) & stale & 3 & 64.138 & 2.76e-6 \\
40 +(1,2,4) & single & 1 & 1415.946 & 0.167 \\
41 +(1,2,4) & single & 2 & 4.37e+5 & 0.028 \\
42 +(1,2,4) & single & 3 & 7.63e+94 & 0.006 \\
43 +(1,2,3) & exact & 0 & 23.384 & 2.154 \\
44 +(1,2,3) & exact & 1 & 2.991 & 0.002 \\
45 +(1,2,3) & exact & 2 & 0.073 & 2.21e-9 \\
46 +(1,2,3) & exact & 3 & 4.99e-5 & 1.28e-13 \\
47 +(1,2,4,8) & exact & 0 & 3530.386 & 1.864 \\
48 +(1,2,4,8) & exact & 1 & 8.08e+5 & 0.001 \\
49 +(1,2,4,8) & exact & 2 & 4.30e+13 & 1.18e-9 \\
50 +(1,2,4,8) & exact & 3 & 7.62e+39 & 1.28e-13 \\
51 +(1,2,3,4) & exact & 0 & 792.244 & 4.986 \\
52 +(1,2,3,4) & exact & 1 & 5.62e+4 & 0.009 \\
53 +(1,2,3,4) & exact & 2 & 1.55e+10 & 5.93e-8 \\
54 +(1,2,3,4) & exact & 3 & 1.55e+10 & 1.27e-13 \\
55 55 \midrule
56 −(1) & $b$-bit Hessian, $b=2$ & 1 & 3.379 & 1.711 \\
57 −(1) & $b$-bit Hessian, $b=3$ & 1 & 3.561 & 1.679 \\
58 −(1) & $b$-bit Hessian, $b=4$ & 1 & 3.459 & 0.988 \\
59 −(1) & $b$-bit Hessian, $b=6$ & 1 & 3.487 & 0.714 \\
60 −(1) & $b$-bit Hessian, $b=8$ & 1 & 3.402 & 0.681 \\
61 −(1) & $b$-bit Hessian, $b=12$ & 1 & 3.396 & 0.680 \\
62 −(1) & $b$-bit Hessian, $b=16$ & 1 & 3.396 & 0.680 \\
63 −(1) & $b$-bit Hessian, $b=24$ & 1 & 3.396 & 0.680 \\
64 −(1) & $b$-bit Hessian, $b=52$ & 1 & 3.396 & 0.680 \\
65 −(1) & $b$-bit score, $b=2$ & 1 & 4.349 & 1.865 \\
66 −(1) & $b$-bit score, $b=3$ & 1 & 4.109 & 1.155 \\
67 −(1) & $b$-bit score, $b=4$ & 1 & 3.566 & 0.836 \\
68 −(1) & $b$-bit score, $b=6$ & 1 & 3.403 & 0.692 \\
69 −(1) & $b$-bit score, $b=8$ & 1 & 3.397 & 0.679 \\
70 −(1) & $b$-bit score, $b=12$ & 1 & 3.396 & 0.679 \\
71 −(1) & $b$-bit score, $b=16$ & 1 & 3.396 & 0.680 \\
72 −(1) & $b$-bit score, $b=24$ & 1 & 3.396 & 0.680 \\
73 −(1) & $b$-bit score, $b=52$ & 1 & 3.396 & 0.680 \\
74 −(1) & $b$-bit both, $b=2$ & 1 & 4.723 & 2.359 \\
75 −(1) & $b$-bit both, $b=3$ & 1 & 4.292 & 1.907 \\
76 −(1) & $b$-bit both, $b=4$ & 1 & 3.621 & 1.107 \\
77 −(1) & $b$-bit both, $b=6$ & 1 & 3.493 & 0.727 \\
78 −(1) & $b$-bit both, $b=8$ & 1 & 3.403 & 0.680 \\
79 −(1) & $b$-bit both, $b=12$ & 1 & 3.396 & 0.679 \\
80 −(1) & $b$-bit both, $b=16$ & 1 & 3.396 & 0.680 \\
81 −(1) & $b$-bit both, $b=24$ & 1 & 3.396 & 0.680 \\
82 −(1) & $b$-bit both, $b=52$ & 1 & 3.396 & 0.680 \\
83 −(1,2) & $b$-bit Hessian, $b=2$ & 1 & 3.87e+5 & 0.377 \\
84 −(1,2) & $b$-bit Hessian, $b=3$ & 1 & 2.88e+5 & 0.338 \\
85 −(1,2) & $b$-bit Hessian, $b=4$ & 1 & 4.23e+5 & 0.141 \\
86 −(1,2) & $b$-bit Hessian, $b=6$ & 1 & 1.10e+6 & 0.053 \\
87 −(1,2) & $b$-bit Hessian, $b=8$ & 1 & 1.14e+7 & 0.035 \\
88 −(1,2) & $b$-bit Hessian, $b=12$ & 1 & 4.41e+7 & 0.034 \\
89 −(1,2) & $b$-bit Hessian, $b=16$ & 1 & 2.85e+7 & 0.034 \\
90 −(1,2) & $b$-bit Hessian, $b=24$ & 1 & 2.84e+7 & 0.034 \\
91 −(1,2) & $b$-bit Hessian, $b=52$ & 1 & 2.84e+7 & 0.034 \\
92 −(1,2) & $b$-bit score, $b=2$ & 1 & 2.70e+7 & 0.489 \\
93 −(1,2) & $b$-bit score, $b=3$ & 1 & 2.82e+7 & 0.254 \\
94 −(1,2) & $b$-bit score, $b=4$ & 1 & 2.82e+7 & 0.128 \\
95 −(1,2) & $b$-bit score, $b=6$ & 1 & 2.86e+7 & 0.047 \\
96 −(1,2) & $b$-bit score, $b=8$ & 1 & 2.84e+7 & 0.035 \\
97 −(1,2) & $b$-bit score, $b=12$ & 1 & 2.84e+7 & 0.034 \\
98 −(1,2) & $b$-bit score, $b=16$ & 1 & 2.84e+7 & 0.034 \\
99 −(1,2) & $b$-bit score, $b=24$ & 1 & 2.84e+7 & 0.034 \\
100 −(1,2) & $b$-bit score, $b=52$ & 1 & 2.84e+7 & 0.034 \\
101 −(1,2) & $b$-bit both, $b=2$ & 1 & 3.67e+5 & 0.596 \\
102 −(1,2) & $b$-bit both, $b=3$ & 1 & 2.86e+5 & 0.412 \\
103 −(1,2) & $b$-bit both, $b=4$ & 1 & 4.19e+5 & 0.189 \\
104 −(1,2) & $b$-bit both, $b=6$ & 1 & 1.10e+6 & 0.062 \\
105 −(1,2) & $b$-bit both, $b=8$ & 1 & 1.14e+7 & 0.036 \\
106 −(1,2) & $b$-bit both, $b=12$ & 1 & 4.41e+7 & 0.034 \\
107 −(1,2) & $b$-bit both, $b=16$ & 1 & 2.85e+7 & 0.034 \\
108 −(1,2) & $b$-bit both, $b=24$ & 1 & 2.84e+7 & 0.034 \\
109 −(1,2) & $b$-bit both, $b=52$ & 1 & 2.84e+7 & 0.034 \\
110 −(1,2,4) & $b$-bit Hessian, $b=2$ & 1 & 5.83e+6 & 513.109 \\
111 −(1,2,4) & $b$-bit Hessian, $b=3$ & 1 & 2.51e+7 & 553.804 \\
112 −(1,2,4) & $b$-bit Hessian, $b=4$ & 1 & 8.40e+7 & 770.186 \\
113 −(1,2,4) & $b$-bit Hessian, $b=6$ & 1 & 1.29e+7 & 690.742 \\
114 −(1,2,4) & $b$-bit Hessian, $b=8$ & 1 & 5.97e+7 & 707.712 \\
115 −(1,2,4) & $b$-bit Hessian, $b=12$ & 1 & 5.29e+8 & 708.627 \\
116 −(1,2,4) & $b$-bit Hessian, $b=16$ & 1 & 3.48e+9 & 708.586 \\
117 −(1,2,4) & $b$-bit Hessian, $b=24$ & 1 & 2.81e+9 & 708.579 \\
118 −(1,2,4) & $b$-bit Hessian, $b=52$ & 1 & 2.81e+9 & 708.579 \\
119 −(1,2,4) & $b$-bit score, $b=2$ & 1 & 2.70e+9 & 723.882 \\
120 −(1,2,4) & $b$-bit score, $b=3$ & 1 & 2.76e+9 & 723.868 \\
121 −(1,2,4) & $b$-bit score, $b=4$ & 1 & 2.76e+9 & 729.492 \\
122 −(1,2,4) & $b$-bit score, $b=6$ & 1 & 2.82e+9 & 706.637 \\
123 −(1,2,4) & $b$-bit score, $b=8$ & 1 & 2.81e+9 & 709.441 \\
124 −(1,2,4) & $b$-bit score, $b=12$ & 1 & 2.81e+9 & 708.518 \\
125 −(1,2,4) & $b$-bit score, $b=16$ & 1 & 2.81e+9 & 708.584 \\
126 −(1,2,4) & $b$-bit score, $b=24$ & 1 & 2.81e+9 & 708.579 \\
127 −(1,2,4) & $b$-bit score, $b=52$ & 1 & 2.81e+9 & 708.579 \\
128 −(1,2,4) & $b$-bit both, $b=2$ & 1 & 5.73e+6 & 525.460 \\
129 −(1,2,4) & $b$-bit both, $b=3$ & 1 & 2.55e+7 & 566.215 \\
130 −(1,2,4) & $b$-bit both, $b=4$ & 1 & 8.34e+7 & 792.684 \\
131 −(1,2,4) & $b$-bit both, $b=6$ & 1 & 1.29e+7 & 688.842 \\
132 −(1,2,4) & $b$-bit both, $b=8$ & 1 & 5.98e+7 & 708.573 \\
133 −(1,2,4) & $b$-bit both, $b=12$ & 1 & 5.29e+8 & 708.567 \\
134 −(1,2,4) & $b$-bit both, $b=16$ & 1 & 3.48e+9 & 708.591 \\
135 −(1,2,4) & $b$-bit both, $b=24$ & 1 & 2.81e+9 & 708.579 \\
136 −(1,2,4) & $b$-bit both, $b=52$ & 1 & 2.81e+9 & 708.579 \\
56 +(1) & $b$-bit Hessian, $b=2$ & 1 & 3.520 & 0.759 \\
57 +(1) & $b$-bit Hessian, $b=3$ & 1 & 3.313 & 0.682 \\
58 +(1) & $b$-bit Hessian, $b=4$ & 1 & 1.939 & 0.306 \\
59 +(1) & $b$-bit Hessian, $b=6$ & 1 & 1.412 & 0.142 \\
60 +(1) & $b$-bit Hessian, $b=8$ & 1 & 1.351 & 0.077 \\
61 +(1) & $b$-bit Hessian, $b=12$ & 1 & 1.350 & 0.073 \\
62 +(1) & $b$-bit Hessian, $b=16$ & 1 & 1.350 & 0.073 \\
63 +(1) & $b$-bit Hessian, $b=24$ & 1 & 1.350 & 0.073 \\
64 +(1) & $b$-bit Hessian, $b=52$ & 1 & 1.350 & 0.073 \\
65 +(1) & $b$-bit score, $b=2$ & 1 & 3.663 & 0.861 \\
66 +(1) & $b$-bit score, $b=3$ & 1 & 2.006 & 0.446 \\
67 +(1) & $b$-bit score, $b=4$ & 1 & 1.626 & 0.241 \\
68 +(1) & $b$-bit score, $b=6$ & 1 & 1.375 & 0.095 \\
69 +(1) & $b$-bit score, $b=8$ & 1 & 1.352 & 0.075 \\
70 +(1) & $b$-bit score, $b=12$ & 1 & 1.350 & 0.073 \\
71 +(1) & $b$-bit score, $b=16$ & 1 & 1.350 & 0.073 \\
72 +(1) & $b$-bit score, $b=24$ & 1 & 1.350 & 0.073 \\
73 +(1) & $b$-bit score, $b=52$ & 1 & 1.350 & 0.073 \\
74 +(1) & $b$-bit both, $b=2$ & 1 & 4.782 & 1.133 \\
75 +(1) & $b$-bit both, $b=3$ & 1 & 3.480 & 0.791 \\
76 +(1) & $b$-bit both, $b=4$ & 1 & 2.180 & 0.382 \\
77 +(1) & $b$-bit both, $b=6$ & 1 & 1.440 & 0.154 \\
78 +(1) & $b$-bit both, $b=8$ & 1 & 1.353 & 0.079 \\
79 +(1) & $b$-bit both, $b=12$ & 1 & 1.350 & 0.073 \\
80 +(1) & $b$-bit both, $b=16$ & 1 & 1.350 & 0.073 \\
81 +(1) & $b$-bit both, $b=24$ & 1 & 1.350 & 0.073 \\
82 +(1) & $b$-bit both, $b=52$ & 1 & 1.350 & 0.073 \\
83 +(1,2) & $b$-bit Hessian, $b=2$ & 1 & 0.714 & 0.072 \\
84 +(1,2) & $b$-bit Hessian, $b=3$ & 1 & 0.654 & 0.066 \\
85 +(1,2) & $b$-bit Hessian, $b=4$ & 1 & 0.256 & 0.027 \\
86 +(1,2) & $b$-bit Hessian, $b=6$ & 1 & 0.099 & 0.008 \\
87 +(1,2) & $b$-bit Hessian, $b=8$ & 1 & 0.063 & 0.002 \\
88 +(1,2) & $b$-bit Hessian, $b=12$ & 1 & 0.061 & 5.76e-4 \\
89 +(1,2) & $b$-bit Hessian, $b=16$ & 1 & 0.061 & 5.63e-4 \\
90 +(1,2) & $b$-bit Hessian, $b=24$ & 1 & 0.061 & 5.63e-4 \\
91 +(1,2) & $b$-bit Hessian, $b=52$ & 1 & 0.061 & 5.63e-4 \\
92 +(1,2) & $b$-bit score, $b=2$ & 1 & 0.855 & 0.116 \\
93 +(1,2) & $b$-bit score, $b=3$ & 1 & 0.461 & 0.058 \\
94 +(1,2) & $b$-bit score, $b=4$ & 1 & 0.234 & 0.030 \\
95 +(1,2) & $b$-bit score, $b=6$ & 1 & 0.083 & 0.008 \\
96 +(1,2) & $b$-bit score, $b=8$ & 1 & 0.063 & 0.002 \\
97 +(1,2) & $b$-bit score, $b=12$ & 1 & 0.061 & 5.71e-4 \\
98 +(1,2) & $b$-bit score, $b=16$ & 1 & 0.061 & 5.63e-4 \\
99 +(1,2) & $b$-bit score, $b=24$ & 1 & 0.061 & 5.63e-4 \\
100 +(1,2) & $b$-bit score, $b=52$ & 1 & 0.061 & 5.63e-4 \\
101 +(1,2) & $b$-bit both, $b=2$ & 1 & 1.093 & 0.136 \\
102 +(1,2) & $b$-bit both, $b=3$ & 1 & 0.766 & 0.085 \\
103 +(1,2) & $b$-bit both, $b=4$ & 1 & 0.345 & 0.040 \\
104 +(1,2) & $b$-bit both, $b=6$ & 1 & 0.115 & 0.011 \\
105 +(1,2) & $b$-bit both, $b=8$ & 1 & 0.065 & 0.003 \\
106 +(1,2) & $b$-bit both, $b=12$ & 1 & 0.061 & 5.84e-4 \\
107 +(1,2) & $b$-bit both, $b=16$ & 1 & 0.061 & 5.63e-4 \\
108 +(1,2) & $b$-bit both, $b=24$ & 1 & 0.061 & 5.63e-4 \\
109 +(1,2) & $b$-bit both, $b=52$ & 1 & 0.061 & 5.63e-4 \\
110 +(1,2,4) & $b$-bit Hessian, $b=2$ & 1 & 710.398 & 0.093 \\
111 +(1,2,4) & $b$-bit Hessian, $b=3$ & 1 & 1702.282 & 0.085 \\
112 +(1,2,4) & $b$-bit Hessian, $b=4$ & 1 & 1382.610 & 0.035 \\
113 +(1,2,4) & $b$-bit Hessian, $b=6$ & 1 & 1398.623 & 0.010 \\
114 +(1,2,4) & $b$-bit Hessian, $b=8$ & 1 & 1400.676 & 0.002 \\
115 +(1,2,4) & $b$-bit Hessian, $b=12$ & 1 & 1411.781 & 8.38e-4 \\
116 +(1,2,4) & $b$-bit Hessian, $b=16$ & 1 & 1410.756 & 8.21e-4 \\
117 +(1,2,4) & $b$-bit Hessian, $b=24$ & 1 & 1410.845 & 8.22e-4 \\
118 +(1,2,4) & $b$-bit Hessian, $b=52$ & 1 & 1410.845 & 8.22e-4 \\
119 +(1,2,4) & $b$-bit score, $b=2$ & 1 & 1328.049 & 0.159 \\
120 +(1,2,4) & $b$-bit score, $b=3$ & 1 & 1499.669 & 0.081 \\
121 +(1,2,4) & $b$-bit score, $b=4$ & 1 & 1408.276 & 0.041 \\
122 +(1,2,4) & $b$-bit score, $b=6$ & 1 & 1407.339 & 0.010 \\
123 +(1,2,4) & $b$-bit score, $b=8$ & 1 & 1413.145 & 0.003 \\
124 +(1,2,4) & $b$-bit score, $b=12$ & 1 & 1410.772 & 8.33e-4 \\
125 +(1,2,4) & $b$-bit score, $b=16$ & 1 & 1410.839 & 8.22e-4 \\
126 +(1,2,4) & $b$-bit score, $b=24$ & 1 & 1410.845 & 8.22e-4 \\
127 +(1,2,4) & $b$-bit score, $b=52$ & 1 & 1410.845 & 8.22e-4 \\
128 +(1,2,4) & $b$-bit both, $b=2$ & 1 & 662.576 & 0.185 \\
129 +(1,2,4) & $b$-bit both, $b=3$ & 1 & 1807.436 & 0.119 \\
130 +(1,2,4) & $b$-bit both, $b=4$ & 1 & 1380.154 & 0.054 \\
131 +(1,2,4) & $b$-bit both, $b=6$ & 1 & 1395.142 & 0.015 \\
132 +(1,2,4) & $b$-bit both, $b=8$ & 1 & 1402.962 & 0.003 \\
133 +(1,2,4) & $b$-bit both, $b=12$ & 1 & 1411.708 & 8.50e-4 \\
134 +(1,2,4) & $b$-bit both, $b=16$ & 1 & 1410.751 & 8.21e-4 \\
135 +(1,2,4) & $b$-bit both, $b=24$ & 1 & 1410.845 & 8.22e-4 \\
136 +(1,2,4) & $b$-bit both, $b=52$ & 1 & 1410.845 & 8.22e-4 \\
137 137 \bottomrule
138 138 \end{tabular}
139 139 \begin{tablenotes}\footnotesize
140 −\item 400 paired replications per column; $K = N/m$. Rows are omitted when the pattern does not divide $m$. Source: \texttt{results/processed/ablation\_logistic\_summary.csv}.
140 +\item 400 paired replications per column (exact count per cell in the processed CSV); $K = N/m$. Rows are omitted when the pattern does not divide $m$. Source: \texttt{results/processed/ablation\_logistic\_summary.csv}.
