premise string | hypothesis string | label int64 |
|---|---|---|
| Command | ANumber | Comments |
| --- | --- | --- |
| \alignauthor | 100 | Authoralignment | | | \numberofauthors | 200 | Authorenumeration |
| --- | --- | --- |
| \table | 300 | Fortables |
| \table* | 400 | Forwidertables | | 1 |
| Command | ANumber | Comments |
| --- | --- | --- |
| \alignauthor | 100 | Authoralignment | | | Command | ANumber | Comments |
| --- | --- | --- |
| \alignauthor | 100 | Authoralignment |
| \numberofauthors | 200 | Authorenumeration |
| \table | 300 | Fortables |
| \table* | 400 | Forwidertables | | 0 |
| Command | ANumber | Comments |
| --- | --- | --- |
| \alignauthor | 100 | Authoralignment | | | \numberofauthors | 200 | Authorenumeration |
| --- | --- | --- |
| \table | 300 | Fortables |
| \table* | 400 | Forwidertables | | 1 |
| Command | ANumber | Comments |
| --- | --- | --- |
| \alignauthor | 100 | Authoralignment | | | \table | 300 | Fortables |
| --- | --- | --- |
| \table* | 400 | Forwidertables | | 0 |
| Network | Vertices | Edges | τ | IMQueries | kmax |
| --- | --- | --- | --- | --- | --- |
| wiki-Vote | 7K | 104K | 10 | 212 | 50 |
| Flixster | 99K | 978K | 10 | 223 | 100 |
| soc-Pokec | 1.6M | 31M | 10 | 636 | 200 | | | flickr-growth | 2.3M | 33M | 10 | 779 | 200 |
| --- | --- | --- | --- | --- | --- |
| Twitter | 41.6M | 1.5G | 10 | 3011 | 500 | | 1 |
| Network | Vertices | Edges | τ | IMQueries | kmax |
| --- | --- | --- | --- | --- | --- |
| wiki-Vote | 7K | 104K | 10 | 212 | 50 |
| Flixster | 99K | 978K | 10 | 223 | 100 |
| soc-Pokec | 1.6M | 31M | 10 | 636 | 200 | | | Dataset | #Updates | LT | IC | | |
| --- | --- | --- | --- | --- | --- |
| Total | ST | Total | ST | | |
| wiki-Vote | 2.1×10 | 11.3 | 2.3 | 29.3 | 8.2 |
| Flixster | 2.2×10 | 266 | 28 | 522 | 85 |
| soc-Pokec | 6.4×10 | 3165 | 311 | 4461 | 735 |
| flickr-growth | 7.8×10 | 1908 | 201 | 3223 | 935 |
| Twitter | 3.0×10 | 15369 | 375 | 19803 | 4770 | | 0 |
| Network | Vertices | Edges | τ | IMQueries | kmax |
| --- | --- | --- | --- | --- | --- |
| wiki-Vote | 7K | 104K | 10 | 212 | 50 |
| Flixster | 99K | 978K | 10 | 223 | 100 |
| soc-Pokec | 1.6M | 31M | 10 | 636 | 200 | | | flickr-growth | 2.3M | 33M | 10 | 779 | 200 |
| --- | --- | --- | --- | --- | --- |
| Twitter | 41.6M | 1.5G | 10 | 3011 | 500 | | 1 |
| Network | Vertices | Edges | τ | IMQueries | kmax |
| --- | --- | --- | --- | --- | --- |
| wiki-Vote | 7K | 104K | 10 | 212 | 50 |
| Flixster | 99K | 978K | 10 | 223 | 100 |
| soc-Pokec | 1.6M | 31M | 10 | 636 | 200 | | | wiki-Vote | 2.1×10 | 11.3 | 2.3 | 29.3 | 8.2 |
| --- | --- | --- | --- | --- | --- |
| Flixster | 2.2×10 | 266 | 28 | 522 | 85 |
| soc-Pokec | 6.4×10 | 3165 | 311 | 4461 | 735 |
| flickr-growth | 7.8×10 | 1908 | 201 | 3223 | 935 |
| Twitter | 3.0×10 | 15369 | 375 | 19803 | 4770 | | 0 |
| Techniques | Movielens100K | OurDataset | Movielens1M | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Errors | MAE | RMSE | MAE | RMSE | MAE | RMSE |
| User-Usersimilarity | 0.6980 | 1.026 | 0.5307 | 1.03 | 0.607 | 0.8810 |
| Item-Itemsimilarity | 0.744 | 1.061 | 0.648 | 1.049 | 0.671 | 0.9196 |
| MatrixFactorization | 0.828 | 1.128 | 0.471 | 0.971 | 0.6863 | 0.8790 | | | ProbabilisticMatrixFactorization | 0.7564 | 0.9639 | 0.481 | 0.9372 | 0.7241 | 0.9127 |
| --- | --- | --- | --- | --- | --- | --- |
| BlindCompressedSensing | 0.7356 | 0.9409 | 0.463 | 0.9612 | 0.6917 | 0.8789 |
| MatrixCompletion | 0.8324 | 1.102 | 0.4827 | 0.9264 | 0.7196 | 0.9102 | | 1 |
| Techniques | Movielens100K | OurDataset | Movielens1M | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Errors | MAE | RMSE | MAE | RMSE | MAE | RMSE |
| User-Usersimilarity | 0.6980 | 1.026 | 0.5307 | 1.03 | 0.607 | 0.8810 |
| Item-Itemsimilarity | 0.744 | 1.061 | 0.648 | 1.049 | 0.671 | 0.9196 |
| MatrixFactorization | 0.828 | 1.128 | 0.471 | 0.971 | 0.6863 | 0.8790 | | | | Algorithm | H.264 | JP2K | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| LCC | SROCC | RMSE | LCC | SROCC | RMSE | | |
| VQUEMODES | SBIQE | 0.9262 | 0.8956 | 0.3286 | 0.9706 | 0.9473 | 0.2415 |
| BRISQUE | 0.9517 | 0.9323 | 0.2319 | 0.9809 | 0.9577 | 0.1097 | |
| NIQE | 0.9594 | 0.9439 | 0.1791 | 0.9859 | 0.9666 | 0.0912 | | | 0 |
| Techniques | Movielens100K | OurDataset | Movielens1M | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Errors | MAE | RMSE | MAE | RMSE | MAE | RMSE |
| User-Usersimilarity | 0.6980 | 1.026 | 0.5307 | 1.03 | 0.607 | 0.8810 | | | Item-Itemsimilarity | 0.744 | 1.061 | 0.648 | 1.049 | 0.671 | 0.9196 |
| --- | --- | --- | --- | --- | --- | --- |
| MatrixFactorization | 0.828 | 1.128 | 0.471 | 0.971 | 0.6863 | 0.8790 |
| ProbabilisticMatrixFactorization | 0.7564 | 0.9639 | 0.481 | 0.9372 | 0.7241 | 0.9127 |
| BlindCompressedSensing | 0.7356 | 0.9409 | 0.463 | 0.9612 | 0.6917 | 0.8789 |
| MatrixCompletion | 0.8324 | 1.102 | 0.4827 | 0.9264 | 0.7196 | 0.9102 | | 1 |
| Techniques | Movielens100K | OurDataset | Movielens1M | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Errors | MAE | RMSE | MAE | RMSE | MAE | RMSE |
| User-Usersimilarity | 0.6980 | 1.026 | 0.5307 | 1.03 | 0.607 | 0.8810 | | | VQUEMODES | SBIQE | 0.9262 | 0.8956 | 0.3286 | 0.9706 | 0.9473 | 0.2415 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| BRISQUE | 0.9517 | 0.9323 | 0.2319 | 0.9809 | 0.9577 | 0.1097 | |
| NIQE | 0.9594 | 0.9439 | 0.1791 | 0.9859 | 0.9666 | 0.0912 | | | 0 |
| Field | Length(bits) |
| --- | --- |
| Messagetype | 6 |
| Priority | 3 |
| Checksumflag | 1 |
| Open-loopsafestate | 8 | | | Sourceentitynumber | 5 |
| --- | --- |
| Sourceunitnumber | 5 |
| Sourceautomatonnumber | 5 |
| Destinationentitynumber | 5 |
| Destinationunitnumber | 5 |
| Destinationautomatonnumber | 5 |
| Application-specificdatalength | 16 | | 1 |
| Field | Length(bits) |
| --- | --- |
| Messagetype | 6 |
| Priority | 3 |