141 141 \end{tablenotes}
142 142 \end{threeparttable}
143 143 \end{table}
modified paper/tables/mc_exp_p1.tex +18 −18
@@ -1,31 +1,31 @@
1 1 \begin{table}[p]
2 2 \centering\scriptsize
3 3 \begin{threeparttable}
4 −\caption{Monte Carlo, exp design, $p = 1$, $N = 1,048,576$: scaled gap to $\widehat\theta_N$, scaled RMSE and 95\% coverage by local sample size $m$.}\label{tab:mc_exp_p1}
4 +\caption{Monte Carlo, exp design, $p = 1$, $N = 4,194,304$: scaled gap to $\widehat\theta_N$, scaled RMSE and 95\% coverage by local sample size $m$.}\label{tab:mc_exp_p1}
5 5 \begin{tabular}{@{}lrrrrrrrrrrrr@{}}
6 6 \toprule
7 −Estimator & \multicolumn{3}{c}{$m = 8$, $K = 131,072$} & \multicolumn{3}{c}{$m = 32$, $K = 32,768$} & \multicolumn{3}{c}{$m = 256$, $K = 4,096$} & \multicolumn{3}{c}{$m = 1024$, $K = 1,024$} \\
7 +Estimator & \multicolumn{3}{c}{$m = 16$, $K = 262,144$} & \multicolumn{3}{c}{$m = 64$, $K = 65,536$} & \multicolumn{3}{c}{$m = 256$, $K = 16,384$} & \multicolumn{3}{c}{$m = 1024$, $K = 4,096$} \\
8 8 & gap & RMSE & cov & gap & RMSE & cov & gap & RMSE & cov & gap & RMSE & cov \\
9 9 \midrule
10 −(1,0) plain average & 146.302 & 146.312 & 0.000 & 33.039 & 33.022 & 0.000 & 4.020 & 4.122 & 0.021 & 1.002 & 1.433 & 0.827 \\
11 −(1,1) average + 1 Newton & 20.903 & 20.921 & 0.000 & 1.066 & 1.483 & 0.802 & 0.016 & 0.975 & 0.955 & 9.84e-4 & 0.995 & 0.952 \\
12 −(1,2) average + 2 Newton & 0.427 & 1.094 & 0.929 & 0.001 & 0.997 & 0.951 & 2.45e-7 & 0.974 & 0.956 & 9.60e-10 & 0.995 & 0.952 \\
13 −(2,0) half-block jackknife & 48.771 & 48.775 & 0.000 & 2.239 & 2.480 & 0.410 & 0.128 & 0.984 & 0.952 & 0.063 & 0.997 & 0.952 \\
14 −(2,1) half-block + 1 Newton & 2.326 & 2.529 & 0.364 & 0.005 & 0.997 & 0.951 & 2.76e-5 & 0.974 & 0.956 & 6.55e-6 & 0.995 & 0.952 \\
15 −(2,2) half-block + 2 Newton & 0.005 & 1.010 & -- & 3.17e-8 & 0.997 & -- & 2.58e-12 & 0.974 & -- & 2.06e-13 & 0.995 & -- \\
16 −(3,0) quarter-block & 48.902 & 48.918 & -- & 0.649 & 1.188 & -- & 0.177 & 0.992 & -- & 0.090 & 0.999 & -- \\
17 −(3,1) quarter-block + 1 Newton & 2.359 & 2.562 & 0.360 & 7.11e-4 & 0.997 & 0.951 & 5.13e-5 & 0.974 & 0.956 & 1.34e-5 & 0.995 & 0.952 \\
18 −analytic Cox--Snell + 1 Newton & 5.66e-4 & 1.010 & 0.951 & 1.14e-4 & 0.997 & 0.951 & 1.31e-5 & 0.974 & 0.956 & 3.13e-6 & 0.995 & 0.952 \\
19 −CSL, 1 round & 1.49e-13 & 1.010 & -- & 1.48e-13 & 0.997 & -- & 1.50e-13 & 0.974 & -- & 1.44e-13 & 0.995 & -- \\
20 −CSL, 2 rounds & 1.57e-13 & 1.010 & -- & 1.55e-13 & 0.997 & -- & 1.50e-13 & 0.974 & -- & 1.52e-13 & 0.995 & -- \\
21 −AEE (Lin--Xi) & 113.780 & 113.779 & -- & 31.035 & 31.084 & -- & 3.988 & 4.120 & -- & 1.000 & 1.390 & -- \\
22 −(2,1) stale Hessian & 3.249 & 3.397 & -- & 0.063 & 1.001 & -- & 4.85e-4 & 0.974 & -- & 6.21e-5 & 0.995 & -- \\
23 −centralized MLE & 0 & 1.010 & 0.951 & 0 & 0.997 & 0.951 & 0 & 0.974 & 0.956 & 0 & 0.995 & 0.952 \\
10 +(1,0) plain average & 136.531 & 136.600 & 0.000 & 32.502 & 32.557 & 0.000 & 8.031 & 8.115 & 0.000 & 2.003 & 2.239 & 0.468 \\
11 +(1,1) average + 1 Newton & 9.102 & 9.100 & 0.000 & 0.516 & 1.107 & 0.930 & 0.032 & 1.059 & 0.944 & 0.002 & 1.000 & 0.952 \\
12 +(1,2) average + 2 Newton & 0.040 & 1.064 & 0.936 & 1.30e-4 & 1.000 & 0.948 & 4.85e-7 & 1.059 & 0.944 & 1.88e-9 & 1.000 & 0.952 \\
13 +(2,0) half-block jackknife & 19.523 & 19.486 & 0.000 & 1.098 & 1.456 & 0.820 & 0.144 & 1.064 & 0.942 & 0.065 & 1.003 & 0.950 \\
14 +(2,1) half-block + 1 Newton & 0.186 & 1.071 & 0.930 & 6.55e-4 & 1.000 & 0.948 & 1.79e-5 & 1.059 & 0.944 & 3.69e-6 & 1.000 & 0.952 \\
15 +(2,2) half-block + 2 Newton & 1.71e-5 & 1.066 & -- & 2.93e-10 & 1.000 & -- & 6.25e-13 & 1.059 & -- & 2.90e-13 & 1.000 & -- \\
16 +(3,0) quarter-block & 6.557 & 6.703 & -- & 0.380 & 1.061 & -- & 0.177 & 1.068 & -- & 0.092 & 1.006 & -- \\
17 +(3,1) quarter-block + 1 Newton & 0.022 & 1.065 & 0.936 & 1.22e-4 & 1.000 & 0.948 & 2.64e-5 & 1.059 & 0.944 & 7.47e-6 & 1.000 & 0.952 \\
18 +analytic Cox--Snell + 1 Newton & 1.31e-4 & 1.066 & 0.932 & 2.44e-5 & 1.000 & 0.948 & 7.50e-6 & 1.059 & 0.944 & 1.59e-6 & 1.000 & 0.952 \\
19 +CSL, 1 round & 2.99e-13 & 1.066 & -- & 2.96e-13 & 1.000 & -- & 3.05e-13 & 1.059 & -- & 2.87e-13 & 1.000 & -- \\
20 +CSL, 2 rounds & 2.88e-13 & 1.066 & -- & 2.99e-13 & 1.000 & -- & 3.22e-13 & 1.059 & -- & 2.86e-13 & 1.000 & -- \\
21 +AEE (Lin--Xi) & 120.465 & 120.405 & -- & 31.499 & 31.476 & -- & 7.968 & 8.023 & -- & 1.999 & 2.234 & -- \\
22 +(2,1) stale Hessian & 0.971 & 1.397 & -- & 0.016 & 1.000 & -- & 5.43e-4 & 1.059 & -- & 6.40e-5 & 1.000 & -- \\
23 +centralized MLE & 0 & 1.066 & 0.932 & 0 & 1.000 & 0.948 & 0 & 1.059 & 0.944 & 0 & 1.000 & 0.952 \\
24 24 \bottomrule
25 25 \end{tabular}
26 26 \begin{tablenotes}\footnotesize
27 −\item 2000 paired replications per column. gap $=$ root mean square of $\sqrt N\,\lVert\tilde\theta - \widehat\theta_N\rVert$; RMSE $=$ root mean square of $\sqrt N\,\lVert\tilde\theta - \theta_0\rVert$; cov $=$ empirical coverage of nominal 95\% Wald intervals (observed information at the estimate; `--' when not computed). Monte Carlo standard errors of the gaps and RMSEs are in \texttt{results/processed/summary.csv}; coverage standard error $\approx 0.005$.
28 −\item Fraction of workers with all local fits valid (orders 2 / 3): $m=8$: 1.000 / 1.000; $m=16$: 1.000 / 1.000; $m=32$: 1.000 / 1.000; $m=64$: 1.000 / 1.000; $m=128$: 1.000 / 1.000; $m=256$: 1.000 / 1.000; $m=512$: 1.000 / 1.000; $m=1024$: 1.000 / 1.000.
27 +\item 500 paired replications per column. gap $=$ root mean square of $\sqrt N\,\lVert\tilde\theta - \widehat\theta_N\rVert$; RMSE $=$ root mean square of $\sqrt N\,\lVert\tilde\theta - \theta_0\rVert$; cov $=$ empirical coverage of nominal 95\% Wald intervals (observed information at the estimate; `--' when not computed). Monte Carlo standard errors of the gaps and RMSEs are in \texttt{results/processed/summary.csv}; coverage standard error $\approx 0.010$.
28 +\item Fraction of workers with all local fits valid (orders 2 / 3): $m=16$: 1.000 / 1.000; $m=32$: 1.000 / 1.000; $m=64$: 1.000 / 1.000; $m=128$: 1.000 / 1.000; $m=256$: 1.000 / 1.000; $m=512$: 1.000 / 1.000; $m=1024$: 1.000 / 1.000.
29 29 \end{tablenotes}
30 30 \end{threeparttable}
31 31 \end{table}
modified paper/tables/mc_logit_misspec_p3.tex +16 −16
@@ -4,28 +4,28 @@
4 4 \caption{Monte Carlo, logit misspec design, $p = 3$, $N = 1,048,576$: scaled gap to $\widehat\theta_N$, scaled RMSE and 95\% coverage by local sample size $m$.}\label{tab:mc_logit_misspec_p3}
5 5 \begin{tabular}{@{}lrrrrrrrrrrrr@{}}
6 6 \toprule
7 −Estimator & \multicolumn{3}{c}{$m = 64$, $K = 16,384$} & \multicolumn{3}{c}{$m = 128$, $K = 8,192$} & \multicolumn{3}{c}{$m = 256$, $K = 4,096$} & \multicolumn{3}{c}{$m = 512$, $K = 2,048$} \\
7 +Estimator & \multicolumn{3}{c}{$m = 32$, $K = 32,768$} & \multicolumn{3}{c}{$m = 64$, $K = 16,384$} & \multicolumn{3}{c}{$m = 256$, $K = 4,096$} & \multicolumn{3}{c}{$m = 512$, $K = 2,048$} \\
8 8 & gap & RMSE & cov & gap & RMSE & cov & gap & RMSE & cov & gap & RMSE & cov \\
9 9 \midrule
10 −(1,0) plain average & 52.024 & 130.880 & 0.007 & 24.676 & 146.781 & 0.002 & 12.064 & 155.047 & 0.000 & 5.968 & 159.218 & 0.000 \\
11 −(1,1) average + 1 Newton & 0.900 & 164.201 & 0.000 & 0.197 & 163.774 & 0.000 & 0.047 & 163.574 & 0.000 & 0.011 & 163.487 & 0.000 \\
12 −(1,2) average + 2 Newton & 2.65e-4 & 163.509 & 0.000 & 1.28e-5 & 163.622 & 0.000 & 7.15e-7 & 163.538 & 0.000 & 4.26e-8 & 163.478 & 0.000 \\
13 −(2,0) half-block jackknife & 41.221 & 185.011 & 0.000 & 2.877 & 165.603 & 0.000 & 0.879 & 163.955 & 0.000 & 0.476 & 163.571 & 0.000 \\
14 −(2,1) half-block + 1 Newton & 1.800 & 163.824 & 0.000 & 0.003 & 163.624 & 0.000 & 2.93e-4 & 163.538 & 0.000 & 7.54e-5 & 163.478 & 0.000 \\
15 −(2,2) half-block + 2 Newton & 0.011 & 163.510 & -- & 3.58e-9 & 163.622 & -- & 5.96e-11 & 163.538 & -- & 5.86e-12 & 163.478 & -- \\
16 −(3,0) quarter-block & 2684.344 & 2590.365 & -- & 15.401 & 160.546 & -- & 0.990 & 163.440 & -- & 0.643 & 163.457 & -- \\
17 −(3,1) quarter-block + 1 Newton & 1.55e+5 & 1.55e+5 & 0.001 & 0.477 & 163.678 & 0.000 & 3.15e-4 & 163.538 & 0.000 & 1.31e-4 & 163.478 & 0.000 \\
18 −analytic Cox--Snell + 1 Newton & 0.021 & 163.522 & 0.000 & 0.005 & 163.625 & 0.000 & 0.001 & 163.539 & 0.000 & 3.26e-4 & 163.478 & 0.000 \\
19 −CSL, 1 round & 12.528 & 165.985 & -- & 4.076 & 164.034 & -- & 1.379 & 163.657 & -- & 0.464 & 163.509 & -- \\
20 −CSL, 2 rounds & 6.106 & 161.226 & -- & 1.253 & 163.102 & -- & 0.264 & 163.414 & -- & 0.059 & 163.450 & -- \\
21 −AEE (Lin--Xi) & 41.700 & 197.944 & -- & 21.366 & 180.844 & -- & 10.841 & 172.157 & -- & 5.470 & 167.791 & -- \\
22 −(2,1) stale Hessian & 4.858 & 162.149 & -- & 0.086 & 163.564 & -- & 0.013 & 163.532 & -- & 0.004 & 163.477 & -- \\
23 −centralized MLE & 0 & 163.509 & 0.000 & 0 & 163.622 & 0.000 & 0 & 163.538 & 0.000 & 0 & 163.478 & 0.000 \\
10 +(1,0) plain average & 135.980 & 120.303 & 0.003 & 52.024 & 130.880 & 0.007 & 12.064 & 155.047 & 0.000 & 5.968 & 159.218 & 0.000 \\
11 +(1,1) average + 1 Newton & 13.101 & 169.121 & 0.000 & 0.900 & 164.201 & 0.000 & 0.047 & 163.574 & 0.000 & 0.011 & 163.487 & 0.000 \\
12 +(1,2) average + 2 Newton & 0.479 & 163.566 & 0.000 & 2.65e-4 & 163.509 & 0.000 & 7.15e-7 & 163.538 & 0.000 & 4.26e-8 & 163.478 & 0.000 \\
13 +(2,0) half-block jackknife & 7708.810 & 7813.703 & 0.001 & 41.221 & 185.011 & 0.000 & 0.879 & 163.955 & 0.000 & 0.476 & 163.571 & 0.000 \\
14 +(2,1) half-block + 1 Newton & 4.73e+6 & 4.73e+6 & 0.001 & 1.800 & 163.824 & 0.000 & 2.93e-4 & 163.538 & 0.000 & 7.54e-5 & 163.478 & 0.000 \\
15 +(2,2) half-block + 2 Newton & 1.75e+16 & 1.75e+16 & -- & 0.011 & 163.510 & -- & 5.96e-11 & 163.538 & -- & 5.86e-12 & 163.478 & -- \\
16 +(3,0) quarter-block & 1.32e+4 & 1.31e+4 & -- & 2684.344 & 2590.365 & -- & 0.990 & 163.440 & -- & 0.643 & 163.457 & -- \\
17 +(3,1) quarter-block + 1 Newton & 5.83e+7 & 5.83e+7 & 0.008 & 1.55e+5 & 1.55e+5 & 0.001 & 3.15e-4 & 163.538 & 0.000 & 1.31e-4 & 163.478 & 0.000 \\
18 +analytic Cox--Snell + 1 Newton & 1.75e+18 & 1.75e+18 & 0.004 & 0.021 & 163.522 & 0.000 & 0.001 & 163.539 & 0.000 & 3.26e-4 & 163.478 & 0.000 \\
19 +CSL, 1 round & 51.104 & 181.310 & -- & 12.528 & 165.985 & -- & 1.379 & 163.657 & -- & 0.464 & 163.509 & -- \\
20 +CSL, 2 rounds & 54.317 & 157.156 & -- & 6.106 & 161.226 & -- & 0.264 & 163.414 & -- & 0.059 & 163.450 & -- \\
21 +AEE (Lin--Xi) & 80.818 & 232.638 & -- & 41.700 & 197.944 & -- & 10.841 & 172.157 & -- & 5.470 & 167.791 & -- \\
22 +(2,1) stale Hessian & 5379.284 & 5461.385 & -- & 4.858 & 162.149 & -- & 0.013 & 163.532 & -- & 0.004 & 163.477 & -- \\
23 +centralized MLE & 0 & 163.528 & 0.000 & 0 & 163.509 & 0.000 & 0 & 163.538 & 0.000 & 0 & 163.478 & 0.000 \\
24 24 \bottomrule
25 25 \end{tabular}
26 26 \begin{tablenotes}\footnotesize
27 27 \item 1000 paired replications per column. gap $=$ root mean square of $\sqrt N\,\lVert\tilde\theta - \widehat\theta_N\rVert$; RMSE $=$ root mean square of $\sqrt N\,\lVert\tilde\theta - \theta_0\rVert$; cov $=$ empirical coverage of nominal 95\% Wald intervals (observed information at the estimate; `--' when not computed). Monte Carlo standard errors of the gaps and RMSEs are in \texttt{results/processed/summary.csv}; coverage standard error $\approx 0.007$.
28 −\item Fraction of workers with all local fits valid (orders 2 / 3): $m=64$: 1.000 / 0.945; $m=128$: 1.000 / 1.000; $m=256$: 1.000 / 1.000; $m=512$: 1.000 / 1.000.
28 +\item Fraction of workers with all local fits valid (orders 2 / 3): $m=32$: 0.972 / 0.268; $m=64$: 1.000 / 0.945; $m=128$: 1.000 / 1.000; $m=256$: 1.000 / 1.000; $m=512$: 1.000 / 1.000.
29 29 \end{tablenotes}
30 30 \end{threeparttable}
31 31 \end{table}
modified paper/tables/mc_logit_p20_p20.tex +18 −18
@@ -2,30 +2,30 @@
2 2 \centering\scriptsize
3 3 \begin{threeparttable}
4 4 \caption{Monte Carlo, logit p20 design, $p = 20$, $N = 1,048,576$: scaled gap to $\widehat\theta_N$, scaled RMSE and 95\% coverage by local sample size $m$.}\label{tab:mc_logit_p20_p20}
5 −\begin{tabular}{@{}lrrrrrr@{}}
5 +\begin{tabular}{@{}lrrrrrrrrrrrr@{}}
6 6 \toprule
7 −Estimator & \multicolumn{3}{c}{$m = 1024$, $K = 1,024$} & \multicolumn{3}{c}{$m = 2048$, $K = 512$} \\
8 − & gap & RMSE & cov & gap & RMSE & cov \\
7 +Estimator & \multicolumn{3}{c}{$m = 128$, $K = 8,192$} & \multicolumn{3}{c}{$m = 256$, $K = 4,096$} & \multicolumn{3}{c}{$m = 1024$, $K = 1,024$} & \multicolumn{3}{c}{$m = 2048$, $K = 512$} \\
8 + & gap & RMSE & cov & gap & RMSE & cov & gap & RMSE & cov & gap & RMSE & cov \\
9 9 \midrule
10 −(1,0) plain average & 29.210 & 30.964 & 0.343 & 14.338 & 17.881 & 0.719 \\
11 −(1,1) average + 1 Newton & 0.369 & 10.159 & 0.953 & 0.088 & 10.329 & 0.954 \\
12 −(1,2) average + 2 Newton & 5.84e-5 & 10.155 & 0.953 & 3.37e-6 & 10.331 & 0.954 \\
13 −(2,0) half-block jackknife & 3.171 & 10.608 & 0.941 & 1.668 & 10.468 & 0.947 \\
14 −(2,1) half-block + 1 Newton & 0.004 & 10.155 & 0.953 & 9.12e-4 & 10.331 & 0.954 \\
15 −(2,2) half-block + 2 Newton & 7.91e-9 & 10.155 & -- & 5.12e-10 & 10.331 & -- \\
16 −(3,0) quarter-block & 3.404 & 10.700 & -- & 2.272 & 10.592 & -- \\
17 −(3,1) quarter-block + 1 Newton & 0.003 & 10.155 & 0.953 & 0.002 & 10.331 & 0.954 \\
18 −analytic Cox--Snell + 1 Newton & 7.34e-4 & 10.155 & 0.953 & 3.59e-4 & 10.331 & 0.954 \\
19 −CSL, 1 round & 2.937 & 10.575 & -- & 1.017 & 10.358 & -- \\
20 −CSL, 2 rounds & 0.691 & 10.182 & -- & 0.163 & 10.334 & -- \\
21 −AEE (Lin--Xi) & 28.049 & 29.782 & -- & 14.027 & 17.221 & -- \\
22 −(2,1) stale Hessian & 0.066 & 10.156 & -- & 0.018 & 10.331 & -- \\
23 −centralized MLE & 0 & 10.155 & 0.953 & 0 & 10.331 & 0.954 \\
10 +(1,0) plain average & 323.376 & 323.718 & 0.000 & 131.255 & 131.770 & 0.000 & 29.210 & 30.964 & 0.343 & 14.338 & 17.881 & 0.719 \\
11 +(1,1) average + 1 Newton & 49.477 & 50.361 & 0.075 & 7.699 & 12.790 & 0.889 & 0.369 & 10.159 & 0.953 & 0.088 & 10.329 & 0.954 \\
12 +(1,2) average + 2 Newton & 1.031 & 10.362 & 0.947 & 0.025 & 10.300 & 0.952 & 5.84e-5 & 10.155 & 0.953 & 3.37e-6 & 10.331 & 0.954 \\
13 +(2,0) half-block jackknife & 1.65e+5 & 1.65e+5 & 0.000 & 61.069 & 61.824 & 0.033 & 3.171 & 10.608 & 0.941 & 1.668 & 10.468 & 0.947 \\
14 +(2,1) half-block + 1 Newton & 2.26e+11 & 2.26e+11 & 0.066 & 1.564 & 10.400 & 0.947 & 0.004 & 10.155 & 0.953 & 9.12e-4 & 10.331 & 0.954 \\
15 +(2,2) half-block + 2 Newton & 1.29e+131 & 1.29e+131 & -- & 0.001 & 10.301 & -- & 7.91e-9 & 10.155 & -- & 5.12e-10 & 10.331 & -- \\
16 +(3,0) quarter-block & 3.25e+5 & 3.25e+5 & -- & 4.40e+4 & 4.40e+4 & -- & 3.404 & 10.700 & -- & 2.272 & 10.592 & -- \\
17 +(3,1) quarter-block + 1 Newton & 1.84e+12 & 1.84e+12 & 0.899 & 4.14e+9 & 4.14e+9 & 0.008 & 0.003 & 10.155 & 0.953 & 0.002 & 10.331 & 0.954 \\
18 +analytic Cox--Snell + 1 Newton & 0.253 & 10.331 & 0.949 & 0.009 & 10.300 & 0.952 & 7.34e-4 & 10.155 & 0.953 & 3.59e-4 & 10.331 & 0.954 \\
19 +CSL, 1 round & 112.258 & 112.746 & -- & 29.269 & 31.021 & -- & 2.937 & 10.575 & -- & 1.017 & 10.358 & -- \\
20 +CSL, 2 rounds & 141.077 & 141.505 & -- & 18.314 & 21.012 & -- & 0.691 & 10.182 & -- & 0.163 & 10.334 & -- \\
21 +AEE (Lin--Xi) & 230.409 & 230.466 & -- & 112.533 & 112.893 & -- & 28.049 & 29.782 & -- & 14.027 & 17.221 & -- \\
22 +(2,1) stale Hessian & 1.63e+5 & 1.63e+5 & -- & 6.341 & 12.156 & -- & 0.066 & 10.156 & -- & 0.018 & 10.331 & -- \\
23 +centralized MLE & 0 & 10.332 & 0.948 & 0 & 10.301 & 0.952 & 0 & 10.155 & 0.953 & 0 & 10.331 & 0.954 \\
24 24 \bottomrule
25 25 \end{tabular}
26 26 \begin{tablenotes}\footnotesize
27 27 \item 500 paired replications per column. gap $=$ root mean square of $\sqrt N\,\lVert\tilde\theta - \widehat\theta_N\rVert$; RMSE $=$ root mean square of $\sqrt N\,\lVert\tilde\theta - \theta_0\rVert$; cov $=$ empirical coverage of nominal 95\% Wald intervals (observed information at the estimate; `--' when not computed). Monte Carlo standard errors of the gaps and RMSEs are in \texttt{results/processed/summary.csv}; coverage standard error $\approx 0.010$.
28 −\item Fraction of workers with all local fits valid (orders 2 / 3): $m=1024$: 1.000 / 1.000; $m=2048$: 1.000 / 1.000.
28 +\item Fraction of workers with all local fits valid (orders 2 / 3): $m=128$: 0.821 / 0.000; $m=256$: 1.000 / 0.674; $m=512$: 1.000 / 1.000; $m=1024$: 1.000 / 1.000; $m=2048$: 1.000 / 1.000.
29 29 \end{tablenotes}
30 30 \end{threeparttable}
31 31 \end{table}
modified paper/tables/mc_logit_p3.tex +16 −16
@@ -4,28 +4,28 @@
4 4 \caption{Monte Carlo, logit design, $p = 3$, $N = 1,048,576$: scaled gap to $\widehat\theta_N$, scaled RMSE and 95\% coverage by local sample size $m$.}\label{tab:mc_logit_p3}
5 5 \begin{tabular}{@{}lrrrrrrrrrrrr@{}}
6 6 \toprule
7 −Estimator & \multicolumn{3}{c}{$m = 64$, $K = 16,384$} & \multicolumn{3}{c}{$m = 128$, $K = 8,192$} & \multicolumn{3}{c}{$m = 512$, $K = 2,048$} & \multicolumn{3}{c}{$m = 1024$, $K = 1,024$} \\
7 +Estimator & \multicolumn{3}{c}{$m = 32$, $K = 32,768$} & \multicolumn{3}{c}{$m = 128$, $K = 8,192$} & \multicolumn{3}{c}{$m = 512$, $K = 2,048$} & \multicolumn{3}{c}{$m = 1024$, $K = 1,024$} \\
8 8 & gap & RMSE & cov & gap & RMSE & cov & gap & RMSE & cov & gap & RMSE & cov \\
9 9 \midrule
10 −(1,0) plain average & 61.612 & 61.746 & 0.000 & 29.019 & 29.330 & 0.008 & 6.969 & 7.892 & 0.572 & 3.463 & 5.064 & 0.860 \\
11 −(1,1) average + 1 Newton & 1.463 & 4.092 & 0.933 & 0.318 & 3.757 & 0.951 & 0.018 & 3.744 & 0.951 & 0.004 & 3.751 & 0.957 \\
12 −(1,2) average + 2 Newton & 7.95e-4 & 3.831 & 0.949 & 3.76e-5 & 3.751 & 0.952 & 1.21e-7 & 3.744 & 0.951 & 6.47e-9 & 3.751 & 0.957 \\
13 −(2,0) half-block jackknife & 3147.554 & 3147.627 & 0.020 & 3.782 & 5.308 & 0.829 & 0.514 & 3.775 & 0.949 & 0.338 & 3.769 & 0.958 \\
14 −(2,1) half-block + 1 Newton & 1.19e+7 & 1.19e+7 & 0.898 & 0.006 & 3.751 & 0.952 & 1.09e-4 & 3.744 & 0.951 & 4.55e-5 & 3.751 & 0.957 \\
15 −(2,2) half-block + 2 Newton & 3.52e+17 & 3.52e+17 & -- & 1.39e-8 & 3.751 & -- & 1.08e-9 & 3.744 & -- & 1.08e-9 & 3.751 & -- \\
16 −(3,0) quarter-block & 7309.080 & 7309.149 & -- & 79.768 & 79.856 & -- & 0.678 & 3.792 & -- & 0.473 & 3.781 & -- \\
17 −(3,1) quarter-block + 1 Newton & 9.24e+7 & 9.24e+7 & 0.001 & 144.811 & 144.911 & 0.947 & 1.73e-4 & 3.744 & 0.951 & 8.65e-5 & 3.751 & 0.957 \\
18 −analytic Cox--Snell + 1 Newton & 5.38e-4 & 3.831 & 0.949 & 1.76e-4 & 3.751 & 0.952 & 4.49e-5 & 3.744 & 0.951 & 2.13e-5 & 3.751 & 0.957 \\
19 −CSL, 1 round & 13.350 & 13.891 & -- & 4.334 & 5.683 & -- & 0.510 & 3.790 & -- & 0.170 & 3.754 & -- \\
20 −CSL, 2 rounds & 6.175 & 7.230 & -- & 1.233 & 3.960 & -- & 0.064 & 3.744 & -- & 0.014 & 3.751 & -- \\
21 −AEE (Lin--Xi) & 52.632 & 52.757 & -- & 26.847 & 27.041 & -- & 6.829 & 7.809 & -- & 3.423 & 5.119 & -- \\
22 −(2,1) stale Hessian & 3046.272 & 3046.346 & -- & 0.102 & 3.753 & -- & 0.004 & 3.744 & -- & 0.001 & 3.751 & -- \\
23 −centralized MLE & 0 & 3.831 & 0.949 & 0 & 3.751 & 0.952 & 0 & 3.744 & 0.951 & 0 & 3.751 & 0.957 \\
10 +(1,0) plain average & 286.566 & 286.648 & 0.000 & 29.019 & 29.330 & 0.008 & 6.969 & 7.892 & 0.572 & 3.463 & 5.064 & 0.860 \\
11 +(1,1) average + 1 Newton & 2689.961 & 2689.977 & 0.331 & 0.318 & 3.757 & 0.951 & 0.018 & 3.744 & 0.951 & 0.004 & 3.751 & 0.957 \\
12 +(1,2) average + 2 Newton & 8.41e+6 & 8.41e+6 & 0.945 & 3.76e-5 & 3.751 & 0.952 & 1.21e-7 & 3.744 & 0.951 & 6.47e-9 & 3.751 & 0.957 \\
13 +(2,0) half-block jackknife & 1.45e+4 & 1.45e+4 & 0.000 & 3.782 & 5.308 & 0.829 & 0.514 & 3.775 & 0.949 & 0.338 & 3.769 & 0.958 \\
14 +(2,1) half-block + 1 Newton & 2.04e+8 & 2.04e+8 & 0.004 & 0.006 & 3.751 & 0.952 & 1.09e-4 & 3.744 & 0.951 & 4.55e-5 & 3.751 & 0.957 \\
15 +(2,2) half-block + 2 Newton & 1.18e+24 & 1.18e+24 & -- & 1.39e-8 & 3.751 & -- & 1.08e-9 & 3.744 & -- & 1.08e-9 & 3.751 & -- \\
16 +(3,0) quarter-block & 2.50e+4 & 2.50e+4 & -- & 79.768 & 79.856 & -- & 0.678 & 3.792 & -- & 0.473 & 3.781 & -- \\
17 +(3,1) quarter-block + 1 Newton & 1.52e+9 & 1.52e+9 & 0.008 & 144.811 & 144.911 & 0.947 & 1.73e-4 & 3.744 & 0.951 & 8.65e-5 & 3.751 & 0.957 \\
18 +analytic Cox--Snell + 1 Newton & 4.62e+117 & 4.62e+117 & 0.457 & 1.76e-4 & 3.751 & 0.952 & 4.49e-5 & 3.744 & 0.951 & 2.13e-5 & 3.751 & 0.957 \\
19 +CSL, 1 round & 57.743 & 57.803 & -- & 4.334 & 5.683 & -- & 0.510 & 3.790 & -- & 0.170 & 3.754 & -- \\
20 +CSL, 2 rounds & 50.483 & 50.642 & -- & 1.233 & 3.960 & -- & 0.064 & 3.744 & -- & 0.014 & 3.751 & -- \\
21 +AEE (Lin--Xi) & 102.585 & 102.557 & -- & 26.847 & 27.041 & -- & 6.829 & 7.809 & -- & 3.423 & 5.119 & -- \\
22 +(2,1) stale Hessian & 1.24e+4 & 1.24e+4 & -- & 0.102 & 3.753 & -- & 0.004 & 3.744 & -- & 0.001 & 3.751 & -- \\
23 +centralized MLE & 0 & 3.806 & 0.950 & 0 & 3.751 & 0.952 & 0 & 3.744 & 0.951 & 0 & 3.751 & 0.957 \\
24 24 \bottomrule
25 25 \end{tabular}
26 26 \begin{tablenotes}\footnotesize
27 27 \item 1000 paired replications per column. gap $=$ root mean square of $\sqrt N\,\lVert\tilde\theta - \widehat\theta_N\rVert$; RMSE $=$ root mean square of $\sqrt N\,\lVert\tilde\theta - \theta_0\rVert$; cov $=$ empirical coverage of nominal 95\% Wald intervals (observed information at the estimate; `--' when not computed). Monte Carlo standard errors of the gaps and RMSEs are in \texttt{results/processed/summary.csv}; coverage standard error $\approx 0.007$.
28 −\item Fraction of workers with all local fits valid (orders 2 / 3): $m=64$: 1.000 / 0.924; $m=128$: 1.000 / 1.000; $m=256$: 1.000 / 1.000; $m=512$: 1.000 / 1.000; $m=1024$: 1.000 / 1.000.
28 +\item Fraction of workers with all local fits valid (orders 2 / 3): $m=32$: 0.961 / 0.234; $m=64$: 1.000 / 0.924; $m=128$: 1.000 / 1.000; $m=256$: 1.000 / 1.000; $m=512$: 1.000 / 1.000; $m=1024$: 1.000 / 1.000.
29 29 \end{tablenotes}
30 30 \end{threeparttable}
31 31 \end{table}
modified paper/tables/mc_logit_p8.tex +18 −18
@@ -2,30 +2,30 @@
2 2 \centering\scriptsize
3 3 \begin{threeparttable}
4 4 \caption{Monte Carlo, logit design, $p = 8$, $N = 1,048,576$: scaled gap to $\widehat\theta_N$, scaled RMSE and 95\% coverage by local sample size $m$.}\label{tab:mc_logit_p8}
5 −\begin{tabular}{@{}lrrrrrrrrr@{}}
5 +\begin{tabular}{@{}lrrrrrrrrrrrr@{}}
6 6 \toprule
7 −Estimator & \multicolumn{3}{c}{$m = 256$, $K = 4,096$} & \multicolumn{3}{c}{$m = 512$, $K = 2,048$} & \multicolumn{3}{c}{$m = 1024$, $K = 1,024$} \\
8 − & gap & RMSE & cov & gap & RMSE & cov & gap & RMSE & cov \\
7 +Estimator & \multicolumn{3}{c}{$m = 64$, $K = 16,384$} & \multicolumn{3}{c}{$m = 128$, $K = 8,192$} & \multicolumn{3}{c}{$m = 512$, $K = 2,048$} & \multicolumn{3}{c}{$m = 1024$, $K = 1,024$} \\
8 + & gap & RMSE & cov & gap & RMSE & cov & gap & RMSE & cov & gap & RMSE & cov \\
9 9 \midrule
10 −(1,0) plain average & 44.320 & 44.777 & 0.000 & 21.491 & 22.386 & 0.148 & 10.589 & 12.356 & 0.633 \\
11 −(1,1) average + 1 Newton & 0.835 & 6.432 & 0.950 & 0.195 & 6.304 & 0.952 & 0.047 & 6.342 & 0.953 \\
12 −(1,2) average + 2 Newton & 2.92e-4 & 6.378 & 0.951 & 1.59e-5 & 6.301 & 0.952 & 9.30e-7 & 6.342 & 0.953 \\
13 −(2,0) half-block jackknife & 6.674 & 9.231 & 0.824 & 1.888 & 6.568 & 0.943 & 0.958 & 6.404 & 0.950 \\
14 −(2,1) half-block + 1 Newton & 0.019 & 6.378 & 0.951 & 0.001 & 6.301 & 0.951 & 3.22e-4 & 6.342 & 0.953 \\
15 −(2,2) half-block + 2 Newton & 1.67e-7 & 6.378 & -- & 1.40e-9 & 6.301 & -- & 7.37e-11 & 6.342 & -- \\
16 −(3,0) quarter-block & 13.791 & 15.259 & -- & 1.925 & 6.571 & -- & 1.281 & 6.458 & -- \\
17 −(3,1) quarter-block + 1 Newton & 0.984 & 6.440 & 0.949 & 0.001 & 6.301 & 0.952 & 5.11e-4 & 6.342 & 0.953 \\
18 −analytic Cox--Snell + 1 Newton & 5.91e-4 & 6.378 & 0.951 & 2.62e-4 & 6.301 & 0.951 & 1.30e-4 & 6.342 & 0.953 \\
19 −CSL, 1 round & 6.304 & 8.966 & -- & 2.097 & 6.631 & -- & 0.718 & 6.378 & -- \\
20 −CSL, 2 rounds & 2.003 & 6.709 & -- & 0.431 & 6.314 & -- & 0.101 & 6.344 & -- \\
21 −AEE (Lin--Xi) & 41.193 & 41.683 & -- & 20.707 & 21.655 & -- & 10.393 & 12.159 & -- \\
22 −(2,1) stale Hessian & 0.209 & 6.382 & -- & 0.031 & 6.301 & -- & 0.008 & 6.342 & -- \\
23 −centralized MLE & 0 & 6.378 & 0.951 & 0 & 6.301 & 0.952 & 0 & 6.342 & 0.953 \\
10 +(1,0) plain average & 233.195 & 233.424 & 0.000 & 94.927 & 95.224 & 0.000 & 21.491 & 22.386 & 0.148 & 10.589 & 12.356 & 0.633 \\
11 +(1,1) average + 1 Newton & 31.483 & 32.009 & 0.099 & 3.909 & 7.327 & 0.916 & 0.195 & 6.304 & 0.952 & 0.047 & 6.342 & 0.953 \\
12 +(1,2) average + 2 Newton & 2.275 & 6.848 & 0.942 & 0.006 & 6.260 & 0.956 & 1.59e-5 & 6.301 & 0.952 & 9.30e-7 & 6.342 & 0.953 \\
13 +(2,0) half-block jackknife & 9.42e+4 & 9.42e+4 & 0.000 & 45.313 & 45.654 & 0.004 & 1.888 & 6.568 & 0.943 & 0.958 & 6.404 & 0.950 \\
14 +(2,1) half-block + 1 Newton & 1.62e+11 & 1.62e+11 & 0.009 & 3.356 & 7.081 & 0.952 & 0.001 & 6.301 & 0.951 & 3.22e-4 & 6.342 & 0.953 \\
15 +(2,2) half-block + 2 Newton & 2.38e+24 & 2.38e+24 & -- & 0.125 & 6.261 & -- & 1.40e-9 & 6.301 & -- & 7.37e-11 & 6.342 & -- \\
16 +(3,0) quarter-block & 1.86e+5 & 1.86e+5 & -- & 2.85e+4 & 2.85e+4 & -- & 1.925 & 6.571 & -- & 1.281 & 6.458 & -- \\
17 +(3,1) quarter-block + 1 Newton & 1.32e+12 & 1.32e+12 & 0.018 & 2.36e+9 & 2.36e+9 & 0.002 & 0.001 & 6.301 & 0.952 & 5.11e-4 & 6.342 & 0.953 \\
18 +analytic Cox--Snell + 1 Newton & 9.07e+53 & 9.07e+53 & 0.918 & 0.003 & 6.260 & 0.956 & 2.62e-4 & 6.301 & 0.951 & 1.30e-4 & 6.342 & 0.953 \\
19 +CSL, 1 round & 76.119 & 76.343 & -- & 20.125 & 21.127 & -- & 2.097 & 6.631 & -- & 0.718 & 6.378 & -- \\
20 +CSL, 2 rounds & 80.931 & 81.210 & -- & 10.636 & 12.318 & -- & 0.431 & 6.314 & -- & 0.101 & 6.344 & -- \\
21 +AEE (Lin--Xi) & 163.596 & 163.586 & -- & 81.848 & 81.995 & -- & 20.707 & 21.655 & -- & 10.393 & 12.159 & -- \\
22 +(2,1) stale Hessian & 9.31e+4 & 9.31e+4 & -- & 7.823 & 10.074 & -- & 0.031 & 6.301 & -- & 0.008 & 6.342 & -- \\
23 +centralized MLE & 0 & 6.495 & 0.945 & 0 & 6.260 & 0.956 & 0 & 6.301 & 0.952 & 0 & 6.342 & 0.953 \\
24 24 \bottomrule
25 25 \end{tabular}
26 26 \begin{tablenotes}\footnotesize
27 27 \item 1000 paired replications per column. gap $=$ root mean square of $\sqrt N\,\lVert\tilde\theta - \widehat\theta_N\rVert$; RMSE $=$ root mean square of $\sqrt N\,\lVert\tilde\theta - \theta_0\rVert$; cov $=$ empirical coverage of nominal 95\% Wald intervals (observed information at the estimate; `--' when not computed). Monte Carlo standard errors of the gaps and RMSEs are in \texttt{results/processed/summary.csv}; coverage standard error $\approx 0.007$.
28 −\item Fraction of workers with all local fits valid (orders 2 / 3): $m=256$: 1.000 / 1.000; $m=512$: 1.000 / 1.000; $m=1024$: 1.000 / 1.000.
28 +\item Fraction of workers with all local fits valid (orders 2 / 3): $m=64$: 0.930 / 0.009; $m=128$: 1.000 / 0.865; $m=256$: 1.000 / 1.000; $m=512$: 1.000 / 1.000; $m=1024$: 1.000 / 1.000.