| Checksumflag | 1 |
| Open-loopsafestate | 8 | | | Parameter | Valuerange | Bits |
| --- | --- | --- |
| Null-moveuse | 0–1 | 1 |
| Null-movereduction | 0–7 | 3 |
| Null-moveuseadaptivity | 0–1 | 1 |
| Null-moveadaptivitydepth | 0–7 | 3 |
| Futilitydepth | 0–3 | 2 |
| Futilitythresholddepth-1 | 0–1023 | 10 |
| Futilitythresholddepth-2 | 0–1023 | 10 |
| Futilitythresholddepth-3 | 0–1023 | 10 |
| Multi-cutuse | 0–1 | 1 |
| Multi-cutreduction | 0–7 | 3 |
| Multi-cutdepth | 0–7 | 3 |
| Multi-cutmovenum | 0–31 | 5 |
| Multi-cutcutnum | 0–7 | 3 |
| Checkextension | 0–4 | 3 |
| One-replyextension | 0–4 | 3 |
| Recaptureextension | 0–4 | 3 |
| Passedpawnextension | 0–4 | 3 |
| Matethreatextension | 0–4 | 3 |
| Totalchromosomelength | | 70 | | 0 |
| Field | Length(bits) |
| --- | --- |
| Messagetype | 6 |
| Priority | 3 |
| Checksumflag | 1 | | | Open-loopsafestate | 8 |
| --- | --- |
| Sourceentitynumber | 5 |
| Sourceunitnumber | 5 |
| Sourceautomatonnumber | 5 |
| Destinationentitynumber | 5 |
| Destinationunitnumber | 5 |
| Destinationautomatonnumber | 5 |
| Application-specificdatalength | 16 | | 1 |
| Field | Length(bits) |
| --- | --- |
| Messagetype | 6 |
| Priority | 3 |
| Checksumflag | 1 | | | Passedpawnextension | 0–4 | 3 |
| --- | --- | --- |
| Matethreatextension | 0–4 | 3 |
| Totalchromosomelength | | 70 | | 0 |
| Paper | Authors | Community | NumberofCitations |
| --- | --- | --- | --- |
| p1 | u,u12 | c1 | 0 | | | p2 | u,u14 | c1 | 0 |
| --- | --- | --- | --- |
| p3 | u,u23 | c1 | 3 |
| p4 | u,u34 | c1 | 3 |
| p5 | u,u12 | c1 | 50 |
| p6 | u,u,u456 | c2 | 9 |
| p7 | u,u67 | c2 | 10 |
| p8 | u,u47 | c2 | 11 | | 1 |
| Paper | Authors | Community | NumberofCitations |
| --- | --- | --- | --- |
| p1 | u,u12 | c1 | 0 | | | language | finalstates | language | finalstates |
| --- | --- | --- | --- |
| L | 3,7,8 | pcpc(L) | 1,5,6,7 |
| c(L) | 1,2,4,5,6 | cpcp(L) | 2,3,6,7 |
| p(L) | 1,2,3,5,6,7,8 | cpcpc(L) | 2,3,4,8 |
| pc(L) | 1,2,3,4,5,6,8 | pcpcp(L) | 1,2,3,5,6,7 |
| cp(L) | 4 | pcpcpc(L) | 1,2,3,4,5,8 |
| cpc(L) | 7 | cpcpcp(L) | 4,8 |
| pcp(L) | 1,4,5,8 | cpcpcpc(L) | 6,7 | | 0 |
| Paper | Authors | Community | NumberofCitations |
| --- | --- | --- | --- |
| p1 | u,u12 | c1 | 0 |
| p2 | u,u14 | c1 | 0 |
| p3 | u,u23 | c1 | 3 |
| p4 | u,u34 | c1 | 3 | | | p5 | u,u12 | c1 | 50 |
| --- | --- | --- | --- |
| p6 | u,u,u456 | c2 | 9 |
| p7 | u,u67 | c2 | 10 |
| p8 | u,u47 | c2 | 11 | | 1 |
| Paper | Authors | Community | NumberofCitations |
| --- | --- | --- | --- |
| p1 | u,u12 | c1 | 0 |
| p2 | u,u14 | c1 | 0 |
| p3 | u,u23 | c1 | 3 |
| p4 | u,u34 | c1 | 3 | | | cp(L) | 4 | pcpcpc(L) | 1,2,3,4,5,8 |
| --- | --- | --- | --- |
| cpc(L) | 7 | cpcpcp(L) | 4,8 |
| pcp(L) | 1,4,5,8 | cpcpcpc(L) | 6,7 | | 0 |
| Hyperparameter | NMT | SPF | Ours |
| --- | --- | --- | --- |
| BatchSize | 128 | 100 | 128 |
| HiddenLayerSize | 512 | 600 | 512 |
| EncoderLayer | 2 | 2 | 2 |
| DecoderLayer | 2 | 1 | 2 |
| Optimizer | ADAM | ADAM | ADAM | | | LearningRate | 0.001 | 0.001 | 0.001 |
| --- | --- | --- | --- |
| BidirectionalEncoder | Used | Used | Used |
| EncoderDropoutRate | 0.2 | 0.4 | 0.2 |
| DecoderDropoutRate | 0.2 | 0.5 | 0.2 |
| BeamSearchSize | - | 5 | - | | 1 |
| Hyperparameter | NMT | SPF | Ours |
| --- | --- | --- | --- |
| BatchSize | 128 | 100 | 128 |
| HiddenLayerSize | 512 | 600 | 512 |
| EncoderLayer | 2 | 2 | 2 |
| DecoderLayer | 2 | 1 | 2 |
| Optimizer | ADAM | ADAM | ADAM | | | ASRsystem | |
| --- | --- |
| Inputunits | 23 |
| Hiddenunits | 512 |
| Outputunits | 27293 |
| LSTMlayerdepth | 2 |
| MTsystem | |
| Sourcevocabulary | 27293 |
| Targetvocabulary | 33155 |
| Embedsize | 128 |
| Inputunits | 128 |
| Hiddenunits | 512 |
| Outputunits | 33155 |
| LSTMlayerdepth | 2 |
| Optimization | |
| Initiallearningrate | 0.001000 |
| Learningdescendrate | 1.800000 |
| Optimizingmethod | Adam | | 0 |
| Hyperparameter | NMT | SPF | Ours |
| --- | --- | --- | --- |
| BatchSize | 128 | 100 | 128 |
| HiddenLayerSize | 512 | 600 | 512 |
| EncoderLayer | 2 | 2 | 2 |
| DecoderLayer | 2 | 1 | 2 | | | Optimizer | ADAM | ADAM | ADAM |
| --- | --- | --- | --- |
| LearningRate | 0.001 | 0.001 | 0.001 |
| BidirectionalEncoder | Used | Used | Used |
| EncoderDropoutRate | 0.2 | 0.4 | 0.2 |
| DecoderDropoutRate | 0.2 | 0.5 | 0.2 |
| BeamSearchSize | - | 5 | - | | 1 |
| Hyperparameter | NMT | SPF | Ours |
| --- | --- | --- | --- |
| BatchSize | 128 | 100 | 128 |
| HiddenLayerSize | 512 | 600 | 512 |
| EncoderLayer | 2 | 2 | 2 |
| DecoderLayer | 2 | 1 | 2 | | | MTsystem | |
| --- | --- |
| Sourcevocabulary | 27293 |
| Targetvocabulary | 33155 |
| Embedsize | 128 |
| Inputunits | 128 |
| Hiddenunits | 512 |
| Outputunits | 33155 |
| LSTMlayerdepth | 2 |
| Optimization | |
| Initiallearningrate | 0.001000 |
| Learningdescendrate | 1.800000 |
| Optimizingmethod | Adam | | 0 |
| Numberofwriters | 16 |
| --- | --- |
| Numberofpages | 176 | | | Numberoflines | 1717 |
| --- | --- |
| NumberofWords | 12853 |
| OOVwords | 1066 | | 1 |
| Numberofwriters | 16 |
| --- | --- |
| Numberofpages | 176 | | | | Count |
| --- | --- |
| Writers | 1001(M:561,F:440) |
| Pages | 4512 |
| Avg.Pages/Writer | 4 |
| Lines | 31124 |
| SegmentedWords | 152680 |
| SegmentedCharacters | 106433 |
| PAWs | 325508 | | 0 |
| Numberofwriters | 16 |
| --- | --- |
| Numberofpages | 176 | | | Numberoflines | 1717 |
| --- | --- |
| NumberofWords | 12853 |
| OOVwords | 1066 | | 1 |
| Numberofwriters | 16 |
| --- | --- |
| Numberofpages | 176 | | | Lines | 31124 |
| --- | --- |
| SegmentedWords | 152680 |
| SegmentedCharacters | 106433 |
| PAWs | 325508 | | 0 |
| Device-directedspeech |
| --- |
| what’stheweatherlikeinlasvegas |
| playpopularmusic |
| markthefirstitemdone | | | whatisscratchprogramming |
| --- |
| Nondevice-directedspeech |
| oriftheywantshecanjustqueueforbetter |
| wellthat’showwehadallthetraining |