29 29 \end{tablenotes}
30 30 \end{threeparttable}
31 31 \end{table}
modified paper/tables/mc_rates.tex +5 −4
@@ -7,12 +7,13 @@
7 7 Design & $p$ & $N$ & r1\_q0 & r1\_q1 & r1\_q2 & r2\_q0 & r2\_q1 & r3\_q0 & r3\_q1 & cs\_q1 \\
8 8 predicted & & & -1 & -2 & -4 & -2 & -4 & -3 & -6 & -4 \\
9 9 \midrule
10 −exp & 1 & 1,048,576 & -1.02 & -2.04 & -4.11 & -1.36 & -2.59 & -1.11 & -2.12 & -1.05 \\
10 +exp & 1 & 4,194,304 & -1.01 & -2.03 & -4.05 & -1.39 & -2.61 & -0.89 & -1.69 & -1.05 \\
11 11 exp contam & 1 & 1,048,576 & -0.90 & -1.81 & -3.62 & -1.10 & -2.12 & -1.47 & -2.76 & -1.50 \\
12 −logit & 3 & 1,048,576 & -1.04 & -2.08 & -4.21 & -2.92 & -8.16 & -3.47 & -9.96 & -1.13 \\
13 −logit & 8 & 1,048,576 & -1.03 & -2.07 & -4.15 & -1.40 & -2.94 & -1.71 & -5.46 & -1.09 \\
12 +logit & 3 & 1,048,576 & -1.21 & -3.35 & -8.38 & -3.33 & -9.25 & -3.57 & -10.15 & -58.39 \\
13 +logit & 8 & 1,048,576 & -1.11 & -2.31 & -5.11 & -3.78 & -10.88 & -4.81 & -14.32 & -38.76 \\
14 14 logit illcond & 8 & 1,048,576 & -1.10 & -2.25 & -4.51 & -3.87 & -11.27 & -5.30 & -15.59 & -1.95 \\
15 −logit misspec & 3 & 1,048,576 & -1.04 & -2.10 & -4.20 & -2.10 & -4.69 & -4.00 & -10.10 & -2.00 \\
15 +logit misspec & 3 & 1,048,576 & -1.11 & -2.46 & -5.54 & -3.35 & -8.43 & -4.00 & -10.63 & -14.84 \\
16 +logit p20 & 20 & 1,048,576 & -1.12 & -2.26 & -4.52 & -3.75 & -10.43 & -4.79 & -14.04 & -2.26 \\
16 17 pois & 3 & 1,048,576 & -1.02 & -2.04 & -4.15 & -1.22 & -2.78 & -1.96 & -3.98 & -1.07 \\
17 18 pois & 8 & 1,048,576 & -1.03 & -2.06 & -4.11 & -1.28 & -2.48 & -2.14 & -4.53 & -1.07 \\
18 19 \bottomrule
modified paper/tables/numbers.tex +2 −2
@@ -1,6 +1,6 @@
1 1 % Auto-generated by experiments/make_tables.py
2 −\newcommand{\numMCcells}{158}
3 −\newcommand{\numManifest}{158}
2 +\newcommand{\numMCcells}{173}
3 +\newcommand{\numManifest}{173}
4 4 \newcommand{\numMCrepsExp}{2000}
5 5 \newcommand{\numMCrepsLogit}{1000}
6 6 \newcommand{\benchHosts}{0}
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modified results/processed/ablation_exponential_summary.csv +127 −127
@@ -757,133 +757,133 @@ N,m,variant,pattern,r,q,hessian,bits,rms,mean0,n,valid
757 757 3145728,192,pat1_q3,1,1,3,exact,64,2.1758484637398277e-13,9.845568954283843e-16,1000,1.0
758 758 3145728,192,pat1_q3_single,1,1,3,single,64,2.1820766258333744e-13,1.1814682745140614e-15,1000,
759 759 3145728,192,pat1_q3_stale,1,1,3,stale,64,2.610114628767646e-06,2.607706495263206e-06,1000,
760 −6291456,24,pat1-2-3-4_q0,1-2-3-4,4,0,exact,64,2.247496608690636,-0.39638191497480785,100,1.0
761 −6291456,24,pat1-2-3-4_q1,1-2-3-4,4,1,exact,64,0.0033186059440164775,-0.00201385962130475,100,1.0
762 −6291456,24,pat1-2-3-4_q2,1-2-3-4,4,2,exact,64,1.1082082844953716e-08,-4.391084427279304e-09,100,1.0
763 −6291456,24,pat1-2-3-4_q3,1-2-3-4,4,3,exact,64,3.0378008013684364e-13,8.354242286656625e-15,100,1.0
764 −6291456,24,pat1-2-3_q0,1-2-3,3,0,exact,64,1.6467940097574683,1.3336086689159403,100,1.0
765 −6291456,24,pat1-2-3_q1,1-2-3,3,1,exact,64,0.0016834679463196165,-0.0010813223158701866,100,1.0
766 −6291456,24,pat1-2-3_q2,1-2-3,3,2,exact,64,3.086847431904937e-09,-1.1301034168429014e-09,100,1.0
767 −6291456,24,pat1-2-3_q3,1-2-3,3,3,exact,64,3.075854069372482e-13,2.2277979431084334e-14,100,1.0
768 −6291456,24,pat1-2-4-8_q0,1-2-4-8,4,0,exact,64,1.3945312543561215,-1.0758480357854432,100,1.0
769 −6291456,24,pat1-2-4-8_q1,1-2-4-8,4,1,exact,64,0.0011057157708327027,-0.0007752680356172265,100,1.0
770 −6291456,24,pat1-2-4-8_q2,1-2-4-8,4,2,exact,64,1.0114125490484862e-09,-4.873697865189741e-10,100,1.0
771 −6291456,24,pat1-2-4-8_q3,1-2-4-8,4,3,exact,64,3.113442275577916e-13,8.354242286656626e-15,100,1.0
772 −6291456,24,pat1-2-4_q0,1-2-4,3,0,exact,64,2.031838644537755,1.910272196879036,100,1.0
773 −6291456,24,pat1-2-4_q1,1-2-4,3,1,exact,64,0.0020052435287412997,-0.0016459949131459291,100,1.0
774 −6291456,24,pat1-2-4_q1_Hbits12,1-2-4,3,1,quantizedH,12,0.001993364260368759,-0.001631416397739828,100,
775 −6291456,24,pat1-2-4_q1_Hbits16,1-2-4,3,1,quantizedH,16,0.0020057906114727595,-0.001646308857278083,100,
776 −6291456,24,pat1-2-4_q1_Hbits2,1-2-4,3,1,quantizedH,2,0.002267699263173942,0.0015601689658671359,100,
777 −6291456,24,pat1-2-4_q1_Hbits24,1-2-4,3,1,quantizedH,24,0.0020052479610826075,-0.001645997897426075,100,
778 −6291456,24,pat1-2-4_q1_Hbits3,1-2-4,3,1,quantizedH,3,0.002267699263173942,0.0015601689658671359,100,
779 −6291456,24,pat1-2-4_q1_Hbits4,1-2-4,3,1,quantizedH,4,0.002267699263173942,0.0015601689658671359,100,
780 −6291456,24,pat1-2-4_q1_Hbits52,1-2-4,3,1,quantizedH,52,0.0020052435287412997,-0.0016459949131459291,100,
781 −6291456,24,pat1-2-4_q1_Hbits6,1-2-4,3,1,quantizedH,6,0.002267699263173942,0.0015601689658671359,100,
782 −6291456,24,pat1-2-4_q1_Hbits8,1-2-4,3,1,quantizedH,8,0.003803745860146607,-0.0015726909928020462,100,
783 −6291456,24,pat1-2-4_q1_bothbits12,1-2-4,3,1,quantizedBoth,12,0.001969861409732011,-0.0016046807509853677,100,
784 −6291456,24,pat1-2-4_q1_bothbits16,1-2-4,3,1,quantizedBoth,16,0.0020058806986110876,-0.0016465389186076926,100,
785 −6291456,24,pat1-2-4_q1_bothbits2,1-2-4,3,1,quantizedBoth,2,0.193854312502042,0.01957230166827056,100,
786 −6291456,24,pat1-2-4_q1_bothbits24,1-2-4,3,1,quantizedBoth,24,0.0020052328556104835,-0.0016459890224750143,100,
787 −6291456,24,pat1-2-4_q1_bothbits3,1-2-4,3,1,quantizedBoth,3,0.10729673290077396,-0.0010952680364624875,100,
788 −6291456,24,pat1-2-4_q1_bothbits4,1-2-4,3,1,quantizedBoth,4,0.04787923641838887,0.009238516815904034,100,
789 −6291456,24,pat1-2-4_q1_bothbits52,1-2-4,3,1,quantizedBoth,52,0.0020052435287412997,-0.0016459949131459291,100,
790 −6291456,24,pat1-2-4_q1_bothbits6,1-2-4,3,1,quantizedBoth,6,0.013737751248475165,0.0005313462458544529,100,
791 −6291456,24,pat1-2-4_q1_bothbits8,1-2-4,3,1,quantizedBoth,8,0.005099457928699871,-0.0013095233433090578,100,
792 −6291456,24,pat1-2-4_q1_gbits12,1-2-4,3,1,quantizedg,12,0.001982091958172051,-0.00161925944777042,100,
793 −6291456,24,pat1-2-4_q1_gbits16,1-2-4,3,1,quantizedg,16,0.0020053358511086254,-0.0016462249736373274,100,
794 −6291456,24,pat1-2-4_q1_gbits2,1-2-4,3,1,quantizedg,2,0.1940872170264872,0.01639779493656739,100,
795 −6291456,24,pat1-2-4_q1_gbits24,1-2-4,3,1,quantizedg,24,0.0020052284232790867,-0.0016459860381892902,100,
796 −6291456,24,pat1-2-4_q1_gbits3,1-2-4,3,1,quantizedg,3,0.10697892522269332,-0.004292802775699215,100,
797 −6291456,24,pat1-2-4_q1_gbits4,1-2-4,3,1,quantizedg,4,0.047666407991559884,0.006041921056905957,100,
798 −6291456,24,pat1-2-4_q1_gbits52,1-2-4,3,1,quantizedg,52,0.0020052435287412997,-0.0016459949131459291,100,
799 −6291456,24,pat1-2-4_q1_gbits6,1-2-4,3,1,quantizedg,6,0.014333022012175706,-0.002678568886806993,100,
800 −6291456,24,pat1-2-4_q1_gbits8,1-2-4,3,1,quantizedg,8,0.0038162568308220883,-0.0013825910245255008,100,
801 −6291456,24,pat1-2-4_q1_single,1-2-4,3,1,single,64,0.0020052435287412997,-0.0016459949131459291,100,
802 −6291456,24,pat1-2-4_q1_stale,1-2-4,3,1,stale,64,0.08318937860698805,0.07801057323069867,100,
803 −6291456,24,pat1-2-4_q2,1-2-4,3,2,exact,64,2.8158417021352474e-09,-1.6032654219797013e-09,100,1.0
804 −6291456,24,pat1-2-4_q2_single,1-2-4,3,2,single,64,2.8158417021352474e-09,-1.6032654219797013e-09,100,
805 −6291456,24,pat1-2-4_q2_stale,1-2-4,3,2,stale,64,0.0033334687265116065,0.003123994013545359,100,
806 −6291456,24,pat1-2-4_q3,1-2-4,3,3,exact,64,3.175100583523304e-13,1.670848457331325e-14,100,1.0
807 −6291456,24,pat1-2-4_q3_single,1-2-4,3,3,single,64,3.175100583523304e-13,1.670848457331325e-14,100,
808 −6291456,24,pat1-2-4_q3_stale,1-2-4,3,3,stale,64,0.00013345734436320995,0.00012500220324905895,100,
809 −6291456,24,pat1-2_q0,1-2,2,0,exact,64,9.971840485025675,-9.961177777513003,100,1.0
810 −6291456,24,pat1-2_q1,1-2,2,1,exact,64,0.03980962360598904,-0.03964284487062894,100,1.0
811 −6291456,24,pat1-2_q1_Hbits12,1-2,2,1,quantizedH,12,0.04026453740453809,-0.04005842870029107,100,
812 −6291456,24,pat1-2_q1_Hbits16,1-2,2,1,quantizedH,16,0.03979651026185885,-0.039630806232244145,100,
813 −6291456,24,pat1-2_q1_Hbits2,1-2,2,1,quantizedH,2,0.04016207116071709,0.03942200199706642,100,
814 −6291456,24,pat1-2_q1_Hbits24,1-2,2,1,quantizedH,24,0.03980963757550623,-0.03964285440149107,100,
815 −6291456,24,pat1-2_q1_Hbits3,1-2,2,1,quantizedH,3,0.04016207116071709,0.03942200199706642,100,
816 −6291456,24,pat1-2_q1_Hbits4,1-2,2,1,quantizedH,4,0.04016207116071709,0.03942200199706642,100,
817 −6291456,24,pat1-2_q1_Hbits52,1-2,2,1,quantizedH,52,0.03980962360598904,-0.03964284487062894,100,
818 −6291456,24,pat1-2_q1_Hbits6,1-2,2,1,quantizedH,6,0.04016207116071709,0.03942200199706642,100,
819 −6291456,24,pat1-2_q1_Hbits8,1-2,2,1,quantizedH,8,0.03886801205631043,-0.038102027301498864,100,
820 −6291456,24,pat1-2_q1_bothbits12,1-2,2,1,quantizedBoth,12,0.0403695484876065,-0.04016102386444367,100,
821 −6291456,24,pat1-2_q1_bothbits16,1-2,2,1,quantizedBoth,16,0.03979422620812405,-0.03962808631317011,100,
822 −6291456,24,pat1-2_q1_bothbits2,1-2,2,1,quantizedBoth,2,0.4890606530220518,-0.1632188063802608,100,
823 −6291456,24,pat1-2_q1_bothbits24,1-2,2,1,quantizedBoth,24,0.039809624633110476,-0.03964284264881264,100,
824 −6291456,24,pat1-2_q1_bothbits3,1-2,2,1,quantizedBoth,3,0.45606937917275353,-0.2122086012359244,100,
825 −6291456,24,pat1-2_q1_bothbits4,1-2,2,1,quantizedBoth,4,0.3232539672924755,0.057235270470233565,100,
826 −6291456,24,pat1-2_q1_bothbits52,1-2,2,1,quantizedBoth,52,0.03980962360598904,-0.03964284487062894,100,
827 −6291456,24,pat1-2_q1_bothbits6,1-2,2,1,quantizedBoth,6,0.08400038892477966,0.03733316631010352,100,
828 −6291456,24,pat1-2_q1_bothbits8,1-2,2,1,quantizedBoth,8,0.04357445663139528,-0.03903537290894465,100,
829 −6291456,24,pat1-2_q1_gbits12,1-2,2,1,quantizedg,12,0.03991756410969313,-0.03974543372975692,100,
830 −6291456,24,pat1-2_q1_gbits16,1-2,2,1,quantizedg,16,0.0398073331724792,-0.03964012498767865,100,
831 −6291456,24,pat1-2_q1_gbits2,1-2,2,1,quantizedg,2,0.5214983135815604,-0.2406020810015157,100,
832 −6291456,24,pat1-2_q1_gbits24,1-2,2,1,quantizedg,24,0.03980961066354705,-0.039642833117942165,100,
833 −6291456,24,pat1-2_q1_gbits3,1-2,2,1,quantizedg,3,0.4975937546905604,-0.28923056066748726,100,
834 −6291456,24,pat1-2_q1_gbits4,1-2,2,1,quantizedg,4,0.31419346946443255,-0.022012919126581078,100,
835 −6291456,24,pat1-2_q1_gbits52,1-2,2,1,quantizedg,52,0.03980962360598904,-0.03964284487062894,100,
836 −6291456,24,pat1-2_q1_gbits6,1-2,2,1,quantizedg,6,0.08445208906051092,-0.041718062853841796,100,
837 −6291456,24,pat1-2_q1_gbits8,1-2,2,1,quantizedg,8,0.04453162371777294,-0.04057568837130456,100,
838 −6291456,24,pat1-2_q1_single,1-2,2,1,single,64,0.03980962360598904,-0.03964284487062894,100,
839 −6291456,24,pat1-2_q1_stale,1-2,2,1,stale,64,0.36035272741162555,-0.36007638863919217,100,
840 −6291456,24,pat1-2_q2,1-2,2,2,exact,64,6.421257616347751e-07,-6.318101772746335e-07,100,1.0
841 −6291456,24,pat1-2_q2_single,1-2,2,2,single,64,6.421257616347751e-07,-6.318101772746335e-07,100,
842 −6291456,24,pat1-2_q2_stale,1-2,2,2,stale,64,0.014357753080157137,-0.01434784845328898,100,
843 −6291456,24,pat1-2_q3,1-2,2,3,exact,64,3.075854069372482e-13,2.2277979431084334e-14,100,1.0
844 −6291456,24,pat1-2_q3_single,1-2,2,3,single,64,3.075854069372482e-13,2.2277979431084334e-14,100,
845 −6291456,24,pat1-2_q3_stale,1-2,2,3,stale,64,0.0005739815048754199,-0.0005736213944751331,100,
846 −6291456,24,pat1-3_q0,1-3,2,0,exact,64,15.613263605741658,-15.60857100072742,100,1.0
847 −6291456,24,pat1-3_q1,1-3,2,1,exact,64,0.097303205388094,-0.09718624591338765,100,1.0
848 −6291456,24,pat1-3_q2,1-3,2,2,exact,64,3.792856988593097e-06,-3.7746016697228493e-06,100,1.0
849 −6291456,24,pat1-3_q3,1-3,2,3,exact,64,2.9470996643830675e-13,4.455595886216867e-14,100,1.0
850 −6291456,24,pat1_q0,1,1,0,exact,64,109.03668784319068,109.03619561880888,100,1.0
851 −6291456,24,pat1_q1,1,1,1,exact,64,4.73992472443309,-4.739838401221248,100,1.0
852 −6291456,24,pat1_q1_Hbits12,1,1,1,quantizedH,12,4.739655558895288,-4.739560154719567,100,
853 −6291456,24,pat1_q1_Hbits16,1,1,1,quantizedH,16,4.739928919339881,-4.739842200962899,100,
854 −6291456,24,pat1_q1_Hbits2,1,1,1,quantizedH,2,4.546101659224278,4.545348508306636,100,
855 −6291456,24,pat1_q1_Hbits24,1,1,1,quantizedH,24,4.739924803468145,-4.739838478438051,100,
856 −6291456,24,pat1_q1_Hbits3,1,1,1,quantizedH,3,10.382328245118506,-10.381915364622246,100,
857 −6291456,24,pat1_q1_Hbits4,1,1,1,quantizedH,4,2.4221848369093637,-2.420707965726807,100,
858 −6291456,24,pat1_q1_Hbits52,1,1,1,quantizedH,52,4.739924724433092,-4.7398384012212516,100,
859 −6291456,24,pat1_q1_Hbits6,1,1,1,quantizedH,6,4.310664822363165,-4.309808026481672,100,
860 −6291456,24,pat1_q1_Hbits8,1,1,1,quantizedH,8,4.778501764241425,-4.777642248709728,100,
861 −6291456,24,pat1_q1_bothbits12,1,1,1,quantizedBoth,12,4.737791898815944,-4.737666658913164,100,
862 −6291456,24,pat1_q1_bothbits16,1,1,1,quantizedBoth,16,4.740015541564325,-4.739928856367367,100,
863 −6291456,24,pat1_q1_bothbits2,1,1,1,quantizedBoth,2,8.545594819417326,-8.539312034783663,100,
864 −6291456,24,pat1_q1_bothbits24,1,1,1,quantizedBoth,24,4.739924862486362,-4.739838538450714,100,
865 −6291456,24,pat1_q1_bothbits3,1,1,1,quantizedBoth,3,2.9586743045794592,-2.9404783369934258,100,
866 −6291456,24,pat1_q1_bothbits4,1,1,1,quantizedBoth,4,5.935572034194511,-5.92652297581481,100,
867 −6291456,24,pat1_q1_bothbits52,1,1,1,quantizedBoth,52,4.739924724433092,-4.7398384012212516,100,
868 −6291456,24,pat1_q1_bothbits6,1,1,1,quantizedBoth,6,4.951531248956158,-4.899121176356149,100,
869 −6291456,24,pat1_q1_bothbits8,1,1,1,quantizedBoth,8,4.7804777783309325,-4.775765120243468,100,
870 −6291456,24,pat1_q1_gbits12,1,1,1,quantizedg,12,4.738060559111038,-4.737944880541475,100,
871 −6291456,24,pat1_q1_gbits16,1,1,1,quantizedg,16,4.740011348439026,-4.739925056695304,100,
872 −6291456,24,pat1_q1_gbits2,1,1,1,quantizedg,2,18.989796883278274,-18.98720671358375,100,
873 −6291456,24,pat1_q1_gbits24,1,1,1,quantizedg,24,4.739924783451465,-4.739838461233919,100,
874 −6291456,24,pat1_q1_gbits3,1,1,1,quantizedg,3,2.370890580765259,2.3500270084816886,100,
875 −6291456,24,pat1_q1_gbits4,1,1,1,quantizedg,4,8.32449997375676,-8.31858985255104,100,
876 −6291456,24,pat1_q1_gbits52,1,1,1,quantizedg,52,4.739924724433092,-4.7398384012212516,100,
877 −6291456,24,pat1_q1_gbits6,1,1,1,quantizedg,6,5.38148948007343,-5.3314835163968155,100,
878 −6291456,24,pat1_q1_gbits8,1,1,1,quantizedg,8,4.741678779248843,-4.737951703912514,100,
879 −6291456,24,pat1_q1_single,1,1,1,single,64,4.739924724433098,-4.739838401221256,100,
880 −6291456,24,pat1_q1_stale,1,1,1,stale,64,8.721043081406435,8.720893091296448,100,
881 −6291456,24,pat1_q2,1,1,2,exact,64,0.008957630727392264,-0.008956973504415431,100,1.0
882 −6291456,24,pat1_q2_single,1,1,2,single,64,0.008957630727397756,-0.008956973504421,100,
883 −6291456,24,pat1_q2_stale,1,1,2,stale,64,0.3777595889502352,0.3777440252609611,100,
884 −6291456,24,pat1_q3,1,1,3,exact,64,3.199873691628786e-08,-3.198930989751232e-08,100,1.0
885 −6291456,24,pat1_q3_single,1,1,3,single,64,3.199872015903501e-08,-3.1989293189027744e-08,100,
886 −6291456,24,pat1_q3_stale,1,1,3,stale,64,0.015161299425971345,0.015160184173586022,100,
760 +6291456,24,pat1-2-3-4_q0,1-2-3-4,4,0,exact,64,2.4111731705478716,-0.44017088807857,300,1.0
761 +6291456,24,pat1-2-3-4_q1,1-2-3-4,4,1,exact,64,0.003906926724598228,-0.0023177959797137746,300,1.0
762 +6291456,24,pat1-2-3-4_q2,1-2-3-4,4,2,exact,64,1.9556426630022855e-08,-6.085529906073862e-09,300,1.0
763 +6291456,24,pat1-2-3-4_q3,1-2-3-4,4,3,exact,64,3.012164893218999e-13,1.2067238858504015e-14,300,1.0
764 +6291456,24,pat1-2-3_q0,1-2-3,3,0,exact,64,1.6968456477840648,1.3797063742829394,300,1.0
765 +6291456,24,pat1-2-3_q1,1-2-3,3,1,exact,64,0.0017522727053054098,-0.0011479436644970006,300,1.0
766 +6291456,24,pat1-2-3_q2,1-2-3,3,2,exact,64,3.2344174985864713e-09,-1.2241331985266507e-09,300,1.0
767 +6291456,24,pat1-2-3_q3,1-2-3,3,3,exact,64,3.033543194789293e-13,2.2277979431084334e-14,300,1.0
768 +6291456,24,pat1-2-4-8_q0,1-2-4-8,4,0,exact,64,1.3024472120286446,-0.9744408522708556,300,1.0
769 +6291456,24,pat1-2-4-8_q1,1-2-4-8,4,1,exact,64,0.0009813907805266686,-0.000676276285060742,300,1.0