| talktoalexabutwe’retalkingtodannyrightnow |
| livetogetherlikemonthsagoandtheymaystillbe<br>boring | | 1 |
| Device-directedspeech |
| --- |
| what’stheweatherlikeinlasvegas |
| playpopularmusic |
| markthefirstitemdone | | | Focus | Description |
| --- | --- |
| F0 | baselinebroadcastspeech(clean,planned) |
| F1 | spontaneousbroadcastspeech(clean) |
| F2 | lowfidelityspeech(typicallynarrowband) |
| F3 | speechinthepresenceofbackgroundmusic |
| F4 | speechunderdegradedacousticalconditions |
| F5 | non-nativespeakers(clean,planned) |
| FX | allotherspeech(e.g.spontanousnon-native) | | 0 |
| Device-directedspeech |
| --- |
| what’stheweatherlikeinlasvegas |
| playpopularmusic |
| markthefirstitemdone | | | whatisscratchprogramming |
| --- |
| Nondevice-directedspeech |
| oriftheywantshecanjustqueueforbetter |
| wellthat’showwehadallthetraining |
| talktoalexabutwe’retalkingtodannyrightnow |
| livetogetherlikemonthsagoandtheymaystillbe<br>boring | | 1 |
| Device-directedspeech |
| --- |
| what’stheweatherlikeinlasvegas |
| playpopularmusic |
| markthefirstitemdone | | | F2 | lowfidelityspeech(typicallynarrowband) |
| --- | --- |
| F3 | speechinthepresenceofbackgroundmusic |
| F4 | speechunderdegradedacousticalconditions |
| F5 | non-nativespeakers(clean,planned) |
| FX | allotherspeech(e.g.spontanousnon-native) | | 0 |
| Method | mean(inmm) | std(inmm) |
| --- | --- | --- |
| Orderudetal. | 3.6 | 1.8 |
| Luetal. | 3.6 | 3.1 | | | Leungetal. | 4.5 | 2.9 |
| --- | --- | --- |
| Karavidesetal. | 5.0 | 2.5 |
| VanStralenetal. | 8.4 | 5.7 |
| Proposed | 7.2 | 3.7 | | 1 |
| Method | mean(inmm) | std(inmm) |
| --- | --- | --- |
| Orderudetal. | 3.6 | 1.8 |
| Luetal. | 3.6 | 3.1 | | | Size,QP | Proposedmethod | Methodin |
| --- | --- | --- |
| 64×64,22 | 0.79 | 0.78 |
| 128×128,22 | 0.91 | 0.90 |
| 64×64,32 | 0.96 | 0.80 |
| 128×128,32 | 0.99 | 0.89 |
| 64×64,42 | 0.61 | 0.75 |
| 128×128,42 | 0.84 | 0.89 |
| Average | 0.85 | 0.84 | | 0 |
| Method | mean(inmm) | std(inmm) |
| --- | --- | --- |
| Orderudetal. | 3.6 | 1.8 | | | Luetal. | 3.6 | 3.1 |
| --- | --- | --- |
| Leungetal. | 4.5 | 2.9 |
| Karavidesetal. | 5.0 | 2.5 |
| VanStralenetal. | 8.4 | 5.7 |
| Proposed | 7.2 | 3.7 | | 1 |
| Method | mean(inmm) | std(inmm) |
| --- | --- | --- |
| Orderudetal. | 3.6 | 1.8 | | | 128×128,22 | 0.91 | 0.90 |
| --- | --- | --- |
| 64×64,32 | 0.96 | 0.80 |
| 128×128,32 | 0.99 | 0.89 |
| 64×64,42 | 0.61 | 0.75 |
| 128×128,42 | 0.84 | 0.89 |
| Average | 0.85 | 0.84 | | 0 |
| OutliersReported | CorrectlyReported | OutliersMissed | ExecutionTime(s) |
| --- | --- | --- | --- |
| 22160 | 406 | 649 | 23.33s |
| 13260 | 523 | 532 | 1813.63s |
| 15432 | 365 | 690 | 1483.54s |
| 14328 | 460 | 595 | 2125.43s |
| 16578 | 396 | 659 | 1594.54s |
| 16579 | 496 | 559 | 1674.43s | | | 18054 | 365 | 690 | 1918.34s |
| --- | --- | --- | --- |
| 21095 | 469 | 586 | 1428.32s |
| 20658 | 584 | 471 | 2043.43s |
| 19574 | 368 | 687 | 1485.85s |
| 25704 | 565 | 490 | 1684.47s |
| 29316 | 354 | 701 | 3510.26s | | 1 |
| OutliersReported | CorrectlyReported | OutliersMissed | ExecutionTime(s) |
| --- | --- | --- | --- |
| 22160 | 406 | 649 | 23.33s |
| 13260 | 523 | 532 | 1813.63s |
| 15432 | 365 | 690 | 1483.54s |
| 14328 | 460 | 595 | 2125.43s |
| 16578 | 396 | 659 | 1594.54s |
| 16579 | 496 | 559 | 1674.43s | | | OutliersReported | CorrectlyReported | OutliersMissed | ExecutionTime(s) |
| --- | --- | --- | --- |
| 7216 | 340 | 1168 | 1.26s |
| 4476 | 519 | 989 | 72.31s |
| 5428 | 447 | 1061 | 63.27s |
| 5558 | 329 | 1508 | 89.96s |
| 5121 | 253 | 1179 | 59.97s |
| 7501 | 470 | 1038 | 60.39s |
| 10110 | 162 | 1346 | 72.69s |
| 9515 | 404 | 1104 | 55.89s |
| 8746 | 284 | 1224 | 81.74s |
| 9133 | 301 | 1207 | 60.51s |
| 10328 | 420 | 1088 | 72.13s |
| 8931 | 319 | 1189 | 291.10s | | 0 |
| OutliersReported | CorrectlyReported | OutliersMissed | ExecutionTime(s) |
| --- | --- | --- | --- |
| 22160 | 406 | 649 | 23.33s |
| 13260 | 523 | 532 | 1813.63s |
| 15432 | 365 | 690 | 1483.54s |
| 14328 | 460 | 595 | 2125.43s |
| 16578 | 396 | 659 | 1594.54s |
| 16579 | 496 | 559 | 1674.43s |
| 18054 | 365 | 690 | 1918.34s | | | 21095 | 469 | 586 | 1428.32s |
| --- | --- | --- | --- |
| 20658 | 584 | 471 | 2043.43s |
| 19574 | 368 | 687 | 1485.85s |
| 25704 | 565 | 490 | 1684.47s |
| 29316 | 354 | 701 | 3510.26s | | 1 |
| OutliersReported | CorrectlyReported | OutliersMissed | ExecutionTime(s) |
| --- | --- | --- | --- |
| 22160 | 406 | 649 | 23.33s |
| 13260 | 523 | 532 | 1813.63s |
| 15432 | 365 | 690 | 1483.54s |
| 14328 | 460 | 595 | 2125.43s |
| 16578 | 396 | 659 | 1594.54s |
| 16579 | 496 | 559 | 1674.43s |
| 18054 | 365 | 690 | 1918.34s | | | 5428 | 447 | 1061 | 63.27s |
| --- | --- | --- | --- |
| 5558 | 329 | 1508 | 89.96s |
| 5121 | 253 | 1179 | 59.97s |
| 7501 | 470 | 1038 | 60.39s |
| 10110 | 162 | 1346 | 72.69s |
| 9515 | 404 | 1104 | 55.89s |
| 8746 | 284 | 1224 | 81.74s |
| 9133 | 301 | 1207 | 60.51s |
| 10328 | 420 | 1088 | 72.13s |
| 8931 | 319 | 1189 | 291.10s | | 0 |
| Image | ind(P)1 | ind(P)2 | ind(P)3 | ind(P)4 |
| --- | --- | --- | --- | --- |
| Tiger | 0.142 | 0.217 | 0.272 | 0.317 |
| Lake | 0.004 | 0.085 | 0.129 | 0.173 |
| Elephant | 0.071 | 0.154 | 0.204 | 0.248 |
| Airplane | 0.205 | 0.306 | 0.363 | 0.408 |
| Ostrich | 0.154 | 0.231 | 0.279 | 0.319 |
| Face | 0.006 | 0.061 | 0.102 | 0.135 |
| Eagle | 0.213 | 0.318 | 0.376 | 0.417 |
| Wolf | 0.014 | 0.103 | 0.181 | 0.215 |
| Wall | 0.201 | 0.304 | 0.362 | 0.399 |
| Horse | 0.078 | 0.169 | 0.214 | 0.252 | | | Pantheon | 0.049 | 0.101 | 0.151 | 0.179 |
| --- | --- | --- | --- | --- |
| Church | 0.009 | 0.081 | 0.126 | 0.167 | | 1 |
| Image | ind(P)1 | ind(P)2 | ind(P)3 | ind(P)4 |
| --- | --- | --- | --- | --- |
| Tiger | 0.142 | 0.217 | 0.272 | 0.317 |
| Lake | 0.004 | 0.085 | 0.129 | 0.173 |
| Elephant | 0.071 | 0.154 | 0.204 | 0.248 |
| Airplane | 0.205 | 0.306 | 0.363 | 0.408 |
| Ostrich | 0.154 | 0.231 | 0.279 | 0.319 |
| Face | 0.006 | 0.061 | 0.102 | 0.135 |
| Eagle | 0.213 | 0.318 | 0.376 | 0.417 |
| Wolf | 0.014 | 0.103 | 0.181 | 0.215 |
| Wall | 0.201 | 0.304 | 0.362 | 0.399 |
| Horse | 0.078 | 0.169 | 0.214 | 0.252 | | | Locations | W | C | TL | TR | BL | BR |
| --- | --- | --- | --- | --- | --- | --- |
| aeroplane | 65.6 | 30.2 | 0 | 0 | 2.1 | 2.1 |
| bird | 78.1 | 21.9 | 0 | 0 | 0 | 0 |
| boat | 45.8 | 21.6 | 0 | 0 | 12.3 | 20.2 |
| car | 54.1 | 40.2 | 2.0 | 0 | 3.7 | 0 |
| cat | 76.4 | 17.3 | 5.0 | 0 | 1.3 | 0 |
| cow | 70.8 | 22.2 | 1.8 | 2.4 | 0 | 2.8 |
| dog | 92.8 | 6.2 | 1.0 | 0 | 0 | 0 |
| horse | 75.9 | 14.7 | 0 | 0 | 8.3 | 1.2 |
| motorbike | 65.3 | 33.7 | 0 | 0 | 0 | 1.0 |
| train | 56.5 | 20.0 | 0 | 2.4 | 12.8 | 8.4 | | 0 |
| Image | ind(P)1 | ind(P)2 | ind(P)3 | ind(P)4 |
| --- | --- | --- | --- | --- |
| Tiger | 0.142 | 0.217 | 0.272 | 0.317 |
| Lake | 0.004 | 0.085 | 0.129 | 0.173 |
| Elephant | 0.071 | 0.154 | 0.204 | 0.248 |
| Airplane | 0.205 | 0.306 | 0.363 | 0.408 | | | Ostrich | 0.154 | 0.231 | 0.279 | 0.319 |
| --- | --- | --- | --- | --- |
| Face | 0.006 | 0.061 | 0.102 | 0.135 |
| Eagle | 0.213 | 0.318 | 0.376 | 0.417 |
| Wolf | 0.014 | 0.103 | 0.181 | 0.215 |
| Wall | 0.201 | 0.304 | 0.362 | 0.399 |
| Horse | 0.078 | 0.169 | 0.214 | 0.252 |
| Pantheon | 0.049 | 0.101 | 0.151 | 0.179 |
| Church | 0.009 | 0.081 | 0.126 | 0.167 | | 1 |
| Image | ind(P)1 | ind(P)2 | ind(P)3 | ind(P)4 |
| --- | --- | --- | --- | --- |
| Tiger | 0.142 | 0.217 | 0.272 | 0.317 |
| Lake | 0.004 | 0.085 | 0.129 | 0.173 |
| Elephant | 0.071 | 0.154 | 0.204 | 0.248 |
| Airplane | 0.205 | 0.306 | 0.363 | 0.408 | | | boat | 45.8 | 21.6 | 0 | 0 | 12.3 | 20.2 |
| --- | --- | --- | --- | --- | --- | --- |
| car | 54.1 | 40.2 | 2.0 | 0 | 3.7 | 0 |
| cat | 76.4 | 17.3 | 5.0 | 0 | 1.3 | 0 |
| cow | 70.8 | 22.2 | 1.8 | 2.4 | 0 | 2.8 |
| dog | 92.8 | 6.2 | 1.0 | 0 | 0 | 0 |
| horse | 75.9 | 14.7 | 0 | 0 | 8.3 | 1.2 |
| motorbike | 65.3 | 33.7 | 0 | 0 | 0 | 1.0 |
| train | 56.5 | 20.0 | 0 | 2.4 | 12.8 | 8.4 | | 0 |
| FreezingLayers | TotalParam. | TrainableParam. | ValLoss | ValAccuracy |
| --- | --- | --- | --- | --- |
| 0-164 | 22,992,167 | 17,830,439 | 0.9951 | 0.6559 | | | 0-132 | 22,992,167 | 19,519,719 | 0.9927 | 0.6670 |
| --- | --- | --- | --- | --- |
| 0-100 | 22,992,167 | 20,815,591 | 0.9480 | 0.6700 |
| Nofreeze | 22,992,167 | 22,957,575 | 0.7742 | 0.7565 | | 1 |
| FreezingLayers | TotalParam. | TrainableParam. | ValLoss | ValAccuracy |
| --- | --- | --- | --- | --- |
| 0-164 | 22,992,167 | 17,830,439 | 0.9951 | 0.6559 | | | V | H | E | Train,Val,Test | Train,Val,Test |
| --- | --- | --- | --- | --- |
| 10 | 128 | 114 | 9k,1k,10k | 0.9744,0.9952,0.9956 |
| 100 | 128 | 200 | 9k,1k,10k | 0.6370,0.5003,0.4996 |
| 100 | 128 | 82 | 135k,15k,10k | 0.9882,0.9907,0.9906 |
| 100 | 256 | 62 | 135k,15k,10k | 0.9886,0.9965,0.9969 |
| 1000 | 256 | 127 | 135k,15k,10k | 0.9069,0.7958,0.7971 | | 0 |
| FreezingLayers | TotalParam. | TrainableParam. | ValLoss | ValAccuracy |
| --- | --- | --- | --- | --- |
| 0-164 | 22,992,167 | 17,830,439 | 0.9951 | 0.6559 |
| 0-132 | 22,992,167 | 19,519,719 | 0.9927 | 0.6670 | | | 0-100 | 22,992,167 | 20,815,591 | 0.9480 | 0.6700 |
| --- | --- | --- | --- | --- |
| Nofreeze | 22,992,167 | 22,957,575 | 0.7742 | 0.7565 | | 1 |
| FreezingLayers | TotalParam. | TrainableParam. | ValLoss | ValAccuracy |
| --- | --- | --- | --- | --- |
| 0-164 | 22,992,167 | 17,830,439 | 0.9951 | 0.6559 |
| 0-132 | 22,992,167 | 19,519,719 | 0.9927 | 0.6670 | | | 100 | 128 | 82 | 135k,15k,10k | 0.9882,0.9907,0.9906 |
| --- | --- | --- | --- | --- |
| 100 | 256 | 62 | 135k,15k,10k | 0.9886,0.9965,0.9969 |
| 1000 | 256 | 127 | 135k,15k,10k | 0.9069,0.7958,0.7971 | | 0 |
| WithoutDebiasing | WithDebiasing | | | | |
| --- | --- | --- | --- | --- | --- |
| Female | Pred0 | Pred1 | Female | Pred0 | Pred1 |
| True0 | 4711 | 120 | True0 | 4518 | 313 |
| True1 | 265 | 325 | True1 | 263 | 327 | | | Male | Pred0 | Pred1 | Male | Pred0 | Pred1 |
| --- | --- | --- | --- | --- | --- |
| True0 | 6907 | 697 | True0 | 7071 | 533 |
| True1 | 1194 | 2062 | True1 | 1416 | 1840 | | 1 |
| WithoutDebiasing | WithDebiasing | | | | |
| --- | --- | --- | --- | --- | --- |
| Female | Pred0 | Pred1 | Female | Pred0 | Pred1 |
| True0 | 4711 | 120 | True0 | 4518 | 313 |
| True1 | 265 | 325 | True1 | 263 | 327 | | | | Comparison1 | Comparison2 | | |
| --- | --- | --- | --- | --- |
| GroupNumber | Group1 | Group2 | Group1 | Group2 |
| AgeRange | 4-10 | 60-80 | 11-20 | 60-80 |
| Female | 7 | 17 | 17 | 17 |
| Male | 5 | 7 | 19 | 7 |
| Total | 12 | 24 | 36 | 24 | | 0 |
| WithoutDebiasing | WithDebiasing | | | | |
| --- | --- | --- | --- | --- | --- |
| Female | Pred0 | Pred1 | Female | Pred0 | Pred1 |
| True0 | 4711 | 120 | True0 | 4518 | 313 |
| True1 | 265 | 325 | True1 | 263 | 327 | | | Male | Pred0 | Pred1 | Male | Pred0 | Pred1 |
| --- | --- | --- | --- | --- | --- |
| True0 | 6907 | 697 | True0 | 7071 | 533 |
| True1 | 1194 | 2062 | True1 | 1416 | 1840 | | 1 |
| WithoutDebiasing | WithDebiasing | | | | |
| --- | --- | --- | --- | --- | --- |
| Female | Pred0 | Pred1 | Female | Pred0 | Pred1 |
| True0 | 4711 | 120 | True0 | 4518 | 313 |
| True1 | 265 | 325 | True1 | 263 | 327 | | | AgeRange | 4-10 | 60-80 | 11-20 | 60-80 |
| --- | --- | --- | --- | --- |
| Female | 7 | 17 | 17 | 17 |
| Male | 5 | 7 | 19 | 7 |
| Total | 12 | 24 | 36 | 24 | | 0 |
| | |
| --- | --- |
| | |
| | |
| | |
| | |
| | |
| Michelleisnottheonelikedby22 | :−tuple(I,michelle),tuple(I,22). |
| MissHansoniswithdrawingmorethanthecustomerwhosenumberis3989. | :−tuple(I,hanson),tuple(J,3989),tuple(I,X),tuple(J,Y),<br>etype(A,rank),element(A,X),element(A,Y),X>Y,I!=J. |
| Albertisthemostpopular. | :−tuple(I,albert),tuple(J,X),highest(X),I!=J. |