770 +6291456,24,pat1-2-4-8_q2,1-2-4-8,4,2,exact,64,8.244104489953272e-10,-3.839368410170214e-10,300,1.0
771 +6291456,24,pat1-2-4-8_q3,1-2-4-8,4,3,exact,64,2.9295048822689583e-13,-7.425993143694777e-15,300,1.0
772 +6291456,24,pat1-2-4_q0,1-2-4,3,0,exact,64,2.0998198163777846,1.9863321284029887,300,1.0
773 +6291456,24,pat1-2-4_q1,1-2-4,3,1,exact,64,0.002111537359746262,-0.001757868700451276,300,1.0
774 +6291456,24,pat1-2-4_q1_Hbits12,1-2-4,3,1,quantizedH,12,0.0021022572496691683,-0.0017470924840383862,300,
775 +6291456,24,pat1-2-4_q1_Hbits16,1-2-4,3,1,quantizedH,16,0.0021122151069881867,-0.001758246578557224,300,
776 +6291456,24,pat1-2-4_q1_Hbits2,1-2-4,3,1,quantizedH,2,0.002743830890217457,0.0017690666698531013,300,
777 +6291456,24,pat1-2-4_q1_Hbits24,1-2-4,3,1,quantizedH,24,0.0021115342616498693,-0.0017578659917079572,300,
778 +6291456,24,pat1-2-4_q1_Hbits3,1-2-4,3,1,quantizedH,3,0.002743830890217457,0.0017690666698531013,300,
779 +6291456,24,pat1-2-4_q1_Hbits4,1-2-4,3,1,quantizedH,4,0.002743830890217457,0.0017690666698531013,300,
780 +6291456,24,pat1-2-4_q1_Hbits52,1-2-4,3,1,quantizedH,52,0.002111537359746262,-0.001757868700451276,300,
781 +6291456,24,pat1-2-4_q1_Hbits6,1-2-4,3,1,quantizedH,6,0.002743830890217457,0.0017690666698531013,300,
782 +6291456,24,pat1-2-4_q1_Hbits8,1-2-4,3,1,quantizedH,8,0.003537705468289356,-0.0014912303861087785,300,
783 +6291456,24,pat1-2-4_q1_bothbits12,1-2-4,3,1,quantizedBoth,12,0.002100245634492451,-0.0017396593113721192,300,
784 +6291456,24,pat1-2-4_q1_bothbits16,1-2-4,3,1,quantizedBoth,16,0.002112447041470371,-0.0017582995684142164,300,
785 +6291456,24,pat1-2-4_q1_bothbits2,1-2-4,3,1,quantizedBoth,2,0.2135026334941154,0.03694654143804295,300,
786 +6291456,24,pat1-2-4_q1_bothbits24,1-2-4,3,1,quantizedBoth,24,0.002111526773474103,-0.0017578605567024777,300,
787 +6291456,24,pat1-2-4_q1_bothbits3,1-2-4,3,1,quantizedBoth,3,0.10564756215943917,-5.0959885244623676e-05,300,
788 +6291456,24,pat1-2-4_q1_bothbits4,1-2-4,3,1,quantizedBoth,4,0.05523849227375273,0.005690031699403445,300,
789 +6291456,24,pat1-2-4_q1_bothbits52,1-2-4,3,1,quantizedBoth,52,0.002111537359746262,-0.001757868700451276,300,
790 +6291456,24,pat1-2-4_q1_bothbits6,1-2-4,3,1,quantizedBoth,6,0.013905499202302501,0.0019583871693821895,300,
791 +6291456,24,pat1-2-4_q1_bothbits8,1-2-4,3,1,quantizedBoth,8,0.005036418998896716,-0.001501685944989096,300,
792 +6291456,24,pat1-2-4_q1_gbits12,1-2-4,3,1,quantizedg,12,0.0021089934346134607,-0.0017504346209385043,300,
793 +6291456,24,pat1-2-4_q1_gbits16,1-2-4,3,1,quantizedg,16,0.002111770742516699,-0.001757921691735913,300,
794 +6291456,24,pat1-2-4_q1_gbits2,1-2-4,3,1,quantizedg,2,0.2129435748797984,0.03350616798384526,300,
795 +6291456,24,pat1-2-4_q1_gbits24,1-2-4,3,1,quantizedg,24,0.0021115298715678682,-0.0017578632654522927,300,
796 +6291456,24,pat1-2-4_q1_gbits3,1-2-4,3,1,quantizedg,3,0.1058456547732417,-0.0035800392913676055,300,
797 +6291456,24,pat1-2-4_q1_gbits4,1-2-4,3,1,quantizedg,4,0.05455526477595933,0.002177363238667795,300,
798 +6291456,24,pat1-2-4_q1_gbits52,1-2-4,3,1,quantizedg,52,0.002111537359746262,-0.001757868700451276,300,
799 +6291456,24,pat1-2-4_q1_gbits6,1-2-4,3,1,quantizedg,6,0.013861031374032242,-0.001568602060307355,300,
800 +6291456,24,pat1-2-4_q1_gbits8,1-2-4,3,1,quantizedg,8,0.004025288969504581,-0.001768062103697865,300,
801 +6291456,24,pat1-2-4_q1_single,1-2-4,3,1,single,64,0.002111537359745394,-0.0017578687004503476,300,
802 +6291456,24,pat1-2-4_q1_stale,1-2-4,3,1,stale,64,0.08600597453284377,0.0811617379382603,300,
803 +6291456,24,pat1-2-4_q2,1-2-4,3,2,exact,64,3.0713701059061907e-09,-1.7774968578644974e-09,300,1.0
804 +6291456,24,pat1-2-4_q2_single,1-2-4,3,2,single,64,3.071369636321931e-09,-1.7774959296153544e-09,300,
805 +6291456,24,pat1-2-4_q2_stale,1-2-4,3,2,stale,64,0.003446172195298379,0.003250280733833366,300,
806 +6291456,24,pat1-2-4_q3,1-2-4,3,3,exact,64,2.9295048822689583e-13,1.4851986287389554e-14,300,1.0
807 +6291456,24,pat1-2-4_q3_single,1-2-4,3,3,single,64,2.9339134699884974e-13,1.57802354303514e-14,300,
808 +6291456,24,pat1-2-4_q3_stale,1-2-4,3,3,stale,64,0.00013796048713882986,0.000130056237760774,300,
809 +6291456,24,pat1-2_q0,1-2,2,0,exact,64,9.932332196635212,-9.92172480646087,300,1.0
810 +6291456,24,pat1-2_q1,1-2,2,1,exact,64,0.039494649332837986,-0.039329818419138685,300,1.0
811 +6291456,24,pat1-2_q1_Hbits12,1-2,2,1,quantizedH,12,0.039626198624626664,-0.039429010171350844,300,
812 +6291456,24,pat1-2_q1_Hbits16,1-2,2,1,quantizedH,16,0.03948869342242451,-0.03932440537939669,300,
813 +6291456,24,pat1-2_q1_Hbits2,1-2,2,1,quantizedH,2,0.040186051989158506,0.03928133659210576,300,
814 +6291456,24,pat1-2_q1_Hbits24,1-2,2,1,quantizedH,24,0.03949463997144342,-0.03932980971203641,300,
815 +6291456,24,pat1-2_q1_Hbits3,1-2,2,1,quantizedH,3,0.040186051989158506,0.03928133659210576,300,
816 +6291456,24,pat1-2_q1_Hbits4,1-2,2,1,quantizedH,4,0.040186051989158506,0.03928133659210576,300,
817 +6291456,24,pat1-2_q1_Hbits52,1-2,2,1,quantizedH,52,0.03949464933283708,-0.039329818419137755,300,
818 +6291456,24,pat1-2_q1_Hbits6,1-2,2,1,quantizedH,6,0.040186051989158506,0.03928133659210576,300,
819 +6291456,24,pat1-2_q1_Hbits8,1-2,2,1,quantizedH,8,0.03873168631959855,-0.037935765292045835,300,
820 +6291456,24,pat1-2_q1_bothbits12,1-2,2,1,quantizedBoth,12,0.03967552406776922,-0.03947152262482188,300,
821 +6291456,24,pat1-2_q1_bothbits16,1-2,2,1,quantizedBoth,16,0.03948944604179537,-0.03932541803847168,300,
822 +6291456,24,pat1-2_q1_bothbits2,1-2,2,1,quantizedBoth,2,0.47308372332805265,-0.1319308011374199,300,
823 +6291456,24,pat1-2_q1_bothbits24,1-2,2,1,quantizedBoth,24,0.03949461790503233,-0.039329787864576145,300,
824 +6291456,24,pat1-2_q1_bothbits3,1-2,2,1,quantizedBoth,3,0.4296113226195683,-0.19316804470700027,300,
825 +6291456,24,pat1-2_q1_bothbits4,1-2,2,1,quantizedBoth,4,0.311690710488258,0.02728603214349408,300,
826 +6291456,24,pat1-2_q1_bothbits52,1-2,2,1,quantizedBoth,52,0.03949464933283708,-0.039329818419137755,300,
827 +6291456,24,pat1-2_q1_bothbits6,1-2,2,1,quantizedBoth,6,0.08070277569121927,0.030347894321969323,300,
828 +6291456,24,pat1-2_q1_bothbits8,1-2,2,1,quantizedBoth,8,0.04137089716241472,-0.03629310084426537,300,
829 +6291456,24,pat1-2_q1_gbits12,1-2,2,1,quantizedg,12,0.03954133672370063,-0.03937234208706145,300,
830 +6291456,24,pat1-2_q1_gbits16,1-2,2,1,quantizedg,16,0.039495392223662586,-0.03933083111821379,300,
831 +6291456,24,pat1-2_q1_gbits2,1-2,2,1,quantizedg,2,0.5026761016630958,-0.20905384571946356,300,
832 +6291456,24,pat1-2_q1_gbits24,1-2,2,1,quantizedg,24,0.039494627266332176,-0.03932979657166635,300,
833 +6291456,24,pat1-2_q1_gbits3,1-2,2,1,quantizedg,3,0.4706590918674665,-0.26986556182270066,300,
834 +6291456,24,pat1-2_q1_gbits4,1-2,2,1,quantizedg,4,0.3108694191883575,-0.05125765067700438,300,
835 +6291456,24,pat1-2_q1_gbits52,1-2,2,1,quantizedg,52,0.039494649332837986,-0.039329818419138685,300,
836 +6291456,24,pat1-2_q1_gbits6,1-2,2,1,quantizedg,6,0.08804270089047436,-0.04819263178642028,300,
837 +6291456,24,pat1-2_q1_gbits8,1-2,2,1,quantizedg,8,0.04219688157278722,-0.037686707180495375,300,
838 +6291456,24,pat1-2_q1_single,1-2,2,1,single,64,0.039494649332837986,-0.039329818419138685,300,
839 +6291456,24,pat1-2_q1_stale,1-2,2,1,stale,64,0.35914576826150063,-0.358865454512399,300,
840 +6291456,24,pat1-2_q2,1-2,2,2,exact,64,6.319167363089957e-07,-6.218634929510041e-07,300,1.0
841 +6291456,24,pat1-2_q2_single,1-2,2,2,single,64,6.319167363089957e-07,-6.218634929510041e-07,300,
842 +6291456,24,pat1-2_q2_stale,1-2,2,2,stale,64,0.0143122569196587,-0.014302036576447873,300,
843 +6291456,24,pat1-2_q3,1-2,2,3,exact,64,2.858042782913011e-13,9.282491429618474e-15,300,1.0
844 +6291456,24,pat1-2_q3_single,1-2,2,3,single,64,2.858042782913011e-13,9.282491429618474e-15,300,
845 +6291456,24,pat1-2_q3_stale,1-2,2,3,stale,64,0.0005722585117523243,-0.000571880139281045,300,
846 +6291456,24,pat1-3_q0,1-3,2,0,exact,64,15.57755716904609,-15.572440396832787,300,1.0
847 +6291456,24,pat1-3_q1,1-3,2,1,exact,64,0.09686951140035317,-0.09674298864512153,300,1.0
848 +6291456,24,pat1-3_q2,1-3,2,2,exact,64,3.760447117925028e-06,-3.7410683315506647e-06,300,1.0
849 +6291456,24,pat1-3_q3,1-3,2,3,exact,64,2.893994419845934e-13,1.2995488001465861e-14,300,1.0
850 +6291456,24,pat1_q0,1,1,0,exact,64,109.04465311478272,109.0441394758334,300,1.0
851 +6291456,24,pat1_q1,1,1,1,exact,64,4.740639693901819,-4.740551646160533,300,1.0
852 +6291456,24,pat1_q1_Hbits12,1,1,1,quantizedH,12,4.740739345034606,-4.740639786882569,300,
853 +6291456,24,pat1_q1_Hbits16,1,1,1,quantizedH,16,4.740598618677345,-4.740510491929185,300,
854 +6291456,24,pat1_q1_Hbits2,1,1,1,quantizedH,2,4.545930902857935,4.545055816158934,300,
855 +6291456,24,pat1_q1_Hbits24,1,1,1,quantizedH,24,4.7406397238157405,-4.740551675452061,300,
856 +6291456,24,pat1_q1_Hbits3,1,1,1,quantizedH,3,10.383788806262242,-10.383384706651688,300,
857 +6291456,24,pat1_q1_Hbits4,1,1,1,quantizedH,4,2.4231356356330283,-2.4215497611526557,300,
858 +6291456,24,pat1_q1_Hbits52,1,1,1,quantizedH,52,4.74063969390182,-4.740551646160534,300,
859 +6291456,24,pat1_q1_Hbits6,1,1,1,quantizedH,6,4.31169786926314,-4.310798731271087,300,
860 +6291456,24,pat1_q1_Hbits8,1,1,1,quantizedH,8,4.77804989728036,-4.777094188279805,300,
861 +6291456,24,pat1_q1_bothbits12,1,1,1,quantizedBoth,12,4.740450544873597,-4.740335606020888,300,
862 +6291456,24,pat1_q1_bothbits16,1,1,1,quantizedBoth,16,4.740668021288285,-4.74057989094596,300,
863 +6291456,24,pat1_q1_bothbits2,1,1,1,quantizedBoth,2,8.53793077289599,-8.531368177759129,300,
864 +6291456,24,pat1_q1_bothbits24,1,1,1,quantizedBoth,24,4.740639672165053,-4.740551624997334,300,
865 +6291456,24,pat1_q1_bothbits3,1,1,1,quantizedBoth,3,2.9515720175000957,-2.9325344799688904,300,
866 +6291456,24,pat1_q1_bothbits4,1,1,1,quantizedBoth,4,5.928034892244096,-5.9185791187902765,300,
867 +6291456,24,pat1_q1_bothbits52,1,1,1,quantizedBoth,52,4.74063969390182,-4.740551646160534,300,
868 +6291456,24,pat1_q1_bothbits6,1,1,1,quantizedBoth,6,5.020400259248832,-4.979746439974628,300,
869 +6291456,24,pat1_q1_bothbits8,1,1,1,quantizedBoth,8,4.767163863188342,-4.761800447464586,300,
870 +6291456,24,pat1_q1_gbits12,1,1,1,quantizedg,12,4.740352280544012,-4.74024752072776,300,
871 +6291456,24,pat1_q1_gbits16,1,1,1,quantizedg,16,4.740709096552119,-4.740621045203315,300,
872 +6291456,24,pat1_q1_gbits2,1,1,1,quantizedg,2,18.9812883418695,-18.978864783305937,300,
873 +6291456,24,pat1_q1_gbits24,1,1,1,quantizedg,24,4.740639642251259,-4.740551595705812,300,
874 +6291456,24,pat1_q1_gbits3,1,1,1,quantizedg,3,2.3780956590748823,2.3583025932172923,300,
875 +6291456,24,pat1_q1_gbits4,1,1,1,quantizedg,4,8.315862297504655,-8.310281095044326,300,
876 +6291456,24,pat1_q1_gbits52,1,1,1,quantizedg,52,4.740639693901821,-4.740551646160535,300,
877 +6291456,24,pat1_q1_gbits6,1,1,1,quantizedg,6,5.449652977290896,-5.4120602537458655,300,
878 +6291456,24,pat1_q1_gbits8,1,1,1,quantizedg,8,4.729334385487147,-4.725244659201141,300,
879 +6291456,24,pat1_q1_single,1,1,1,single,64,4.740639693901822,-4.740551646160537,300,
880 +6291456,24,pat1_q1_stale,1,1,1,stale,64,8.722617999766138,8.722469077025844,300,
881 +6291456,24,pat1_q2,1,1,2,exact,64,0.008960374644583442,-0.008959711173781477,300,1.0
882 +6291456,24,pat1_q2_single,1,1,2,single,64,0.00896037464458154,-0.008959711173779621,300,
883 +6291456,24,pat1_q2_stale,1,1,2,stale,64,0.37788355357962145,0.3778686137075084,300,
884 +6291456,24,pat1_q3,1,1,3,exact,64,3.201850654408515e-08,-3.200901755506654e-08,300,1.0
885 +6291456,24,pat1_q3_single,1,1,3,single,64,3.2018500865324653e-08,-3.200901198557168e-08,300,
886 +6291456,24,pat1_q3_stale,1,1,3,stale,64,0.015168455328555834,0.01516740340434592,300,
887 887 6291456,96,pat1-2-3-4_q0,1-2-3-4,4,0,exact,64,0.9571000199160629,-0.0021729995637650053,1000,1.0
888 888 6291456,96,pat1-2-3-4_q1,1-2-3-4,4,1,exact,64,0.000645811853752122,-0.00036519137618658206,1000,1.0
889 889 6291456,96,pat1-2-3-4_q2,1-2-3-4,4,2,exact,64,6.127309313644234e-10,-1.6625276320138148e-10,1000,1.0
modified results/processed/ablation_logistic_summary.csv +508 −0
@@ -253,3 +253,511 @@ N,m,variant,pattern,r,q,hessian,bits,rms,mean0,n,valid
253 253 196608,192,pat1_q3,1,1,3,exact,64,1.9853099476732712e-10,-5.1954821232532e-11,400,1.0
254 254 196608,192,pat1_q3_single,1,1,3,single,64,0.8159298315844629,-0.05223291474973047,400,
255 255 196608,192,pat1_q3_stale,1,1,3,stale,64,0.0004861281912600072,-2.799877484371397e-05,400,
256 +196608,384,pat1-2-3-4_q0,1-2-3-4,4,0,exact,64,7.733350534846879,-0.07475528439907486,400,1.0
257 +196608,384,pat1-2-3-4_q1,1-2-3-4,4,1,exact,64,0.04524632086100771,-0.008814739660483439,400,1.0
258 +196608,384,pat1-2-3-4_q2,1-2-3-4,4,2,exact,64,3.415674931085675e-06,-4.7531320011587734e-07,400,1.0
259 +196608,384,pat1-2-3-4_q3,1-2-3-4,4,3,exact,64,7.645188897493598e-14,-1.907578984892496e-15,400,1.0
260 +196608,384,pat1-2-3_q0,1-2-3,3,0,exact,64,3.2711859595876125,0.0560167665074083,400,1.0
261 +196608,384,pat1-2-3_q1,1-2-3,3,1,exact,64,0.007892072032429,-0.0015908499181389547,400,1.0
262 +196608,384,pat1-2-3_q2,1-2-3,3,2,exact,64,1.0164950408938023e-07,-1.4645491068723711e-08,400,1.0
263 +196608,384,pat1-2-3_q3,1-2-3,3,3,exact,64,6.234177410830129e-14,6.153480596427404e-16,400,1.0
264 +196608,384,pat1-2-4-8_q0,1-2-4-8,4,0,exact,64,28.029152769654704,-2.2680003304766796,400,0.9947607421875
265 +196608,384,pat1-2-4-8_q1,1-2-4-8,4,1,exact,64,3.6261598840916545,-0.12347227924813492,400,0.9947607421875
266 +196608,384,pat1-2-4-8_q2,1-2-4-8,4,2,exact,64,0.21282288344885011,-0.0032323621302444176,400,0.9947607421875
267 +196608,384,pat1-2-4-8_q3,1-2-4-8,4,3,exact,64,0.0008676672929593144,-1.1981636575533278e-05,400,0.9947607421875
268 +196608,384,pat1-2-4_q0,1-2-4,3,0,exact,64,2.2817462627485647,0.09960745014287072,400,1.0
269 +196608,384,pat1-2-4_q1,1-2-4,3,1,exact,64,0.0038414351377092882,-0.0008100355256297837,400,1.0
270 +196608,384,pat1-2-4_q1_Hbits12,1-2-4,3,1,quantizedH,12,0.0038495880233723337,-0.0008082676190854559,400,
271 +196608,384,pat1-2-4_q1_Hbits16,1-2-4,3,1,quantizedH,16,0.0038402820266261583,-0.0008098737843725602,400,
272 +196608,384,pat1-2-4_q1_Hbits2,1-2-4,3,1,quantizedH,2,0.14324445889327203,-0.009573603803408834,400,
273 +196608,384,pat1-2-4_q1_Hbits24,1-2-4,3,1,quantizedH,24,0.003841437997961135,-0.0008100356922939776,400,
274 +196608,384,pat1-2-4_q1_Hbits3,1-2-4,3,1,quantizedH,3,0.12966965492105956,0.004209585200908929,400,
275 +196608,384,pat1-2-4_q1_Hbits4,1-2-4,3,1,quantizedH,4,0.052338151379081356,-0.0018684377051486224,400,
276 +196608,384,pat1-2-4_q1_Hbits52,1-2-4,3,1,quantizedH,52,0.0038414351377093034,-0.0008100355256298452,400,
277 +196608,384,pat1-2-4_q1_Hbits6,1-2-4,3,1,quantizedH,6,0.015579093884073768,-0.001480491852557985,400,
278 +196608,384,pat1-2-4_q1_Hbits8,1-2-4,3,1,quantizedH,8,0.0050425787077649315,-0.0007425838507603114,400,
279 +196608,384,pat1-2-4_q1_bothbits12,1-2-4,3,1,quantizedBoth,12,0.0038653977502441793,-0.0008086926737009875,400,
280 +196608,384,pat1-2-4_q1_bothbits16,1-2-4,3,1,quantizedBoth,16,0.003840746791792292,-0.000809689594210366,400,
281 +196608,384,pat1-2-4_q1_bothbits2,1-2-4,3,1,quantizedBoth,2,0.28206847953261777,-0.015022055364495704,400,
282 +196608,384,pat1-2-4_q1_bothbits24,1-2-4,3,1,quantizedBoth,24,0.0038414349686207677,-0.0008100348519595271,400,
283 +196608,384,pat1-2-4_q1_bothbits3,1-2-4,3,1,quantizedBoth,3,0.17891941737864694,0.0031272412538008803,400,
284 +196608,384,pat1-2-4_q1_bothbits4,1-2-4,3,1,quantizedBoth,4,0.08185612658441138,-0.0009411684268164708,400,
285 +196608,384,pat1-2-4_q1_bothbits52,1-2-4,3,1,quantizedBoth,52,0.0038414351377092783,-0.0008100355256297837,400,
286 +196608,384,pat1-2-4_q1_bothbits6,1-2-4,3,1,quantizedBoth,6,0.02156149118324992,-0.0017867342591996042,400,
287 +196608,384,pat1-2-4_q1_bothbits8,1-2-4,3,1,quantizedBoth,8,0.0062916395293877376,-0.0007515591684721676,400,
288 +196608,384,pat1-2-4_q1_gbits12,1-2-4,3,1,quantizedg,12,0.00385699941217152,-0.0008104604710882932,400,
289 +196608,384,pat1-2-4_q1_gbits16,1-2-4,3,1,quantizedg,16,0.0038419003200105863,-0.0008098513353503055,400,