| Petetalkedaboutgovernment. | :−tuple(I,pete),tuple(J,government),I!=J. | | | Jackhasashavedmustache | :−tuple(I,jack),tuple(J,mustache),I!=J. |
| --- | --- |
| Jackdidnotgetahaircutat1 | :−tuple(I,jack),tuple(I,1). |
| Thefirstopenhousewasnotlistedfor100000. | :−tuple(I,X),first(X),tuple(I,100000). |
| ThecandidatesurnamedWaringismorepopularthanthePanGlobal | :−tuple(I,waring),tuple(J,panglobal),tuple(I,X),tuple(J,Y),<br>etype(A,time),element(A,X),element(A,Y),X<Y. |
| Rosalynisnottheleastpopular. | :−tuple(I,rosalyn),tuple(I,X),lowest(X). | | 1 |
| | |
| --- | --- |
| | |
| | |
| | |
| | |
| | |
| Michelleisnottheonelikedby22 | :−tuple(I,michelle),tuple(I,22). |
| MissHansoniswithdrawingmorethanthecustomerwhosenumberis3989. | :−tuple(I,hanson),tuple(J,3989),tuple(I,X),tuple(J,Y),<br>etype(A,rank),element(A,X),element(A,Y),X>Y,I!=J. |
| Albertisthemostpopular. | :−tuple(I,albert),tuple(J,X),highest(X),I!=J. |
| Petetalkedaboutgovernment. | :−tuple(I,pete),tuple(J,government),I!=J. | | | FamilyName | Size | FamilyName | Size |
| --- | --- | --- | --- |
| ABU,Banload | 16 | Hupigon,AWQ | 219 |
| Agent,Agent | 42 | IRCBot,Sdbot | 66 |
| Agent,Small | 15 | LdPinch,LdPinch | 16 |
| Allaple,RAHack | 201 | Lmir,LegMir | 23 |
| Ardamax,Ardamax | 25 | Mydoom,Mydoom | 15 |
| Bactera,VB | 28 | Nilage,Lineage | 24 |
| Banbra,Banker | 52 | OnLineGames,Delf | 11 |
| Bancos,Banker | 46 | OnLineGames,LegMir | 76 |
| Banker,Banker | 317 | OnLineGames,Mmorpg | 19 |
| Banker,Delf | 20 | OnLineGames,OnLineGames | 23 |
| Banload,Banker | 138 | Parite,Pate | 71 |
| BDH,Small | 5 | Plemood,Pupil | 32 |
| BGM,Delf | 17 | PolyCrypt,Swizzor | 43 |
| Bifrose,CEP | 35 | Prorat,AVW | 40 |
| Bobax,Bobic | 15 | Rbot,Sdbot | 302 |
| DKI,PoisonIvy | 15 | SdBot,SdBot | 75 |
| DNSChanger,DNSChanger | 22 | Small,Downloader | 29 |
| Downloader,Agent | 13 | Stration,Warezov | 19 |
| Downloader,Delf | 22 | Swizzor,Obfuscated | 27 |
| Downloader,VB | 17 | Viking,HLLP | 32 |
| Gaobot,Agobot | 20 | Virut,Virut | 115 |
| Gobot,Gbot | 58 | VS,INService | 17 |
| Horst,CMQ | 48 | Zhelatin,ASH | 53 |
| Hupigon,ARR | 33 | Zlob,Puper | 64 | | 0 |
| | |
| --- | --- |
| | |
| | |
| | |
| | |
| | | | | Michelleisnottheonelikedby22 | :−tuple(I,michelle),tuple(I,22). |
| --- | --- |
| MissHansoniswithdrawingmorethanthecustomerwhosenumberis3989. | :−tuple(I,hanson),tuple(J,3989),tuple(I,X),tuple(J,Y),<br>etype(A,rank),element(A,X),element(A,Y),X>Y,I!=J. |
| Albertisthemostpopular. | :−tuple(I,albert),tuple(J,X),highest(X),I!=J. |
| Petetalkedaboutgovernment. | :−tuple(I,pete),tuple(J,government),I!=J. |
| Jackhasashavedmustache | :−tuple(I,jack),tuple(J,mustache),I!=J. |
| Jackdidnotgetahaircutat1 | :−tuple(I,jack),tuple(I,1). |
| Thefirstopenhousewasnotlistedfor100000. | :−tuple(I,X),first(X),tuple(I,100000). |
| ThecandidatesurnamedWaringismorepopularthanthePanGlobal | :−tuple(I,waring),tuple(J,panglobal),tuple(I,X),tuple(J,Y),<br>etype(A,time),element(A,X),element(A,Y),X<Y. |
| Rosalynisnottheleastpopular. | :−tuple(I,rosalyn),tuple(I,X),lowest(X). | | 1 |
| | |
| --- | --- |
| | |
| | |
| | |
| | |
| | | | | Bactera,VB | 28 | Nilage,Lineage | 24 |
| --- | --- | --- | --- |
| Banbra,Banker | 52 | OnLineGames,Delf | 11 |
| Bancos,Banker | 46 | OnLineGames,LegMir | 76 |
| Banker,Banker | 317 | OnLineGames,Mmorpg | 19 |
| Banker,Delf | 20 | OnLineGames,OnLineGames | 23 |
| Banload,Banker | 138 | Parite,Pate | 71 |
| BDH,Small | 5 | Plemood,Pupil | 32 |
| BGM,Delf | 17 | PolyCrypt,Swizzor | 43 |
| Bifrose,CEP | 35 | Prorat,AVW | 40 |
| Bobax,Bobic | 15 | Rbot,Sdbot | 302 |
| DKI,PoisonIvy | 15 | SdBot,SdBot | 75 |
| DNSChanger,DNSChanger | 22 | Small,Downloader | 29 |
| Downloader,Agent | 13 | Stration,Warezov | 19 |
| Downloader,Delf | 22 | Swizzor,Obfuscated | 27 |
| Downloader,VB | 17 | Viking,HLLP | 32 |
| Gaobot,Agobot | 20 | Virut,Virut | 115 |
| Gobot,Gbot | 58 | VS,INService | 17 |
| Horst,CMQ | 48 | Zhelatin,ASH | 53 |
| Hupigon,ARR | 33 | Zlob,Puper | 64 | | 0 |
| City | Users | Venues | Check-ins |
| --- | --- | --- | --- |
| Atlanta | 28,275 | 18,270 | 368,608 |
| Boston | 23,579 | 13,243 | 296,150 |
| Chicago | 42,791 | 33,261 | 715,652 | | | Minneapolis | 13,396 | 12,696 | 235,793 |
| --- | --- | --- | --- |
| Seattle | 16,205 | 15,051 | 260,023 | | 1 |
| City | Users | Venues | Check-ins |
| --- | --- | --- | --- |
| Atlanta | 28,275 | 18,270 | 368,608 |
| Boston | 23,579 | 13,243 | 296,150 |
| Chicago | 42,791 | 33,261 | 715,652 | | | City | N | K | NGC | C | Cr | d | dr | Q | Qr |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Atlanta | 13,011 | 46,756 | 11,476 | 0.16 | 0.0006 | 4.6 | 4.6 | 0.53 | 0.17 |
| Boston | 10,478 | 41,505 | 8,816 | 0.17 | 0.0010 | 4.3 | 4.0 | 0.45 | 0.15 |
| Chicago | 19,931 | 84,778 | 17,287 | 0.16 | 0.0004 | 4.6 | 4.9 | 0.47 | 0.14 |
| Minneapolis | 6,499 | 30,640 | 5,914 | 0.18 | 0.0016 | 4.4 | 4.2 | 0.41 | 0.12 |
| Seattle | 7,445 | 28,466 | 6,392 | 0.18 | 0.0008 | 4.4 | 4.6 | 0.46 | 0.16 | | 0 |
| City | Users | Venues | Check-ins |
| --- | --- | --- | --- |
| Atlanta | 28,275 | 18,270 | 368,608 |
| Boston | 23,579 | 13,243 | 296,150 |
| Chicago | 42,791 | 33,261 | 715,652 | | | Minneapolis | 13,396 | 12,696 | 235,793 |
| --- | --- | --- | --- |
| Seattle | 16,205 | 15,051 | 260,023 | | 1 |
| City | Users | Venues | Check-ins |
| --- | --- | --- | --- |
| Atlanta | 28,275 | 18,270 | 368,608 |
| Boston | 23,579 | 13,243 | 296,150 |
| Chicago | 42,791 | 33,261 | 715,652 | | | Minneapolis | 6,499 | 30,640 | 5,914 | 0.18 | 0.0016 | 4.4 | 4.2 | 0.41 | 0.12 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Seattle | 7,445 | 28,466 | 6,392 | 0.18 | 0.0008 | 4.4 | 4.6 | 0.46 | 0.16 | | 0 |
| | PPV | NPV | MCC | F1 | ACC |
| --- | --- | --- | --- | --- | --- |
| PCA+logisticregression | 0.875 | 0.805 | 0.545 | 0.609 | 0.816 |
| Non-transfer(L=1) | 0.725 | 0.983 | 0.755 | 0.829 | 0.878 |
| Non-transfer(L=2) | 0.718 | 0.967 | 0.726 | 0.811 | 0.867 |
| Non-transfer(L=3) | 0.644 | 0.981 | 0.676 | 0.773 | 0.827 | | | Non-transfer(L=4) | 0.644 | 0.981 | 0.676 | 0.773 | 0.827 |
| --- | --- | --- | --- | --- | --- |
| SSL(L=1) | 0.682 | 1 | 0.736 | 0.811 | 0.857 |
| SSL(L=2) | 0.644 | 0.981 | 0.676 | 0.773 | 0.827 |
| SSL(L=3) | 0.592 | 0.980 | 0.620 | 0.734 | 0.786 |
| SSL(L=4) | 0.558 | 0.978 | 0.580 | 0.707 | 0.755 |
| Oquabetal.(L=1) | 0.732 | 1 | 0.783 | 0.845 | 0.888 |
| Oquabetal.(L=2) | 0.771 | 0.952 | 0.753 | 0.831 | 0.888 |
| Oquabetal.(L=3) | 0.702 | 0.934 | 0.670 | 0.776 | 0.847 |
| Oquabetal.(L=4) | 0.658 | 0.947 | 0.648 | 0.761 | 0.827 |
| Agrawaletal.(L=1) | 0.750 | 1 | 0.800 | 0.857 | 0.898 |
| Agrawaletal.(L=2) | 0.744 | 0.983 | 0.796 | 0.841 | 0.888 |
| Agrawaletal.(L=3) | 0.690 | 0.982 | 0.722 | 0.806 | 0.857 |
| Agrawaletal.(L=4) | 0.667 | 1 | 0.720 | 0.8 | 0.847 |
| ATDL(L=1) | 0.844 | 0.955 | 0.812 | 0.871 | 0.918 |
| ATDL(L=2) | 0.871 | 0.955 | 0.834 | 0.885 | 0.929 |
| ATDL(L=3) | 0.875 | 0.970 | 0.859 | 0.903 | 0.939 |
| ATDL(L=4) | 0.958 | 0.905 | 0.806 | 0.852 | 0.918 | | 1 |
| | PPV | NPV | MCC | F1 | ACC |
| --- | --- | --- | --- | --- | --- |
| PCA+logisticregression | 0.875 | 0.805 | 0.545 | 0.609 | 0.816 |
| Non-transfer(L=1) | 0.725 | 0.983 | 0.755 | 0.829 | 0.878 |
| Non-transfer(L=2) | 0.718 | 0.967 | 0.726 | 0.811 | 0.867 |
| Non-transfer(L=3) | 0.644 | 0.981 | 0.676 | 0.773 | 0.827 | | | | PPV | NPV | MCC | F1 | ACC |
| --- | --- | --- | --- | --- | --- |
| Non-transfer(D=188)i | 0.718 | 0.967 | 0.726 | 0.811 | 0.867 |
| Non-transfer(D=500)i | 0.644 | 0.981 | 0.676 | 0.773 | 0.827 |
| Non-transfer(D=1,000)i | 0.7 | 0.966 | 0.709 | 0.8 | 0.857 |
| CIFAR-10(D=188)i | 0.657 | 0.889 | 0.568 | 0.708 | 0.806 |
| CIFAR-10(D=500)i | 0.923 | 0.912 | 0.804 | 0.857 | 0.918 |
| CIFAR-10(D=1,000)i | 0.690 | 0.982 | 0.722 | 0.806 | 0.857 |
| MNIST(D=188)i | 0.778 | 0.968 | 0.780 | 0.849 | 0.898 |
| MNIST(D=500)i | 0.839 | 0.940 | 0.786 | 0.852 | 0.908 |
| MNIST(D=1,000)i | 0.828 | 0.913 | 0.735 | 0.813 | 0.888 |
| 2-DEimage(D=188)i | 0.875 | 0.970 | 0.859 | 0.903 | 0.939 |
| 2-DEimage(D=500)i | 0.844 | 0.955 | 0.812 | 0.871 | 0.918 |
| 2-DEimage(D=1,000)i | 0.824 | 0.969 | 0.818 | 0.875 | 0.918 | | 0 |
| | PPV | NPV | MCC | F1 | ACC |
| --- | --- | --- | --- | --- | --- |
| PCA+logisticregression | 0.875 | 0.805 | 0.545 | 0.609 | 0.816 |
| Non-transfer(L=1) | 0.725 | 0.983 | 0.755 | 0.829 | 0.878 | | | Non-transfer(L=2) | 0.718 | 0.967 | 0.726 | 0.811 | 0.867 |
| --- | --- | --- | --- | --- | --- |
| Non-transfer(L=3) | 0.644 | 0.981 | 0.676 | 0.773 | 0.827 |
| Non-transfer(L=4) | 0.644 | 0.981 | 0.676 | 0.773 | 0.827 |
| SSL(L=1) | 0.682 | 1 | 0.736 | 0.811 | 0.857 |
| SSL(L=2) | 0.644 | 0.981 | 0.676 | 0.773 | 0.827 |
| SSL(L=3) | 0.592 | 0.980 | 0.620 | 0.734 | 0.786 |
| SSL(L=4) | 0.558 | 0.978 | 0.580 | 0.707 | 0.755 |
| Oquabetal.(L=1) | 0.732 | 1 | 0.783 | 0.845 | 0.888 |
| Oquabetal.(L=2) | 0.771 | 0.952 | 0.753 | 0.831 | 0.888 |
| Oquabetal.(L=3) | 0.702 | 0.934 | 0.670 | 0.776 | 0.847 |
| Oquabetal.(L=4) | 0.658 | 0.947 | 0.648 | 0.761 | 0.827 |
| Agrawaletal.(L=1) | 0.750 | 1 | 0.800 | 0.857 | 0.898 |
| Agrawaletal.(L=2) | 0.744 | 0.983 | 0.796 | 0.841 | 0.888 |
| Agrawaletal.(L=3) | 0.690 | 0.982 | 0.722 | 0.806 | 0.857 |
| Agrawaletal.(L=4) | 0.667 | 1 | 0.720 | 0.8 | 0.847 |
| ATDL(L=1) | 0.844 | 0.955 | 0.812 | 0.871 | 0.918 |
| ATDL(L=2) | 0.871 | 0.955 | 0.834 | 0.885 | 0.929 |
| ATDL(L=3) | 0.875 | 0.970 | 0.859 | 0.903 | 0.939 |
| ATDL(L=4) | 0.958 | 0.905 | 0.806 | 0.852 | 0.918 | | 1 |
| | PPV | NPV | MCC | F1 | ACC |
| --- | --- | --- | --- | --- | --- |
| PCA+logisticregression | 0.875 | 0.805 | 0.545 | 0.609 | 0.816 |
| Non-transfer(L=1) | 0.725 | 0.983 | 0.755 | 0.829 | 0.878 | | | MNIST(D=1,000)i | 0.828 | 0.913 | 0.735 | 0.813 | 0.888 |
| --- | --- | --- | --- | --- | --- |
| 2-DEimage(D=188)i | 0.875 | 0.970 | 0.859 | 0.903 | 0.939 |
| 2-DEimage(D=500)i | 0.844 | 0.955 | 0.812 | 0.871 | 0.918 |
| 2-DEimage(D=1,000)i | 0.824 | 0.969 | 0.818 | 0.875 | 0.918 | | 0 |
| λ | Sims<br>(LCFS) | Diff<br>Equations<br>(LCFS) | JIQ-<br>Random<br>(FCFS) |
| --- | --- | --- | --- |
| 0.50 | 1.10976 | 1.10980 | 1.12886 |
| 0.60 | 1.15732 | 1.15379 | 1.17987 |
| 0.70 | 1.23305 | 1.23310 | 1.25888 |
| 0.80 | 1.37805 | 1.37796 | 1.40787 |
| 0.90 | 1.79941 | 1.79893 | 1.83712 |
| 0.95 | 2.63751 | 2.63559 | 2.68138 |
| 0.96 | 3.05663 | 3.05429 | 3.10314 |
| 0.97 | 3.75659 | 3.75259 | 3.80509 | | | 0.98 | 5.15449 | 5.15006 | 5.20555 |
| --- | --- | --- | --- |
| 0.99 | 9.35407 | 9.34465 | 9.40217 | | 1 |
| λ | Sims<br>(LCFS) | Diff<br>Equations<br>(LCFS) | JIQ-<br>Random<br>(FCFS) |
| --- | --- | --- | --- |
| 0.50 | 1.10976 | 1.10980 | 1.12886 |
| 0.60 | 1.15732 | 1.15379 | 1.17987 |
| 0.70 | 1.23305 | 1.23310 | 1.25888 |
| 0.80 | 1.37805 | 1.37796 | 1.40787 |
| 0.90 | 1.79941 | 1.79893 | 1.83712 |
| 0.95 | 2.63751 | 2.63559 | 2.68138 |
| 0.96 | 3.05663 | 3.05429 | 3.10314 |
| 0.97 | 3.75659 | 3.75259 | 3.80509 | | | λ | Sims<br>JIQ-SQ(2) | Diff<br>Equations | JIQ-<br>Random |
| --- | --- | --- | --- |
| 0.50 | 1.01029 | 1.01033 | 1.12886 |
| 0.60 | 1.02377 | 1.02379 | 1.17987 |
| 0.70 | 1.05558 | 1.05557 | 1.25888 |
| 0.80 | 1.14044 | 1.14027 | 1.40787 |
| 0.90 | 1.46106 | 1.46035 | 1.83712 |
| 0.95 | 2.19241 | 2.19045 | 2.68138 |
| 0.96 | 2.57696 | 2.57420 | 3.10314 |
| 0.97 | 3.23186 | 3.22894 | 3.80509 |
| 0.98 | 4.57810 | 4.57186 | 5.20555 |
| 0.99 | 8.71553 | 8.70009 | 9.40217 | | 0 |
| λ | Sims<br>(LCFS) | Diff<br>Equations<br>(LCFS) | JIQ-<br>Random<br>(FCFS) |
| --- | --- | --- | --- |
| 0.50 | 1.10976 | 1.10980 | 1.12886 |
| 0.60 | 1.15732 | 1.15379 | 1.17987 | | | 0.70 | 1.23305 | 1.23310 | 1.25888 |
| --- | --- | --- | --- |
| 0.80 | 1.37805 | 1.37796 | 1.40787 |