290 +196608,384,pat1-2-4_q1_gbits2,1-2-4,3,1,quantizedg,2,0.23413877898039492,-0.005745805701089227,400,
291 +196608,384,pat1-2-4_q1_gbits24,1-2-4,3,1,quantizedg,24,0.003841432108368682,-0.000810034685295831,400,
292 +196608,384,pat1-2-4_q1_gbits3,1-2-4,3,1,quantizedg,3,0.12376400921601517,-0.0019464377681875597,400,
293 +196608,384,pat1-2-4_q1_gbits4,1-2-4,3,1,quantizedg,4,0.06148849871739479,0.00010850729257604547,400,
294 +196608,384,pat1-2-4_q1_gbits52,1-2-4,3,1,quantizedg,52,0.0038414351377092223,-0.0008100355256297222,400,
295 +196608,384,pat1-2-4_q1_gbits6,1-2-4,3,1,quantizedg,6,0.01582452567140576,-0.001118099982893709,400,
296 +196608,384,pat1-2-4_q1_gbits8,1-2-4,3,1,quantizedg,8,0.005286061189356118,-0.0008189997424401975,400,
297 +196608,384,pat1-2-4_q1_single,1-2-4,3,1,single,64,0.3578563062309809,-0.003982690142613944,400,
298 +196608,384,pat1-2-4_q1_stale,1-2-4,3,1,stale,64,0.05411884618347463,-0.0008774471687022733,400,
299 +196608,384,pat1-2-4_q2,1-2-4,3,2,exact,64,2.4048112701254045e-08,-3.592771796378164e-09,400,1.0
300 +196608,384,pat1-2-4_q2_single,1-2-4,3,2,single,64,0.0903142609758707,-0.00019998032499142417,400,
301 +196608,384,pat1-2-4_q2_stale,1-2-4,3,2,stale,64,0.001352778594516768,1.5140673174522633e-05,400,
302 +196608,384,pat1-2-4_q3,1-2-4,3,3,exact,64,6.249949413527104e-14,9.230220894641104e-16,400,1.0
303 +196608,384,pat1-2-4_q3_single,1-2-4,3,3,single,64,0.028083946099019576,-0.00011717330098180581,400,
304 +196608,384,pat1-2-4_q3_stale,1-2-4,3,3,stale,64,3.444101838290942e-05,-2.420072602153543e-07,400,
305 +196608,384,pat1-2_q0,1-2,2,0,exact,64,1.9143066701719214,-0.3145479674149128,400,1.0
306 +196608,384,pat1-2_q1,1-2,2,1,exact,64,0.0032735183812437705,-0.0006956819595986257,400,1.0
307 +196608,384,pat1-2_q1_Hbits12,1-2,2,1,quantizedH,12,0.003271259273660929,-0.0006928033517244983,400,
308 +196608,384,pat1-2_q1_Hbits16,1-2,2,1,quantizedH,16,0.0032733899311499317,-0.0006956225509772469,400,
309 +196608,384,pat1-2_q1_Hbits2,1-2,2,1,quantizedH,2,0.12190320441267107,0.03326808481697505,400,
310 +196608,384,pat1-2_q1_Hbits24,1-2,2,1,quantizedH,24,0.003273519217508583,-0.0006956819775269147,400,
311 +196608,384,pat1-2_q1_Hbits3,1-2,2,1,quantizedH,3,0.1097721023638195,-0.014755031713613564,400,
312 +196608,384,pat1-2_q1_Hbits4,1-2,2,1,quantizedH,4,0.043747473314212915,0.0024109065289113552,400,
313 +196608,384,pat1-2_q1_Hbits52,1-2,2,1,quantizedH,52,0.0032735183812437263,-0.0006956819595985642,400,
314 +196608,384,pat1-2_q1_Hbits6,1-2,2,1,quantizedH,6,0.01303883819960067,-0.0021833633615233744,400,
315 +196608,384,pat1-2_q1_Hbits8,1-2,2,1,quantizedH,8,0.004324846904816304,-0.0006604537750094627,400,
316 +196608,384,pat1-2_q1_bothbits12,1-2,2,1,quantizedBoth,12,0.0032748555393939953,-0.0006951924714138274,400,
317 +196608,384,pat1-2_q1_bothbits16,1-2,2,1,quantizedBoth,16,0.0032729812715293904,-0.000695650944530541,400,
318 +196608,384,pat1-2_q1_bothbits2,1-2,2,1,quantizedBoth,2,0.22547646404862012,0.035346202003721044,400,
319 +196608,384,pat1-2_q1_bothbits24,1-2,2,1,quantizedBoth,24,0.0032735192024288145,-0.0006956818631125418,400,
320 +196608,384,pat1-2_q1_bothbits3,1-2,2,1,quantizedBoth,3,0.13741055316409967,-0.014973194557722988,400,
321 +196608,384,pat1-2_q1_bothbits4,1-2,2,1,quantizedBoth,4,0.06460167001183904,0.0012012686812627189,400,
322 +196608,384,pat1-2_q1_bothbits52,1-2,2,1,quantizedBoth,52,0.00327351838124362,-0.0006956819595985642,400,
323 +196608,384,pat1-2_q1_bothbits6,1-2,2,1,quantizedBoth,6,0.017742361472129608,-0.0018782927565750252,400,
324 +196608,384,pat1-2_q1_bothbits8,1-2,2,1,quantizedBoth,8,0.005234787324946448,-0.0006414635518523299,400,
325 +196608,384,pat1-2_q1_gbits12,1-2,2,1,quantizedg,12,0.0032773342910366187,-0.0006980709541803145,400,
326 +196608,384,pat1-2_q1_gbits16,1-2,2,1,quantizedg,16,0.0032731100139497186,-0.0006957103516001987,400,
327 +196608,384,pat1-2_q1_gbits2,1-2,2,1,quantizedg,2,0.18543323853894547,0.0012396007437142098,400,
328 +196608,384,pat1-2_q1_gbits24,1-2,2,1,quantizedg,24,0.0032735183661684888,-0.0006956818451843759,400,
329 +196608,384,pat1-2_q1_gbits3,1-2,2,1,quantizedg,3,0.09465535813785848,-0.0008949304933980332,400,
330 +196608,384,pat1-2_q1_gbits4,1-2,2,1,quantizedg,4,0.04775909214189395,-0.0018970976658512575,400,
331 +196608,384,pat1-2_q1_gbits52,1-2,2,1,quantizedg,52,0.0032735183812437276,-0.000695681959598564,400,
332 +196608,384,pat1-2_q1_gbits6,1-2,2,1,quantizedg,6,0.012154423072370434,-0.0003896518347560711,400,
333 +196608,384,pat1-2_q1_gbits8,1-2,2,1,quantizedg,8,0.004420861953128696,-0.000676639381728216,400,
334 +196608,384,pat1-2_q1_single,1-2,2,1,single,64,0.2725054124966719,0.004490200421937712,400,
335 +196608,384,pat1-2_q1_stale,1-2,2,1,stale,64,0.04507978089549791,0.005951706783819753,400,
336 +196608,384,pat1-2_q2,1-2,2,2,exact,64,1.5330713793626896e-08,-2.5675981138553885e-09,400,1.0
337 +196608,384,pat1-2_q2_single,1-2,2,2,single,64,0.06603108238278063,-0.005955670322115871,400,
338 +196608,384,pat1-2_q2_stale,1-2,2,2,stale,64,0.0010482689640109052,-9.688277038621597e-05,400,
339 +196608,384,pat1-2_q3,1-2,2,3,exact,64,6.243887973430223e-14,4.307436417499182e-16,400,1.0
340 +196608,384,pat1-2_q3_single,1-2,2,3,single,64,0.01939098591608127,0.0004754117213431204,400,
341 +196608,384,pat1-2_q3_stale,1-2,2,3,stale,64,2.561027609364802e-05,1.533478072528534e-06,400,
342 +196608,384,pat1-3_q0,1-3,2,0,exact,64,2.2126373886821433,-0.4998303343760672,400,1.0
343 +196608,384,pat1-3_q1,1-3,2,1,exact,64,0.004790348884130398,-0.0011073559274418277,400,1.0
344 +196608,384,pat1-3_q2,1-3,2,2,exact,64,3.050826226166484e-08,-5.746538863763691e-09,400,1.0
345 +196608,384,pat1-3_q3,1-3,2,3,exact,64,6.208614923855362e-14,1.846044178928221e-15,400,1.0
346 +196608,384,pat1_q0,1,1,0,exact,64,12.539793428103524,3.1763856304080873,400,1.0
347 +196608,384,pat1_q1,1,1,1,exact,64,0.15375550050576145,-0.03996592609498389,400,1.0
348 +196608,384,pat1_q1_Hbits12,1,1,1,quantizedH,12,0.15375070256695447,-0.03997465815603492,400,
349 +196608,384,pat1_q1_Hbits16,1,1,1,quantizedH,16,0.15375436785795182,-0.03996623070477716,400,
350 +196608,384,pat1_q1_Hbits2,1,1,1,quantizedH,2,0.8143617835958684,-0.34247791164746344,400,
351 +196608,384,pat1_q1_Hbits24,1,1,1,quantizedH,24,0.15375551131507367,-0.03996592402432647,400,
352 +196608,384,pat1_q1_Hbits3,1,1,1,quantizedH,3,0.7267466077671576,0.032667074319537553,400,
353 +196608,384,pat1_q1_Hbits4,1,1,1,quantizedH,4,0.33668632325166103,-0.0454467282092443,400,
354 +196608,384,pat1_q1_Hbits52,1,1,1,quantizedH,52,0.1537555005057617,-0.03996592609498389,400,
355 +196608,384,pat1_q1_Hbits6,1,1,1,quantizedH,6,0.17192400147672693,-0.04513452413231761,400,
356 +196608,384,pat1_q1_Hbits8,1,1,1,quantizedH,8,0.15458768369240514,-0.040336961096358113,400,
357 +196608,384,pat1_q1_bothbits12,1,1,1,quantizedBoth,12,0.15374274654726938,-0.03997724292161445,400,
358 +196608,384,pat1_q1_bothbits16,1,1,1,quantizedBoth,16,0.15375359691416104,-0.03996732799492693,400,
359 +196608,384,pat1_q1_bothbits2,1,1,1,quantizedBoth,2,1.164241443090455,-0.28007725280024004,400,
360 +196608,384,pat1_q1_bothbits24,1,1,1,quantizedBoth,24,0.1537555065818816,-0.03996592283739206,400,
361 +196608,384,pat1_q1_bothbits3,1,1,1,quantizedBoth,3,0.8512124832620546,0.05168938920596115,400,
362 +196608,384,pat1_q1_bothbits4,1,1,1,quantizedBoth,4,0.40726513684086796,-0.03895211251516629,400,
363 +196608,384,pat1_q1_bothbits52,1,1,1,quantizedBoth,52,0.15375550050576162,-0.03996592609498401,400,
364 +196608,384,pat1_q1_bothbits6,1,1,1,quantizedBoth,6,0.18306679865836958,-0.046369181022526934,400,
365 +196608,384,pat1_q1_bothbits8,1,1,1,quantizedBoth,8,0.15574622827530465,-0.040215914257387665,400,
366 +196608,384,pat1_q1_gbits12,1,1,1,quantizedg,12,0.15374785151710682,-0.039968511930566934,400,
367 +196608,384,pat1_q1_gbits16,1,1,1,quantizedg,16,0.15375472833137785,-0.039967023384482686,400,
368 +196608,384,pat1_q1_gbits2,1,1,1,quantizedg,2,0.9041034146261923,0.01716190568568566,400,
369 +196608,384,pat1_q1_gbits24,1,1,1,quantizedg,24,0.15375549577257272,-0.03996592490804929,400,
370 +196608,384,pat1_q1_gbits3,1,1,1,quantizedg,3,0.49245229174060523,-0.020379133428573587,400,
371 +196608,384,pat1_q1_gbits4,1,1,1,quantizedg,4,0.28388638440037034,-0.033509781356286336,400,
372 +196608,384,pat1_q1_gbits52,1,1,1,quantizedg,52,0.15375550050576142,-0.039965926094983825,400,
373 +196608,384,pat1_q1_gbits6,1,1,1,quantizedg,6,0.16522601805016035,-0.04119674417018161,400,
374 +196608,384,pat1_q1_gbits8,1,1,1,quantizedg,8,0.15491457342234874,-0.03984444024308276,400,
375 +196608,384,pat1_q1_single,1,1,1,single,64,1.4742672395451388,-0.09577159443842748,400,
376 +196608,384,pat1_q1_stale,1,1,1,stale,64,0.07564091370931468,-0.011688604884125285,400,
377 +196608,384,pat1_q2,1,1,2,exact,64,2.3086560984800187e-05,-6.049803998394885e-06,400,1.0
378 +196608,384,pat1_q2_single,1,1,2,single,64,0.3546385929834056,0.04483136040855015,400,
379 +196608,384,pat1_q2_stale,1,1,2,stale,64,0.0014601199170811941,0.0001549030316300936,400,
380 +196608,384,pat1_q3,1,1,3,exact,64,5.452081040895352e-13,-1.3697647807647405e-13,400,1.0
381 +196608,384,pat1_q3_single,1,1,3,single,64,0.09928136430257321,-0.004663568767423621,400,
382 +196608,384,pat1_q3_stale,1,1,3,stale,64,2.9353596067044334e-05,-1.530928029679472e-06,400,
383 +196608,768,pat1-2-3-4_q0,1-2-3-4,4,0,exact,64,5.011752477685713,-0.007394733868905977,400,1.0
384 +196608,768,pat1-2-3-4_q1,1-2-3-4,4,1,exact,64,0.01880844241890707,-0.0037452407965326323,400,1.0
385 +196608,768,pat1-2-3-4_q2,1-2-3-4,4,2,exact,64,5.771759357072456e-07,-8.450524044556625e-08,400,1.0
386 +196608,768,pat1-2-3-4_q3,1-2-3-4,4,3,exact,64,6.46613409651872e-14,1.7229745669996733e-15,400,1.0
387 +196608,768,pat1-2-3_q0,1-2-3,3,0,exact,64,2.188827897629002,0.010824096326452839,400,1.0
388 +196608,768,pat1-2-3_q1,1-2-3,3,1,exact,64,0.0035578718359183473,-0.0007192880790334483,400,1.0
389 +196608,768,pat1-2-3_q2,1-2-3,3,2,exact,64,2.2087162575281653e-08,-3.069831477874063e-09,400,1.0
390 +196608,768,pat1-2-3_q3,1-2-3,3,3,exact,64,6.456464557850137e-14,1.6614397610353993e-15,400,1.0
391 +196608,768,pat1-2-4-8_q0,1-2-4-8,4,0,exact,64,1.9138771952968514,0.0021022288743869537,400,1.0
392 +196608,768,pat1-2-4-8_q1,1-2-4-8,4,1,exact,64,0.0026801229369853175,-0.000555490859621294,400,1.0
393 +196608,768,pat1-2-4-8_q2,1-2-4-8,4,2,exact,64,1.2197416564636568e-08,-1.7579833795525097e-09,400,1.0
394 +196608,768,pat1-2-4-8_q3,1-2-4-8,4,3,exact,64,6.448542332454546e-14,1.1691613133212068e-15,400,1.0
395 +196608,768,pat1-2-4_q0,1-2-4,3,0,exact,64,1.5586626900222154,0.01689703972488076,400,1.0
396 +196608,768,pat1-2-4_q1,1-2-4,3,1,exact,64,0.0017739620988378166,-0.00036643005565858435,400,1.0
397 +196608,768,pat1-2-4_q1_Hbits12,1-2-4,3,1,quantizedH,12,0.0017797387419156538,-0.0003685819885308105,400,
398 +196608,768,pat1-2-4_q1_Hbits16,1-2-4,3,1,quantizedH,16,0.0017739079181083924,-0.0003665712511217174,400,
399 +196608,768,pat1-2-4_q1_Hbits2,1-2-4,3,1,quantizedH,2,0.09597114913982217,-0.0013805900141857091,400,
400 +196608,768,pat1-2-4_q1_Hbits24,1-2-4,3,1,quantizedH,24,0.001773964754582145,-0.00036642965014421167,400,
401 +196608,768,pat1-2-4_q1_Hbits3,1-2-4,3,1,quantizedH,3,0.0871425544093131,0.000896938028110618,400,
402 +196608,768,pat1-2-4_q1_Hbits4,1-2-4,3,1,quantizedH,4,0.03614558119804557,-0.0005993841171279731,400,
403 +196608,768,pat1-2-4_q1_Hbits52,1-2-4,3,1,quantizedH,52,0.0017739620988377759,-0.0003664300556585229,400,
404 +196608,768,pat1-2-4_q1_Hbits6,1-2-4,3,1,quantizedH,6,0.010814453029664476,-0.00047650735700656774,400,
405 +196608,768,pat1-2-4_q1_Hbits8,1-2-4,3,1,quantizedH,8,0.002790794196998082,-0.00030348712536647167,400,
406 +196608,768,pat1-2-4_q1_bothbits12,1-2-4,3,1,quantizedBoth,12,0.0017758734408788292,-0.0003651786582911209,400,
407 +196608,768,pat1-2-4_q1_bothbits16,1-2-4,3,1,quantizedBoth,16,0.001774070270449351,-0.0003667683967975919,400,
408 +196608,768,pat1-2-4_q1_bothbits2,1-2-4,3,1,quantizedBoth,2,0.19545439895695385,0.0004967573999185213,400,
409 +196608,768,pat1-2-4_q1_bothbits24,1-2-4,3,1,quantizedBoth,24,0.0017739657878891738,-0.0003664303559025945,400,
410 +196608,768,pat1-2-4_q1_bothbits3,1-2-4,3,1,quantizedBoth,3,0.12174963429631652,-4.2648432968273934e-05,400,
411 +196608,768,pat1-2-4_q1_bothbits4,1-2-4,3,1,quantizedBoth,4,0.05579674120162243,5.670695380820202e-05,400,
412 +196608,768,pat1-2-4_q1_bothbits52,1-2-4,3,1,quantizedBoth,52,0.0017739620988380144,-0.0003664300556585844,400,
413 +196608,768,pat1-2-4_q1_bothbits6,1-2-4,3,1,quantizedBoth,6,0.014479628610347491,-0.0005622735861089477,400,
414 +196608,768,pat1-2-4_q1_bothbits8,1-2-4,3,1,quantizedBoth,8,0.0037969860105957075,-0.0003149317577349911,400,
415 +196608,768,pat1-2-4_q1_gbits12,1-2-4,3,1,quantizedg,12,0.001769651206990958,-0.00036302639419530993,400,
416 +196608,768,pat1-2-4_q1_gbits16,1-2-4,3,1,quantizedg,16,0.0017741227930826635,-0.00036662720137033334,400,
417 +196608,768,pat1-2-4_q1_gbits2,1-2-4,3,1,quantizedg,2,0.16911659034744408,0.0013265811517595742,400,
418 +196608,768,pat1-2-4_q1_gbits24,1-2-4,3,1,quantizedg,24,0.001773963132122099,-0.00036643076141597714,400,
419 +196608,768,pat1-2-4_q1_gbits3,1-2-4,3,1,quantizedg,3,0.08314588680078076,-0.0013786293697535617,400,
420 +196608,768,pat1-2-4_q1_gbits4,1-2-4,3,1,quantizedg,4,0.04155636841153089,0.00028777932734871703,400,
421 +196608,768,pat1-2-4_q1_gbits52,1-2-4,3,1,quantizedg,52,0.0017739620988379361,-0.00036643005565864593,400,
422 +196608,768,pat1-2-4_q1_gbits6,1-2-4,3,1,quantizedg,6,0.010287885888962603,-0.00045603115468475114,400,
423 +196608,768,pat1-2-4_q1_gbits8,1-2-4,3,1,quantizedg,8,0.0031413265727983234,-0.0003778766096392442,400,
424 +196608,768,pat1-2-4_q1_single,1-2-4,3,1,single,64,0.16679252193237706,0.002112805591753514,400,
425 +196608,768,pat1-2-4_q1_stale,1-2-4,3,1,stale,64,0.018654572587562698,9.669954094960801e-05,400,
426 +196608,768,pat1-2-4_q2,1-2-4,3,2,exact,64,5.370787578617583e-09,-7.621936129693766e-10,400,1.0
427 +196608,768,pat1-2-4_q2_single,1-2-4,3,2,single,64,0.028167929345602465,-0.0008760744730580213,400,
428 +196608,768,pat1-2-4_q2_stale,1-2-4,3,2,stale,64,0.00022974592900204145,9.765136618649583e-07,400,
429 +196608,768,pat1-2-4_q3,1-2-4,3,3,exact,64,6.38688601380521e-14,1.8460441789282216e-15,400,1.0
430 +196608,768,pat1-2-4_q3_single,1-2-4,3,3,single,64,0.005715501295829811,0.00018375104650712043,400,
431 +196608,768,pat1-2-4_q3_stale,1-2-4,3,3,stale,64,2.9034938965330638e-06,-2.973745856764264e-08,400,
432 +196608,768,pat1-2_q0,1-2,2,0,exact,64,1.1299269223173396,-0.05889809956182143,400,1.0
433 +196608,768,pat1-2_q1,1-2,2,1,exact,64,0.0009828690014311268,-0.00019561986176495075,400,1.0
434 +196608,768,pat1-2_q1_Hbits12,1-2,2,1,quantizedH,12,0.0009870580449500982,-0.00019471237689887473,400,
435 +196608,768,pat1-2_q1_Hbits16,1-2,2,1,quantizedH,16,0.0009829074622764783,-0.00019567624036633677,400,
436 +196608,768,pat1-2_q1_Hbits2,1-2,2,1,quantizedH,2,0.07017148185414421,0.006480906106249112,400,
437 +196608,768,pat1-2_q1_Hbits24,1-2,2,1,quantizedH,24,0.0009828683259498457,-0.00019561995712187097,400,
438 +196608,768,pat1-2_q1_Hbits3,1-2,2,1,quantizedH,3,0.06379191706599606,-0.00244355089118738,400,
439 +196608,768,pat1-2_q1_Hbits4,1-2,2,1,quantizedH,4,0.026162124060008517,0.00024738108746945016,400,
440 +196608,768,pat1-2_q1_Hbits52,1-2,2,1,quantizedH,52,0.0009828690014311765,-0.00019561986176501228,400,
441 +196608,768,pat1-2_q1_Hbits6,1-2,2,1,quantizedH,6,0.007706575549332022,-0.0006168655528701559,400,
442 +196608,768,pat1-2_q1_Hbits8,1-2,2,1,quantizedH,8,0.001879080688875885,-0.0001630450736993014,400,
443 +196608,768,pat1-2_q1_bothbits12,1-2,2,1,quantizedBoth,12,0.0009916869229530327,-0.00019616206548173174,400,
444 +196608,768,pat1-2_q1_bothbits16,1-2,2,1,quantizedBoth,16,0.0009827056338576807,-0.00019561434585134421,400,
445 +196608,768,pat1-2_q1_bothbits2,1-2,2,1,quantizedBoth,2,0.13736587547028964,0.004141659360512987,400,
446 +196608,768,pat1-2_q1_bothbits24,1-2,2,1,quantizedBoth,24,0.0009828684260749358,-0.00019561965283662448,400,
447 +196608,768,pat1-2_q1_bothbits3,1-2,2,1,quantizedBoth,3,0.08601753071375846,-0.0019888717068458454,400,