| 0.90 | 1.79941 | 1.79893 | 1.83712 |
| 0.95 | 2.63751 | 2.63559 | 2.68138 |
| 0.96 | 3.05663 | 3.05429 | 3.10314 |
| 0.97 | 3.75659 | 3.75259 | 3.80509 |
| 0.98 | 5.15449 | 5.15006 | 5.20555 |
| 0.99 | 9.35407 | 9.34465 | 9.40217 | | 1 |
| λ | Sims<br>(LCFS) | Diff<br>Equations<br>(LCFS) | JIQ-<br>Random<br>(FCFS) |
| --- | --- | --- | --- |
| 0.50 | 1.10976 | 1.10980 | 1.12886 |
| 0.60 | 1.15732 | 1.15379 | 1.17987 | | | 0.70 | 1.05558 | 1.05557 | 1.25888 |
| --- | --- | --- | --- |
| 0.80 | 1.14044 | 1.14027 | 1.40787 |
| 0.90 | 1.46106 | 1.46035 | 1.83712 |
| 0.95 | 2.19241 | 2.19045 | 2.68138 |
| 0.96 | 2.57696 | 2.57420 | 3.10314 |
| 0.97 | 3.23186 | 3.22894 | 3.80509 |
| 0.98 | 4.57810 | 4.57186 | 5.20555 |
| 0.99 | 8.71553 | 8.70009 | 9.40217 | | 0 |
| Approach | Input | Actions | Evaluations | SuccessRate |
| --- | --- | --- | --- | --- |
| Singhetal. | Silhouette | 14 | LOSO | 82.4 |
| Eweiwietal. | Silhouette | 14 | LOSO | 91.9 |
| Cheemaetal. | Silhouette | 14 | LOSO | 86.0 | | | Chaaraouietal. | Silhouette | 14 | LOSO | 92.8 |
| --- | --- | --- | --- | --- |
| Proposed | Silhouette | 10 | NoTraining | 93.75 | | 1 |
| Approach | Input | Actions | Evaluations | SuccessRate |
| --- | --- | --- | --- | --- |
| Singhetal. | Silhouette | 14 | LOSO | 82.4 |
| Eweiwietal. | Silhouette | 14 | LOSO | 91.9 |
| Cheemaetal. | Silhouette | 14 | LOSO | 86.0 | | | Approach | Input | Actions | Evaluations | Rate |
| --- | --- | --- | --- | --- |
| IkizlerandDuyugulu | Silhouette | 9 | LOSO | 100 |
| TranandSorokin | Silhouette | 10 | LOSO | 100 |
| Eweiwietal. | Silhouette | 10 | LOSO | 100 |
| Harnandezetal. | Images | 10 | LASO | 90.3 |
| Cheemaetal. | Silhouette | 9 | LOSO | 91.6 |
| Chaaraouietal. | Silhouette | 9 | LOSO | 92.8 |
| Proposed | Silhouette | 9 | NoTraining | 95.06 | | 0 |
| Approach | Input | Actions | Evaluations | SuccessRate |
| --- | --- | --- | --- | --- |
| Singhetal. | Silhouette | 14 | LOSO | 82.4 |
| Eweiwietal. | Silhouette | 14 | LOSO | 91.9 |
| Cheemaetal. | Silhouette | 14 | LOSO | 86.0 | | | Chaaraouietal. | Silhouette | 14 | LOSO | 92.8 |
| --- | --- | --- | --- | --- |
| Proposed | Silhouette | 10 | NoTraining | 93.75 | | 1 |
| Approach | Input | Actions | Evaluations | SuccessRate |
| --- | --- | --- | --- | --- |
| Singhetal. | Silhouette | 14 | LOSO | 82.4 |
| Eweiwietal. | Silhouette | 14 | LOSO | 91.9 |
| Cheemaetal. | Silhouette | 14 | LOSO | 86.0 | | | TranandSorokin | Silhouette | 10 | LOSO | 100 |
| --- | --- | --- | --- | --- |
| Eweiwietal. | Silhouette | 10 | LOSO | 100 |
| Harnandezetal. | Images | 10 | LASO | 90.3 |
| Cheemaetal. | Silhouette | 9 | LOSO | 91.6 |
| Chaaraouietal. | Silhouette | 9 | LOSO | 92.8 |
| Proposed | Silhouette | 9 | NoTraining | 95.06 | | 0 |
| l | 100 | 200 | 400 | 800 | 1600 | 3200 | 6400 | 12800 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| BEGK | 4.7 | 51 | 110 | 340 | - | - | - | - |
| DL | 0.11 | 6.4 | 44 | 210 | - | - | - | - |
| BMR | 0.047 | 2.2 | 5.1 | 16 | 130 | - | - | - |
| HBC | 110 | - | - | - | - | - | - | - |
| KS | 0.057 | 2.6 | 4.6 | 20 | 97 | - | - | - |
| RS | 0.009 | 0.052 | 0.14 | 0.41 | 1.6 | 15 | 98 | 420 |
| DFS | 0.006 | 0.044 | 0.09 | 0.28 | 0.94 | 12 | 40 | 180 |
| \|F\| | 100 | 200 | 400 | 800 | 1600 | 3200 | 6400 | 12800 |
| \|F\| | 8 | 8 | 8 | 8 | 8 | 8 | 8 | 8 | | | \|dual(F)\| | 2341 | 22760 | 33087 | 79632 | 212761 | 2396735 | 4707877 | 16405082 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| \|S\| | 11.19 | 12.43 | 13.59 | 14.62 | 15.73 | 17.06 | 17.41 | 19.09 | | 1 |
| l | 100 | 200 | 400 | 800 | 1600 | 3200 | 6400 | 12800 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| BEGK | 4.7 | 51 | 110 | 340 | - | - | - | - |
| DL | 0.11 | 6.4 | 44 | 210 | - | - | - | - |
| BMR | 0.047 | 2.2 | 5.1 | 16 | 130 | - | - | - |
| HBC | 110 | - | - | - | - | - | - | - |
| KS | 0.057 | 2.6 | 4.6 | 20 | 97 | - | - | - |
| RS | 0.009 | 0.052 | 0.14 | 0.41 | 1.6 | 15 | 98 | 420 |
| DFS | 0.006 | 0.044 | 0.09 | 0.28 | 0.94 | 12 | 40 | 180 |
| \|F\| | 100 | 200 | 400 | 800 | 1600 | 3200 | 6400 | 12800 |
| \|F\| | 8 | 8 | 8 | 8 | 8 | 8 | 8 | 8 | | | ac | 200 | 150 | 130 | 110 | 90 | 70 | 50 | 30 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| BEGK | 0.54 | 3.2 | 8.7 | 22 | 87 | 430 | - | - |
| DL | 0.004 | 0.042 | 0.28 | 0.98 | 4.8 | 31 | 270 | - |
| BMR | 0.008 | 0.041 | 0.074 | 0.17 | 2.3 | 5.7 | 21 | 140 |
| HBC | 0.004 | 0.018 | 0.064 | 0.16 | 0.95 | 3.4 | 19 | 170 |
| KS | fail | fail | fail | fail | fail | fail | fail | fail |
| RS | 0.001 | 0.011 | 0.02 | 0.052 | 0.26 | 0.78 | 3.3 | 32 |
| DFS | 0.002 | 0.013 | 0.034 | 0.05 | 0.23 | 0.76 | 3.2 | 28 |
| cRS | 0 | 0.007 | 0.027 | 0.05 | 0.23 | 1.4 | 12 | 230 |
| cDFS | 0.001 | 0.005 | 0.019 | 0.051 | 0.18 | 0.95 | 8.4 | 170 |
| \|F\| | 81 | 447 | 990 | 2000 | 4322 | 10968 | 32207 | 135439 |
| \|F\| | 57.48 | 56.34 | 72.85 | 72.23 | 326.66 | 326.08 | 325.31 | 430.39 |
| \|dual(F)\| | 253 | 1039 | 1916 | 3547 | 7617 | 17486 | 47137 | 185218 |
| \|S\| | 2.57 | 3.77 | 4.25 | 4.73 | 5.09 | 5.70 | 6.46 | 7.32 | | 0 |
| l | 100 | 200 | 400 | 800 | 1600 | 3200 | 6400 | 12800 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| BEGK | 4.7 | 51 | 110 | 340 | - | - | - | - | | | DL | 0.11 | 6.4 | 44 | 210 | - | - | - | - |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| BMR | 0.047 | 2.2 | 5.1 | 16 | 130 | - | - | - |
| HBC | 110 | - | - | - | - | - | - | - |
| KS | 0.057 | 2.6 | 4.6 | 20 | 97 | - | - | - |
| RS | 0.009 | 0.052 | 0.14 | 0.41 | 1.6 | 15 | 98 | 420 |
| DFS | 0.006 | 0.044 | 0.09 | 0.28 | 0.94 | 12 | 40 | 180 |
| \|F\| | 100 | 200 | 400 | 800 | 1600 | 3200 | 6400 | 12800 |
| \|F\| | 8 | 8 | 8 | 8 | 8 | 8 | 8 | 8 |
| \|dual(F)\| | 2341 | 22760 | 33087 | 79632 | 212761 | 2396735 | 4707877 | 16405082 |
| \|S\| | 11.19 | 12.43 | 13.59 | 14.62 | 15.73 | 17.06 | 17.41 | 19.09 | | 1 |