448 +196608,768,pat1-2_q1_bothbits4,1-2,2,1,quantizedBoth,4,0.03955346955419754,0.0001965110238264099,400,
449 +196608,768,pat1-2_q1_bothbits52,1-2,2,1,quantizedBoth,52,0.0009828690014311331,-0.00019561986176501228,400,
450 +196608,768,pat1-2_q1_bothbits6,1-2,2,1,quantizedBoth,6,0.010677394895040488,-0.000497901911121133,400,
451 +196608,768,pat1-2_q1_bothbits8,1-2,2,1,quantizedBoth,8,0.002642172585567249,-0.00016053823574432115,400,
452 +196608,768,pat1-2_q1_gbits12,1-2,2,1,quantizedg,12,0.000987214097798096,-0.00019706949109920546,400,
453 +196608,768,pat1-2_q1_gbits16,1-2,2,1,quantizedg,16,0.0009826683388413067,-0.0001955579690749546,400,
454 +196608,768,pat1-2_q1_gbits2,1-2,2,1,quantizedg,2,0.1162398728491924,-0.0023185432205146688,400,
455 +196608,768,pat1-2_q1_gbits24,1-2,2,1,quantizedg,24,0.0009828691015472315,-0.0001956195574790296,400,
456 +196608,768,pat1-2_q1_gbits3,1-2,2,1,quantizedg,3,0.05956391021025329,0.00028255893765270524,400,
457 +196608,768,pat1-2_q1_gbits4,1-2,2,1,quantizedg,4,0.030513711692143806,-0.00024683809404813954,400,
458 +196608,768,pat1-2_q1_gbits52,1-2,2,1,quantizedg,52,0.0009828690014311362,-0.00019561986176495075,400,
459 +196608,768,pat1-2_q1_gbits6,1-2,2,1,quantizedg,6,0.007327920637651211,-7.638513386002266e-05,400,
460 +196608,768,pat1-2_q1_gbits8,1-2,2,1,quantizedg,8,0.002080420783242019,-0.0001931689597802545,400,
461 +196608,768,pat1-2_q1_single,1-2,2,1,single,64,0.12056243934524465,0.002796311480426655,400,
462 +196608,768,pat1-2_q1_stale,1-2,2,1,stale,64,0.013660933990330441,0.0005499868750836255,400,
463 +196608,768,pat1-2_q2,1-2,2,2,exact,64,1.732672244304225e-09,-2.2766727505909863e-10,400,1.0
464 +196608,768,pat1-2_q2_single,1-2,2,2,single,64,0.02040255079446266,-0.0010542189678932167,400,
465 +196608,768,pat1-2_q2_stale,1-2,2,2,stale,64,0.00016573381259574064,-2.7690841663442196e-06,400,
466 +196608,768,pat1-2_q3,1-2,2,3,exact,64,6.436787779603728e-14,1.415300537178303e-15,400,1.0
467 +196608,768,pat1-2_q3_single,1-2,2,3,single,64,0.00411508786435181,0.00016416583006402137,400,
468 +196608,768,pat1-2_q3_stale,1-2,2,3,stale,64,2.0788197154987486e-06,1.0813732977403355e-09,400,
469 +196608,768,pat1-3_q0,1-3,2,0,exact,64,1.0353866577323187,-0.09375919750595835,400,1.0
470 +196608,768,pat1-3_q1,1-3,2,1,exact,64,0.0008821053227007227,-0.00017417577522241615,400,1.0
471 +196608,768,pat1-3_q2,1-3,2,2,exact,64,1.2357219374204686e-09,-1.808245809016606e-10,400,1.0
472 +196608,768,pat1-3_q3,1-3,2,3,exact,64,6.470817156409456e-14,1.6614397610353993e-15,400,1.0
473 +196608,768,pat1_q0,1,1,0,exact,64,6.151520845555843,1.5721790905210475,400,1.0
474 +196608,768,pat1_q1,1,1,1,exact,64,0.036817536792675784,-0.009604381019031617,400,1.0
475 +196608,768,pat1_q1_Hbits12,1,1,1,quantizedH,12,0.036819875716667394,-0.009603834714117618,400,
476 +196608,768,pat1_q1_Hbits16,1,1,1,quantizedH,16,0.036818715145111966,-0.009603728320179474,400,
477 +196608,768,pat1_q1_Hbits2,1,1,1,quantizedH,2,0.3918162734933197,-0.16494854972087455,400,
478 +196608,768,pat1_q1_Hbits24,1,1,1,quantizedH,24,0.036817530786346225,-0.00960438034258374,400,
479 +196608,768,pat1_q1_Hbits3,1,1,1,quantizedH,3,0.34579262300284186,0.07080167296259027,400,
480 +196608,768,pat1_q1_Hbits4,1,1,1,quantizedH,4,0.15081826470605184,-0.018204852024349797,400,
481 +196608,768,pat1_q1_Hbits52,1,1,1,quantizedH,52,0.036817536792675694,-0.009604381019031678,400,
482 +196608,768,pat1_q1_Hbits6,1,1,1,quantizedH,6,0.06201167571368842,-0.019144514609978572,400,
483 +196608,768,pat1_q1_Hbits8,1,1,1,quantizedH,8,0.03802831281335063,-0.009929699506592745,400,
484 +196608,768,pat1_q1_bothbits12,1,1,1,quantizedBoth,12,0.03682164311508552,-0.0096090676035078,400,
485 +196608,768,pat1_q1_bothbits16,1,1,1,quantizedBoth,16,0.036818019409757353,-0.009603396722788888,400,
486 +196608,768,pat1_q1_bothbits2,1,1,1,quantizedBoth,2,0.5804055254571522,-0.14140375764930557,400,
487 +196608,768,pat1_q1_bothbits24,1,1,1,quantizedBoth,24,0.03681752723378252,-0.009604379227128406,400,
488 +196608,768,pat1_q1_bothbits3,1,1,1,quantizedBoth,3,0.417491345627959,0.07576010763164027,400,
489 +196608,768,pat1_q1_bothbits4,1,1,1,quantizedBoth,4,0.18861208150303369,-0.014641041806362054,400,
490 +196608,768,pat1_q1_bothbits52,1,1,1,quantizedBoth,52,0.036817536792675715,-0.009604381019031617,400,
491 +196608,768,pat1_q1_bothbits6,1,1,1,quantizedBoth,6,0.0688589596830805,-0.01955314400136937,400,
492 +196608,768,pat1_q1_bothbits8,1,1,1,quantizedBoth,8,0.038584160412823816,-0.009950203072671924,400,
493 +196608,768,pat1_q1_gbits12,1,1,1,quantizedg,12,0.03681935814665003,-0.009609615260811182,400,
494 +196608,768,pat1_q1_gbits16,1,1,1,quantizedg,16,0.03681684013378436,-0.009604049423383759,400,
495 +196608,768,pat1_q1_gbits2,1,1,1,quantizedg,2,0.4505286877568466,0.01195603435521708,400,
496 +196608,768,pat1_q1_gbits24,1,1,1,quantizedg,24,0.036817533240111146,-0.009604379903575606,400,
497 +196608,768,pat1_q1_gbits3,1,1,1,quantizedg,3,0.2436939490345656,-0.004354896015661857,400,
498 +196608,768,pat1_q1_gbits4,1,1,1,quantizedg,4,0.12611549984994033,-0.00609272765507157,400,
499 +196608,768,pat1_q1_gbits52,1,1,1,quantizedg,52,0.03681753679267585,-0.009604381019031678,400,
500 +196608,768,pat1_q1_gbits6,1,1,1,quantizedg,6,0.04733505113508281,-0.01001244001464598,400,
501 +196608,768,pat1_q1_gbits8,1,1,1,quantizedg,8,0.03739295479219176,-0.009624972658909279,400,
502 +196608,768,pat1_q1_single,1,1,1,single,64,0.49758256476065016,-0.025623175971072554,400,
503 +196608,768,pat1_q1_stale,1,1,1,stale,64,0.018810584553949707,-0.0029896407484908444,400,
504 +196608,768,pat1_q2,1,1,2,exact,64,1.3369870845058987e-06,-3.47963080693151e-07,400,1.0
505 +196608,768,pat1_q2_single,1,1,2,single,64,0.08198802555410661,0.010453219117604056,400,
506 +196608,768,pat1_q2_stale,1,1,2,stale,64,0.000185541358956782,2.0604542576570066e-05,400,
507 +196608,768,pat1_q3,1,1,3,exact,64,6.435611143494894e-14,1.1076265073569326e-15,400,1.0
508 +196608,768,pat1_q3_single,1,1,3,single,64,0.014580288953048734,-0.0006076047786582812,400,
509 +196608,768,pat1_q3_stale,1,1,3,stale,64,1.950891941225607e-06,-1.1952289019649174e-07,400,
510 +786432,192,pat1-2-3-4_q0,1-2-3-4,4,0,exact,64,792.2441039159679,-77.5001709280484,400,0.997203369140625
511 +786432,192,pat1-2-3-4_q1,1-2-3-4,4,1,exact,64,56156.73462320005,558.0084085012114,400,0.997203369140625
512 +786432,192,pat1-2-3-4_q2,1-2-3-4,4,2,exact,64,15507430647.14913,-155071339.5853536,400,0.997203369140625
513 +786432,192,pat1-2-3-4_q3,1-2-3-4,4,3,exact,64,15507433225.136108,-154997841.83404675,400,0.997203369140625
514 +786432,192,pat1-2-3_q0,1-2-3,3,0,exact,64,23.384064574125784,2.1754150167069906,400,0.9999603271484375
515 +786432,192,pat1-2-3_q1,1-2-3,3,1,exact,64,2.990691118361066,-0.05501356653288217,400,0.9999603271484375
516 +786432,192,pat1-2-3_q2,1-2-3,3,2,exact,64,0.07260683273852966,-0.0009976353860264313,400,0.9999603271484375
517 +786432,192,pat1-2-3_q3,1-2-3,3,3,exact,64,4.9855226130686546e-05,-6.567674618254918e-07,400,0.9999603271484375
518 +786432,192,pat1-2-4-8_q0,1-2-4-8,4,0,exact,64,3530.3856479864617,-793.707931208403,400,0.1713970947265625
519 +786432,192,pat1-2-4-8_q1,1-2-4-8,4,1,exact,64,807975.6724300863,7162.860719205587,400,0.1713970947265625
520 +786432,192,pat1-2-4-8_q2,1-2-4-8,4,2,exact,64,42979510094520.16,-211043823992.8495,400,0.1713970947265625
521 +786432,192,pat1-2-4-8_q3,1-2-4-8,4,3,exact,64,7.621625274976593e+39,-1.3493893846785462e+38,400,0.1713970947265625
522 +786432,192,pat1-2-4_q0,1-2-4,3,0,exact,64,267.5758805247388,28.73394366495873,400,0.9972186279296875
523 +786432,192,pat1-2-4_q1,1-2-4,3,1,exact,64,1410.844784632145,-18.779860609068336,400,0.9972186279296875
524 +786432,192,pat1-2-4_q1_Hbits12,1-2-4,3,1,quantizedH,12,1411.780651197749,-18.790518255506093,400,
525 +786432,192,pat1-2-4_q1_Hbits16,1-2-4,3,1,quantizedH,16,1410.756105355328,-18.778750870731542,400,
526 +786432,192,pat1-2-4_q1_Hbits2,1-2-4,3,1,quantizedH,2,710.3984241779608,-11.549664012844977,400,
527 +786432,192,pat1-2-4_q1_Hbits24,1-2-4,3,1,quantizedH,24,1410.8448720782906,-18.779861602230838,400,
528 +786432,192,pat1-2-4_q1_Hbits3,1-2-4,3,1,quantizedH,3,1702.2815307879055,-23.878406161986863,400,
529 +786432,192,pat1-2-4_q1_Hbits4,1-2-4,3,1,quantizedH,4,1382.6095023201367,-19.155250537452755,400,
530 +786432,192,pat1-2-4_q1_Hbits52,1-2-4,3,1,quantizedH,52,1410.8447846321442,-18.77986060906832,400,
531 +786432,192,pat1-2-4_q1_Hbits6,1-2-4,3,1,quantizedH,6,1398.622884581613,-18.64639256556606,400,
532 +786432,192,pat1-2-4_q1_Hbits8,1-2-4,3,1,quantizedH,8,1400.6764696845928,-18.64315801191875,400,
533 +786432,192,pat1-2-4_q1_bothbits12,1-2-4,3,1,quantizedBoth,12,1411.7082061648644,-18.78976860665215,400,
534 +786432,192,pat1-2-4_q1_bothbits16,1-2-4,3,1,quantizedBoth,16,1410.7505739412181,-18.77869452910552,400,
535 +786432,192,pat1-2-4_q1_bothbits2,1-2-4,3,1,quantizedBoth,2,662.575666828146,-10.73323829886434,400,
536 +786432,192,pat1-2-4_q1_bothbits24,1-2-4,3,1,quantizedBoth,24,1410.844856651542,-18.779861463693095,400,
537 +786432,192,pat1-2-4_q1_bothbits3,1-2-4,3,1,quantizedBoth,3,1807.4355696419068,-25.098912008592396,400,
538 +786432,192,pat1-2-4_q1_bothbits4,1-2-4,3,1,quantizedBoth,4,1380.153723830648,-19.08508501704907,400,
539 +786432,192,pat1-2-4_q1_bothbits52,1-2-4,3,1,quantizedBoth,52,1410.8447846321442,-18.77986060906832,400,
540 +786432,192,pat1-2-4_q1_bothbits6,1-2-4,3,1,quantizedBoth,6,1395.1420168742509,-18.584425289214533,400,
541 +786432,192,pat1-2-4_q1_bothbits8,1-2-4,3,1,quantizedBoth,8,1402.9624759727337,-18.672825857578264,400,
542 +786432,192,pat1-2-4_q1_gbits12,1-2-4,3,1,quantizedg,12,1410.772377529441,-18.779111436203365,400,
543 +786432,192,pat1-2-4_q1_gbits16,1-2-4,3,1,quantizedg,16,1410.8392529078621,-18.779804263382072,400,
544 +786432,192,pat1-2-4_q1_gbits2,1-2-4,3,1,quantizedg,2,1328.0494461797489,-17.609350157616902,400,
545 +786432,192,pat1-2-4_q1_gbits24,1-2-4,3,1,quantizedg,24,1410.8447692053971,-18.7798604705306,400,
546 +786432,192,pat1-2-4_q1_gbits3,1-2-4,3,1,quantizedg,3,1499.669234668472,-19.75134508301168,400,
547 +786432,192,pat1-2-4_q1_gbits4,1-2-4,3,1,quantizedg,4,1408.276315802962,-18.709735566582168,400,
548 +786432,192,pat1-2-4_q1_gbits52,1-2-4,3,1,quantizedg,52,1410.844784632145,-18.779860609068336,400,
549 +786432,192,pat1-2-4_q1_gbits6,1-2-4,3,1,quantizedg,6,1407.3391596404244,-18.717695691150446,400,
550 +786432,192,pat1-2-4_q1_gbits8,1-2-4,3,1,quantizedg,8,1413.1447683572485,-18.80971649610857,400,
551 +786432,192,pat1-2-4_q1_single,1-2-4,3,1,single,64,1415.946272259588,-19.80466732742233,400,
552 +786432,192,pat1-2-4_q1_stale,1-2-4,3,1,stale,64,167.4628841777602,3.4775254369183735,400,
553 +786432,192,pat1-2-4_q2,1-2-4,3,2,exact,64,577389.92895574,6294.252842639041,400,0.9972186279296875
554 +786432,192,pat1-2-4_q2_single,1-2-4,3,2,single,64,437125.8640671221,4711.712617748484,400,
555 +786432,192,pat1-2-4_q2_stale,1-2-4,3,2,stale,64,112.54867238993995,1.3224975741440201,400,
556 +786432,192,pat1-2-4_q3,1-2-4,3,3,exact,64,15450161676531.732,-168435399751.17694,400,0.9972186279296875
557 +786432,192,pat1-2-4_q3_single,1-2-4,3,3,single,64,7.626787784937874e+94,-8.975008577668867e+91,400,
558 +786432,192,pat1-2-4_q3_stale,1-2-4,3,3,stale,64,64.13820840354863,0.7976160539422134,400,
559 +786432,192,pat1-2_q0,1-2,2,0,exact,64,11.227837585924028,-2.964600953128102,400,1.0
560 +786432,192,pat1-2_q1,1-2,2,1,exact,64,0.060946868890865105,-0.016066946370505066,400,1.0
561 +786432,192,pat1-2_q1_Hbits12,1-2,2,1,quantizedH,12,0.060925438454725894,-0.01605566409571279,400,
562 +786432,192,pat1-2_q1_Hbits16,1-2,2,1,quantizedH,16,0.06094295316889248,-0.016066461256375744,400,
563 +786432,192,pat1-2_q1_Hbits2,1-2,2,1,quantizedH,2,0.7142118160082552,0.2981084137838561,400,
564 +786432,192,pat1-2_q1_Hbits24,1-2,2,1,quantizedH,24,0.06094686266971935,-0.01606694700427714,400,
565 +786432,192,pat1-2_q1_Hbits3,1-2,2,1,quantizedH,3,0.6542578916827564,-0.1313001478076561,400,
566 +786432,192,pat1-2_q1_Hbits4,1-2,2,1,quantizedH,4,0.2559502729638737,0.026470257801754108,400,
567 +786432,192,pat1-2_q1_Hbits52,1-2,2,1,quantizedH,52,0.06094686889086525,-0.016066946370505188,400,
568 +786432,192,pat1-2_q1_Hbits6,1-2,2,1,quantizedH,6,0.099065327869121,-0.032049010067457286,400,
569 +786432,192,pat1-2_q1_Hbits8,1-2,2,1,quantizedH,8,0.06302349803510089,-0.01649305158101683,400,
570 +786432,192,pat1-2_q1_bothbits12,1-2,2,1,quantizedBoth,12,0.060989977225663614,-0.01606232241052833,400,
571 +786432,192,pat1-2_q1_bothbits16,1-2,2,1,quantizedBoth,16,0.06094441407087573,-0.01606609929985251,400,
572 +786432,192,pat1-2_q1_bothbits2,1-2,2,1,quantizedBoth,2,1.0926181082194653,0.2685272663021829,400,
573 +786432,192,pat1-2_q1_bothbits24,1-2,2,1,quantizedBoth,24,0.06094686218973681,-0.0160669461257948,400,
574 +786432,192,pat1-2_q1_bothbits3,1-2,2,1,quantizedBoth,3,0.7656164759037223,-0.1532100388495624,400,
575 +786432,192,pat1-2_q1_bothbits4,1-2,2,1,quantizedBoth,4,0.34531242409500496,0.02922510152360878,400,
576 +786432,192,pat1-2_q1_bothbits52,1-2,2,1,quantizedBoth,52,0.06094686889086519,-0.016066946370505313,400,
577 +786432,192,pat1-2_q1_bothbits6,1-2,2,1,quantizedBoth,6,0.11518942780186296,-0.03221678756469315,400,
578 +786432,192,pat1-2_q1_bothbits8,1-2,2,1,quantizedBoth,8,0.06460007534050105,-0.016644865346970367,400,
579 +786432,192,pat1-2_q1_gbits12,1-2,2,1,quantizedg,12,0.06101169165223578,-0.016073604883318687,400,
580 +786432,192,pat1-2_q1_gbits16,1-2,2,1,quantizedg,16,0.06094832953910508,-0.016066584413709232,400,
581 +786432,192,pat1-2_q1_gbits2,1-2,2,1,quantizedg,2,0.8546767655423951,-0.042905640619395495,400,
582 +786432,192,pat1-2_q1_gbits24,1-2,2,1,quantizedg,24,0.06094686841087952,-0.01606694549202335,400,
583 +786432,192,pat1-2_q1_gbits3,1-2,2,1,quantizedg,3,0.4609966165437193,-0.03905593282712921,400,
584 +786432,192,pat1-2_q1_gbits4,1-2,2,1,quantizedg,4,0.23364473581060324,-0.013351538466378177,400,
585 +786432,192,pat1-2_q1_gbits52,1-2,2,1,quantizedg,52,0.0609468688908653,-0.016066946370505188,400,
586 +786432,192,pat1-2_q1_gbits6,1-2,2,1,quantizedg,6,0.08323642320296915,-0.016237131299476328,400,
587 +786432,192,pat1-2_q1_gbits8,1-2,2,1,quantizedg,8,0.06259874324664053,-0.01621859140989931,400,
588 +786432,192,pat1-2_q1_single,1-2,2,1,single,64,1.9004541787397589,0.03470793886734694,400,
589 +786432,192,pat1-2_q1_stale,1-2,2,1,stale,64,0.49018368623672154,0.11896717169624337,400,
590 +786432,192,pat1-2_q2,1-2,2,2,exact,64,1.908529053473055e-06,-4.813804594344185e-07,400,1.0
591 +786432,192,pat1-2_q2_single,1-2,2,2,single,64,0.7102485035708066,-0.08620796804853098,400,
592 +786432,192,pat1-2_q2_stale,1-2,2,2,stale,64,0.01876185059586915,-0.003973002116880935,400,
593 +786432,192,pat1-2_q3,1-2,2,3,exact,64,1.3045378864426097e-13,3.692088357856443e-16,400,1.0
594 +786432,192,pat1-2_q3_single,1-2,2,3,single,64,0.3355227421493444,0.010853554410681405,400,
595 +786432,192,pat1-2_q3_stale,1-2,2,3,stale,64,0.0007410384754650917,0.00012824017468143623,400,
596 +786432,192,pat1-3_q0,1-3,2,0,exact,64,23.359644103971778,-5.534608938045584,400,0.9999603271484375
597 +786432,192,pat1-3_q1,1-3,2,1,exact,64,0.7346336355792382,-0.06465389887590647,400,0.9999603271484375
598 +786432,192,pat1-3_q2,1-3,2,2,exact,64,0.003838944289763411,-6.390965794243084e-05,400,0.9999603271484375
599 +786432,192,pat1-3_q3,1-3,2,3,exact,64,1.3853865792478252e-07,-1.865373984456167e-09,400,0.9999603271484375
600 +786432,192,pat1_q0,1,1,0,exact,64,52.26849490985705,13.359085396649698,400,1.0
601 +786432,192,pat1_q1,1,1,1,exact,64,1.350101417925109,-0.35354722584944165,400,1.0
602 +786432,192,pat1_q1_Hbits12,1,1,1,quantizedH,12,1.3500935277440065,-0.3535806507710631,400,
603 +786432,192,pat1_q1_Hbits16,1,1,1,quantizedH,16,1.3501003310194586,-0.35354619310399904,400,
604 +786432,192,pat1_q1_Hbits2,1,1,1,quantizedH,2,3.520418050904636,-1.5853585868658222,400,
605 +786432,192,pat1_q1_Hbits24,1,1,1,quantizedH,24,1.350101427488896,-0.3535472347252536,400,
606 +786432,192,pat1_q1_Hbits3,1,1,1,quantizedH,3,3.31335204900417,-1.4733426309819908,400,
607 +786432,192,pat1_q1_Hbits4,1,1,1,quantizedH,4,1.9391843575700176,-0.2604164501618895,400,
608 +786432,192,pat1_q1_Hbits52,1,1,1,quantizedH,52,1.3501014179251087,-0.3535472258494415,400,
609 +786432,192,pat1_q1_Hbits6,1,1,1,quantizedH,6,1.412495458269975,-0.2630221686438134,400,
610 +786432,192,pat1_q1_Hbits8,1,1,1,quantizedH,8,1.350563257816875,-0.356852931831705,400,
611 +786432,192,pat1_q1_bothbits12,1,1,1,quantizedBoth,12,1.350109066521084,-0.3536638093921768,400,
612 +786432,192,pat1_q1_bothbits16,1,1,1,quantizedBoth,16,1.3500985897165465,-0.353548106903985,400,
613 +786432,192,pat1_q1_bothbits2,1,1,1,quantizedBoth,2,4.781872522091928,-1.345236801810819,400,
614 +786432,192,pat1_q1_bothbits24,1,1,1,quantizedBoth,24,1.350101419410133,-0.35354721908782794,400,
615 +786432,192,pat1_q1_bothbits3,1,1,1,quantizedBoth,3,3.4797369664589923,-1.2007215873867372,400,
616 +786432,192,pat1_q1_bothbits4,1,1,1,quantizedBoth,4,2.179865940522414,-0.19557312474995617,400,
617 +786432,192,pat1_q1_bothbits52,1,1,1,quantizedBoth,52,1.3501014179251092,-0.35354722584944176,400,
618 +786432,192,pat1_q1_bothbits6,1,1,1,quantizedBoth,6,1.439894556713057,-0.26426495591610244,400,
619 +786432,192,pat1_q1_bothbits8,1,1,1,quantizedBoth,8,1.3527440761968907,-0.35621011228331206,400,
620 +786432,192,pat1_q1_gbits12,1,1,1,quantizedg,12,1.3501170520600474,-0.3536303755848401,400,
621 +786432,192,pat1_q1_gbits16,1,1,1,quantizedg,16,1.350099677286528,-0.3535491396493897,400,
622 +786432,192,pat1_q1_gbits2,1,1,1,quantizedg,2,3.662638506083238,-0.14114973336634506,400,
623 +786432,192,pat1_q1_gbits24,1,1,1,quantizedg,24,1.350101409846364,-0.3535472102120153,400,
624 +786432,192,pat1_q1_gbits3,1,1,1,quantizedg,3,2.006224560792289,-0.09931485379201599,400,
625 +786432,192,pat1_q1_gbits4,1,1,1,quantizedg,4,1.6256645986246232,-0.287943042368286,400,
626 +786432,192,pat1_q1_gbits52,1,1,1,quantizedg,52,1.3501014179251094,-0.35354722584944176,400,
627 +786432,192,pat1_q1_gbits6,1,1,1,quantizedg,6,1.375490927434224,-0.3547607305335415,400,
628 +786432,192,pat1_q1_gbits8,1,1,1,quantizedg,8,1.3523208385786278,-0.35290434969924994,400,
629 +786432,192,pat1_q1_single,1,1,1,single,64,9.113415420593412,-0.6066819226931919,400,
630 +786432,192,pat1_q1_stale,1,1,1,stale,64,0.6154136719291023,-0.10028178328086006,400,
631 +786432,192,pat1_q2,1,1,2,exact,64,0.000879551173290798,-0.00023381862617951926,400,1.0
632 +786432,192,pat1_q2_single,1,1,2,single,64,3.3415919194835424,0.3982157154697103,400,
633 +786432,192,pat1_q2_stale,1,1,2,stale,64,0.02362674423776891,0.00278074647471095,400,
634 +786432,192,pat1_q3,1,1,3,exact,64,3.7536178993428846e-10,-1.0033656242194247e-10,400,1.0
635 +786432,192,pat1_q3_single,1,1,3,single,64,1.538057892879525,-0.061989144714993616,400,
636 +786432,192,pat1_q3_stale,1,1,3,stale,64,0.0009102878847814294,-5.725027832503484e-05,400,
637 +786432,768,pat1-2-3-4_q0,1-2-3-4,4,0,exact,64,4.986018208506649,-0.13762561556908282,400,1.0
638 +786432,768,pat1-2-3-4_q1,1-2-3-4,4,1,exact,64,0.008927005909645269,-0.0018349126756300313,400,1.0
639 +786432,768,pat1-2-3-4_q2,1-2-3-4,4,2,exact,64,5.928729414583947e-08,-9.395325670941523e-09,400,1.0
640 +786432,768,pat1-2-3-4_q3,1-2-3-4,4,3,exact,64,1.267079206011133e-13,-1.969113790856769e-15,400,1.0
641 +786432,768,pat1-2-3_q0,1-2-3,3,0,exact,64,2.1540595594722562,-0.03739080593578284,400,1.0
642 +786432,768,pat1-2-3_q1,1-2-3,3,1,exact,64,0.001668959898753101,-0.0003383502868700715,400,1.0
643 +786432,768,pat1-2-3_q2,1-2-3,3,2,exact,64,2.2122358412955058e-09,-3.268737507695072e-10,400,1.0
644 +786432,768,pat1-2-3_q3,1-2-3,3,3,exact,64,1.2782661841497101e-13,-1.3537657312140286e-15,400,1.0
645 +786432,768,pat1-2-4-8_q0,1-2-4-8,4,0,exact,64,1.8639381870145941,-0.03475825718667972,400,1.0
646 +786432,768,pat1-2-4-8_q1,1-2-4-8,4,1,exact,64,0.0012395827070401909,-0.0002473233844382177,400,1.0
647 +786432,768,pat1-2-4-8_q2,1-2-4-8,4,2,exact,64,1.1847074984316457e-09,-1.7839284843956443e-10,400,1.0
648 +786432,768,pat1-2-4-8_q3,1-2-4-8,4,3,exact,64,1.275181732249539e-13,-2.2152530147138657e-15,400,1.0
649 +786432,768,pat1-2-4_q0,1-2-4,3,0,exact,64,1.5110451830356038,-0.003979202724711466,400,1.0
650 +786432,768,pat1-2-4_q1,1-2-4,3,1,exact,64,0.0008216544768970721,-0.00016467915897317158,400,1.0
651 +786432,768,pat1-2-4_q1_Hbits12,1-2-4,3,1,quantizedH,12,0.0008380846736121138,-0.00016758877896029786,400,
652 +786432,768,pat1-2-4_q1_Hbits16,1-2-4,3,1,quantizedH,16,0.0008213531689268534,-0.0001646519263919512,400,
653 +786432,768,pat1-2-4_q1_Hbits2,1-2-4,3,1,quantizedH,2,0.09338888314072155,-0.00041311064730731746,400,
654 +786432,768,pat1-2-4_q1_Hbits24,1-2-4,3,1,quantizedH,24,0.0008216542242822217,-0.0001646789080241427,400,
655 +786432,768,pat1-2-4_q1_Hbits3,1-2-4,3,1,quantizedH,3,0.08527843430502234,-0.0007137896866015434,400,
656 +786432,768,pat1-2-4_q1_Hbits4,1-2-4,3,1,quantizedH,4,0.034991269977984206,-3.433161018864331e-06,400,
657 +786432,768,pat1-2-4_q1_Hbits52,1-2-4,3,1,quantizedH,52,0.0008216544768970738,-0.00016467915897317158,400,
658 +786432,768,pat1-2-4_q1_Hbits6,1-2-4,3,1,quantizedH,6,0.010346203574861216,-0.0001057152708614529,400,
659 +786432,768,pat1-2-4_q1_Hbits8,1-2-4,3,1,quantizedH,8,0.00229765101220229,-0.00014481449597832707,400,
660 +786432,768,pat1-2-4_q1_bothbits12,1-2-4,3,1,quantizedBoth,12,0.0008503439858621292,-0.00016677900277798808,400,
661 +786432,768,pat1-2-4_q1_bothbits16,1-2-4,3,1,quantizedBoth,16,0.0008212842430070299,-0.00016444857645763592,400,
662 +786432,768,pat1-2-4_q1_bothbits2,1-2-4,3,1,quantizedBoth,2,0.1851366724544236,-0.0007678336115980275,400,
663 +786432,768,pat1-2-4_q1_bothbits24,1-2-4,3,1,quantizedBoth,24,0.0008216557477154035,-0.00016467814511771022,400,
664 +786432,768,pat1-2-4_q1_bothbits3,1-2-4,3,1,quantizedBoth,3,0.11919184466906177,-0.0011209161215371517,400,
665 +786432,768,pat1-2-4_q1_bothbits4,1-2-4,3,1,quantizedBoth,4,0.05421806570627469,-0.0010490205651338077,400,
666 +786432,768,pat1-2-4_q1_bothbits52,1-2-4,3,1,quantizedBoth,52,0.0008216544768971577,-0.00016467915897329456,400,
667 +786432,768,pat1-2-4_q1_bothbits6,1-2-4,3,1,quantizedBoth,6,0.014566527326198257,-0.00039011710968514675,400,
668 +786432,768,pat1-2-4_q1_bothbits8,1-2-4,3,1,quantizedBoth,8,0.003463912185521952,-8.395211824522951e-05,400,
669 +786432,768,pat1-2-4_q1_gbits12,1-2-4,3,1,quantizedg,12,0.0008330463313287028,-0.00016386932793812037,400,
670 +786432,768,pat1-2-4_q1_gbits16,1-2-4,3,1,quantizedg,16,0.0008215928581106568,-0.00016447580915060505,400,
671 +786432,768,pat1-2-4_q1_gbits2,1-2-4,3,1,quantizedg,2,0.1587085025081943,-0.0004219163045658744,400,
672 +786432,768,pat1-2-4_q1_gbits24,1-2-4,3,1,quantizedg,24,0.0008216560003283251,-0.0001646783960677282,400,
673 +786432,768,pat1-2-4_q1_gbits3,1-2-4,3,1,quantizedg,3,0.08148833071913175,-0.0006001162883182593,400,
674 +786432,768,pat1-2-4_q1_gbits4,1-2-4,3,1,quantizedg,4,0.04063554011621837,-0.0011990819235139095,400,
675 +786432,768,pat1-2-4_q1_gbits52,1-2-4,3,1,quantizedg,52,0.000821654476897156,-0.00016467915897329456,400,
676 +786432,768,pat1-2-4_q1_gbits6,1-2-4,3,1,quantizedg,6,0.010220674930926188,-0.00044991773025020057,400,
677 +786432,768,pat1-2-4_q1_gbits8,1-2-4,3,1,quantizedg,8,0.0026993906690647193,-0.00010384461497968454,400,
678 +786432,768,pat1-2-4_q1_single,1-2-4,3,1,single,64,0.16720048726250333,0.000979475477261655,400,
679 +786432,768,pat1-2-4_q1_stale,1-2-4,3,1,stale,64,0.01799903276285127,0.00024146515211394373,400,
680 +786432,768,pat1-2-4_q2,1-2-4,3,2,exact,64,5.366069712928225e-10,-7.853564215608368e-11,400,1.0
681 +786432,768,pat1-2-4_q2_single,1-2-4,3,2,single,64,0.02773437357746464,-0.00016665093215339873,400,
682 +786432,768,pat1-2-4_q2_stale,1-2-4,3,2,stale,64,0.00022124797714687846,-2.461218942403359e-06,400,
683 +786432,768,pat1-2-4_q3,1-2-4,3,3,exact,64,1.2737556198940502e-13,-2.0921834027853174e-15,400,1.0
684 +786432,768,pat1-2-4_q3_single,1-2-4,3,3,single,64,0.005539165216592986,2.5381686309366624e-05,400,
685 +786432,768,pat1-2-4_q3_stale,1-2-4,3,3,stale,64,2.764999226510358e-06,2.6282620546317337e-08,400,
686 +786432,768,pat1-2_q0,1-2,2,0,exact,64,1.1671323591914733,-0.14630221880072025,400,1.0
687 +786432,768,pat1-2_q1,1-2,2,1,exact,64,0.0005633629190991921,-0.00011751852903369301,400,1.0
688 +786432,768,pat1-2_q1_Hbits12,1-2,2,1,quantizedH,12,0.0005756848268925734,-0.00011564596711267867,400,
689 +786432,768,pat1-2_q1_Hbits16,1-2,2,1,quantizedH,16,0.0005634062216795882,-0.00011755625927411338,400,
690 +786432,768,pat1-2_q1_Hbits2,1-2,2,1,quantizedH,2,0.07175209845376214,0.014316005123713388,400,
691 +786432,768,pat1-2_q1_Hbits24,1-2,2,1,quantizedH,24,0.0005633635465364064,-0.00011751836096232409,400,
692 +786432,768,pat1-2_q1_Hbits3,1-2,2,1,quantizedH,3,0.06550290921516466,-0.007112992385440199,400,
693 +786432,768,pat1-2_q1_Hbits4,1-2,2,1,quantizedH,4,0.0266200645042257,0.0013708456375289666,400,
694 +786432,768,pat1-2_q1_Hbits52,1-2,2,1,quantizedH,52,0.0005633629190990796,-0.00011751852903369301,400,
695 +786432,768,pat1-2_q1_Hbits6,1-2,2,1,quantizedH,6,0.008084219542099614,-0.0008270449026094498,400,
696 +786432,768,pat1-2_q1_Hbits8,1-2,2,1,quantizedH,8,0.0017575224251456711,-1.590445672017667e-05,400,
697 +786432,768,pat1-2_q1_bothbits12,1-2,2,1,quantizedBoth,12,0.0005836730182696897,-0.00011395677179066129,400,
698 +786432,768,pat1-2_q1_bothbits16,1-2,2,1,quantizedBoth,16,0.0005634298938737238,-0.00011736980319760674,400,
699 +786432,768,pat1-2_q1_bothbits2,1-2,2,1,quantizedBoth,2,0.13555542026143944,0.015770009330439635,400,
700 +786432,768,pat1-2_q1_bothbits24,1-2,2,1,quantizedBoth,24,0.0005633643090846661,-0.00011751867548296294,400,
701 +786432,768,pat1-2_q1_bothbits3,1-2,2,1,quantizedBoth,3,0.08468958294776778,-0.006032329570818138,400,
702 +786432,768,pat1-2_q1_bothbits4,1-2,2,1,quantizedBoth,4,0.040348375995282064,0.0010014919561904532,400,
703 +786432,768,pat1-2_q1_bothbits52,1-2,2,1,quantizedBoth,52,0.000563362919099077,-0.00011751852903369301,400,
704 +786432,768,pat1-2_q1_bothbits6,1-2,2,1,quantizedBoth,6,0.011114159751628602,-0.0007991087874496736,400,
705 +786432,768,pat1-2_q1_bothbits8,1-2,2,1,quantizedBoth,8,0.0025675745247050064,-2.4767117365895914e-05,400,
706 +786432,768,pat1-2_q1_gbits12,1-2,2,1,quantizedg,12,0.0005709662668021073,-0.00011582934077476323,400,
707 +786432,768,pat1-2_q1_gbits16,1-2,2,1,quantizedg,16,0.0005633840095100463,-0.00011733207256446777,400,
708 +786432,768,pat1-2_q1_gbits2,1-2,2,1,quantizedg,2,0.11588543838560315,0.0011948028195157988,400,
709 +786432,768,pat1-2_q1_gbits24,1-2,2,1,quantizedg,24,0.0005633636815796808,-0.00011751884355470227,400,
710 +786432,768,pat1-2_q1_gbits3,1-2,2,1,quantizedg,3,0.05849617367247083,0.0010260931491219236,400,
711 +786432,768,pat1-2_q1_gbits4,1-2,2,1,quantizedg,4,0.030332537194058984,-0.0004870516939536654,400,
712 +786432,768,pat1-2_q1_gbits52,1-2,2,1,quantizedg,52,0.000563362919099101,-0.00011751852903369301,400,
713 +786432,768,pat1-2_q1_gbits6,1-2,2,1,quantizedg,6,0.007512458019991443,-8.903164506179975e-05,400,
714 +786432,768,pat1-2_q1_gbits8,1-2,2,1,quantizedg,8,0.0020030675085190193,-0.00012640319877673927,400,
715 +786432,768,pat1-2_q1_single,1-2,2,1,single,64,0.12096905239220475,0.0013745586278274004,400,
716 +786432,768,pat1-2_q1_stale,1-2,2,1,stale,64,0.013644563067335008,0.0013181536787130021,400,
717 +786432,768,pat1-2_q2,1-2,2,2,exact,64,2.414062839151719e-10,-3.825754263372038e-11,400,1.0
718 +786432,768,pat1-2_q2_single,1-2,2,2,single,64,0.019867002401137673,-0.0010219719866132828,400,
719 +786432,768,pat1-2_q2_stale,1-2,2,2,stale,64,0.00016174689913417534,-1.0572550576124022e-05,400,
720 +786432,768,pat1-2_q3,1-2,2,3,exact,64,1.2723279090550589e-13,-1.599904955071125e-15,400,1.0
721 +786432,768,pat1-2_q3_single,1-2,2,3,single,64,0.0039085030159716075,4.882284329173393e-05,400,
722 +786432,768,pat1-2_q3_stale,1-2,2,3,stale,64,1.982582960124037e-06,8.230782557114894e-08,400,
723 +786432,768,pat1-3_q0,1-3,2,0,exact,64,1.2014139000046757,-0.20075792523320643,400,1.0
724 +786432,768,pat1-3_q1,1-3,2,1,exact,64,0.0006831629562325114,-0.00014098577140672305,400,1.0
725 +786432,768,pat1-3_q2,1-3,2,2,exact,64,3.6129078842078333e-10,-5.615469480920563e-11,400,1.0
726 +786432,768,pat1-3_q3,1-3,2,3,exact,64,1.2742311680233283e-13,-1.5999049550711248e-15,400,1.0
727 +786432,768,pat1_q0,1,1,0,exact,64,12.2961925767473,3.1516521836036056,400,1.0
728 +786432,768,pat1_q1,1,1,1,exact,64,0.07338344813428402,-0.019258219032004004,400,1.0
729 +786432,768,pat1_q1_Hbits12,1,1,1,quantizedH,12,0.07338281064373217,-0.019261207101063663,400,
730 +786432,768,pat1_q1_Hbits16,1,1,1,quantizedH,16,0.07338398544075639,-0.01925827419495453,400,
731 +786432,768,pat1_q1_Hbits2,1,1,1,quantizedH,2,0.7590665727637258,-0.32188435320924214,400,
732 +786432,768,pat1_q1_Hbits24,1,1,1,quantizedH,24,0.07338345292759642,-0.019258217921186427,400,
733 +786432,768,pat1_q1_Hbits3,1,1,1,quantizedH,3,0.681815873260594,0.14826931098142881,400,
734 +786432,768,pat1_q1_Hbits4,1,1,1,quantizedH,4,0.3064005947871396,-0.040595245542801944,400,
735 +786432,768,pat1_q1_Hbits52,1,1,1,quantizedH,52,0.07338344813428425,-0.019258219032003757,400,
736 +786432,768,pat1_q1_Hbits6,1,1,1,quantizedH,6,0.14215661917705208,-0.042394806471225434,400,
737 +786432,768,pat1_q1_Hbits8,1,1,1,quantizedH,8,0.07708746512801695,-0.02146146358562574,400,
738 +786432,768,pat1_q1_bothbits12,1,1,1,quantizedBoth,12,0.07339755738041875,-0.01927578412178828,400,
739 +786432,768,pat1_q1_bothbits16,1,1,1,quantizedBoth,16,0.07338248433901955,-0.01925771802574986,400,
740 +786432,768,pat1_q1_bothbits2,1,1,1,quantizedBoth,2,1.1333273076929224,-0.2897438845946383,400,
741 +786432,768,pat1_q1_bothbits24,1,1,1,quantizedBoth,24,0.07338346683107207,-0.01925822123666614,400,
742 +786432,768,pat1_q1_bothbits3,1,1,1,quantizedBoth,3,0.7909446830378264,0.17374648925579592,400,
743 +786432,768,pat1_q1_bothbits4,1,1,1,quantizedBoth,4,0.3822148224404738,-0.03411987345182587,400,
744 +786432,768,pat1_q1_bothbits52,1,1,1,quantizedBoth,52,0.07338344813428407,-0.019258219032003882,400,
745 +786432,768,pat1_q1_bothbits6,1,1,1,quantizedBoth,6,0.15352997516199599,-0.04159178990563265,400,
746 +786432,768,pat1_q1_bothbits8,1,1,1,quantizedBoth,8,0.07907700667717775,-0.021936718098019437,400,
747 +786432,768,pat1_q1_gbits12,1,1,1,quantizedg,12,0.0733982931920051,-0.01927279714979576,400,
748 +786432,768,pat1_q1_gbits16,1,1,1,quantizedg,16,0.07338194943515276,-0.01925766287040959,400,
749 +786432,768,pat1_q1_gbits2,1,1,1,quantizedg,2,0.8606775568937779,0.009104400694126037,400,
750 +786432,768,pat1_q1_gbits24,1,1,1,quantizedg,24,0.07338346203775303,-0.019258222347480397,400,
751 +786432,768,pat1_q1_gbits3,1,1,1,quantizedg,3,0.44556635400948835,0.007824904372389281,400,
752 +786432,768,pat1_q1_gbits4,1,1,1,quantizedg,4,0.2405415786045958,-0.012821941460921464,400,
753 +786432,768,pat1_q1_gbits52,1,1,1,quantizedg,52,0.07338344813428388,-0.019258219032004004,400,
754 +786432,768,pat1_q1_gbits6,1,1,1,quantizedg,6,0.09521209713213563,-0.018461005658203956,400,
755 +786432,768,pat1_q1_gbits8,1,1,1,quantizedg,8,0.07541182641604685,-0.019732817194248443,400,
756 +786432,768,pat1_q1_single,1,1,1,single,64,1.0133393975473626,-0.04230667122851182,400,
757 +786432,768,pat1_q1_stale,1,1,1,stale,64,0.036105097762282046,-0.00601262744931846,400,
758 +786432,768,pat1_q2,1,1,2,exact,64,2.609643726065326e-06,-6.929186294074258e-07,400,1.0
759 +786432,768,pat1_q2_single,1,1,2,single,64,0.16667964738499363,0.022077884504407917,400,
760 +786432,768,pat1_q2_stale,1,1,2,stale,64,0.00033201384394034267,3.972457440233659e-05,400,
761 +786432,768,pat1_q3,1,1,3,exact,64,1.2694676703476543e-13,-2.2152530147138653e-15,400,1.0
762 +786432,768,pat1_q3_single,1,1,3,single,64,0.03018338868073322,-0.001257402858222569,400,
763 +786432,768,pat1_q3_stale,1,1,3,stale,64,3.141353299175483e-06,-2.0216029286550581e-07,400,
modified results/processed/summary.csv +330 −0
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modified results/raw/ablation_logistic_N196608_m768.csv +10160 −0
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added results/raw/ablation_logistic_N786432_m192.csv +7801 −0
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