| l | 100 | 200 | 400 | 800 | 1600 | 3200 | 6400 | 12800 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| BEGK | 4.7 | 51 | 110 | 340 | - | - | - | - | | | \|F\| | 81 | 447 | 990 | 2000 | 4322 | 10968 | 32207 | 135439 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| \|F\| | 57.48 | 56.34 | 72.85 | 72.23 | 326.66 | 326.08 | 325.31 | 430.39 |
| \|dual(F)\| | 253 | 1039 | 1916 | 3547 | 7617 | 17486 | 47137 | 185218 |
| \|S\| | 2.57 | 3.77 | 4.25 | 4.73 | 5.09 | 5.70 | 6.46 | 7.32 | | 0 |
| Datasets | Market-1501 | RAiD | CUHK03 | VIPeR | i-LIDS | CUHK01 | CUHK02 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| #identities | 1,501 | 43 | 1,360 | 632 | 119 | 971 | 1,816 | | | #BBoxes | 32,643 | 6920 | 13,164 | 1,264 | 476 | 1,942 | 7,264 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| #distractors | 2,793 | 0 | 0 | 0 | 0 | 0 | 0 |
| #cam.perID | 6 | 4 | 2 | 2 | 2 | 2 | 2 |
| DPMorHand | DPM | hand | DPM | hand | hand | hand | hand |
| Evaluation | mAP | CMC | CMC | CMC | CMC | CMC | CMC | | 1 |
| Datasets | Market-1501 | RAiD | CUHK03 | VIPeR | i-LIDS | CUHK01 | CUHK02 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| #identities | 1,501 | 43 | 1,360 | 632 | 119 | 971 | 1,816 | | | | MKCF | UT | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Dataset | MOTA | MOTP | MOTA | MOTP | | | | |
| | ViBe | Ours | ViBe | Ours | ViBe | Ours | ViBe | Ours |
| Sherbrooke | 0.317 | 0.523 | 0.553 | 0.576 | 0.404 | 0.690 | 0.576 | 0.590 |
| Rene-Levesque | 0.334 | 0.424 | 0.5309 | 0.660 | 0.565 | 0.613 | 0.582 | 0.705 |
| Rouen | 0.501 | 0.629 | 0.582 | 0.600 | 0.696 | 0.670 | 0.617 | 0.620 |
| St-Marc | 0.463 | 0.534 | 0.652 | 0.651 | 0.638 | 0.653 | 0.691 | 0.682 | | 0 |
| Datasets | Market-1501 | RAiD | CUHK03 | VIPeR | i-LIDS | CUHK01 | CUHK02 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| #identities | 1,501 | 43 | 1,360 | 632 | 119 | 971 | 1,816 |
| #BBoxes | 32,643 | 6920 | 13,164 | 1,264 | 476 | 1,942 | 7,264 | | | #distractors | 2,793 | 0 | 0 | 0 | 0 | 0 | 0 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| #cam.perID | 6 | 4 | 2 | 2 | 2 | 2 | 2 |
| DPMorHand | DPM | hand | DPM | hand | hand | hand | hand |
| Evaluation | mAP | CMC | CMC | CMC | CMC | CMC | CMC | | 1 |
| Datasets | Market-1501 | RAiD | CUHK03 | VIPeR | i-LIDS | CUHK01 | CUHK02 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| #identities | 1,501 | 43 | 1,360 | 632 | 119 | 971 | 1,816 |
| #BBoxes | 32,643 | 6920 | 13,164 | 1,264 | 476 | 1,942 | 7,264 | | | | ViBe | Ours | ViBe | Ours | ViBe | Ours | ViBe | Ours |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Sherbrooke | 0.317 | 0.523 | 0.553 | 0.576 | 0.404 | 0.690 | 0.576 | 0.590 |
| Rene-Levesque | 0.334 | 0.424 | 0.5309 | 0.660 | 0.565 | 0.613 | 0.582 | 0.705 |
| Rouen | 0.501 | 0.629 | 0.582 | 0.600 | 0.696 | 0.670 | 0.617 | 0.620 |
| St-Marc | 0.463 | 0.534 | 0.652 | 0.651 | 0.638 | 0.653 | 0.691 | 0.682 | | 0 |
| Non-EnglishorMath | Frequency | Comments |
| --- | --- | --- |
| Ø | 1in1,000 | ForSwedishnames | | | π | 1in5 | Commoninmath |
| --- | --- | --- |
| $ | 4in5 | Usedinbusiness |
| Ψ | 1in40,000 | Unexplainedusage | | 1 |
| Non-EnglishorMath | Frequency | Comments |
| --- | --- | --- |
| Ø | 1in1,000 | ForSwedishnames | | | Non-EnglishorMath | Frequency | Comments |
| --- | --- | --- |
| Ø | 1in1,000 | ForSwedishnames |
| π | 1in5 | Commoninmath |
| $ | 4in5 | Usedinbusiness |
| Ψ | 1in40,000 | Unexplainedusage | | 0 |
| Non-EnglishorMath | Frequency | Comments |
| --- | --- | --- |
| Ø | 1in1,000 | ForSwedishnames |
| π | 1in5 | Commoninmath | | | $ | 4in5 | Usedinbusiness |
| --- | --- | --- |
| Ψ | 1in40,000 | Unexplainedusage | | 1 |
| Non-EnglishorMath | Frequency | Comments |
| --- | --- | --- |
| Ø | 1in1,000 | ForSwedishnames |
| π | 1in5 | Commoninmath | | | π | 1in5 | Commoninmath |
| --- | --- | --- |
| $ | 4in5 | Usedinbusiness |
| Ψ | 1in40,000 | Unexplainedusage | | 0 |
| Datasets | Algorithms | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | Patterns | Dimensions | Classes | N | APR | MARWa=3 | MARWa=4 | LD-ABCD |
| Wine(40) | 178 | 13 | 3 | 82.31 | 86.80 | 88.02 | 91.76 | 100.0±0.000 |
| BreastCancer(160) | 683 | 9 | 2 | 93.26 | 94.66 | 94.37 | 96.02 | 100.0±0.000 | | | Iris(40) | 150 | 4 | 3 | - | - | - | - | 76.00±0.120 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| E-Coli(50) | 336 | 8 | 8 | - | - | - | - | 91.00±0.231 | | 1 |
| Datasets | Algorithms | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | Patterns | Dimensions | Classes | N | APR | MARWa=3 | MARWa=4 | LD-ABCD |
| Wine(40) | 178 | 13 | 3 | 82.31 | 86.80 | 88.02 | 91.76 | 100.0±0.000 |
| BreastCancer(160) | 683 | 9 | 2 | 93.26 | 94.66 | 94.37 | 96.02 | 100.0±0.000 | | | Dataset | #ofsamples | #ofclasses | #ofattributes |
| --- | --- | --- | --- |
| Breastcancer | 286 | 2 | 9 |
| Diabetes | 768 | 2 | 8 |
| SolarFlare | 144 | 3 | 9 |
| German | 1000 | 2 | 20 |
| Heart | 270 | 2 | 13 |
| Image | 2310 | 7 | 19 |
| Ringnorm | 7400 | 2 | 20 |
| Splice | 3190 | 3 | 60 |
| Thyroid | 215 | 3 | 5 |
| Twonorm | 7400 | 2 | 20 |
| Waveform | 5000 | 3 | 21 | | 0 |
| Datasets | Algorithms | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | Patterns | Dimensions | Classes | N | APR | MARWa=3 | MARWa=4 | LD-ABCD |
| Wine(40) | 178 | 13 | 3 | 82.31 | 86.80 | 88.02 | 91.76 | 100.0±0.000 | | | BreastCancer(160) | 683 | 9 | 2 | 93.26 | 94.66 | 94.37 | 96.02 | 100.0±0.000 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Iris(40) | 150 | 4 | 3 | - | - | - | - | 76.00±0.120 |
| E-Coli(50) | 336 | 8 | 8 | - | - | - | - | 91.00±0.231 | | 1 |
| Datasets | Algorithms | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | Patterns | Dimensions | Classes | N | APR | MARWa=3 | MARWa=4 | LD-ABCD |
| Wine(40) | 178 | 13 | 3 | 82.31 | 86.80 | 88.02 | 91.76 | 100.0±0.000 | | | Thyroid | 215 | 3 | 5 |
| --- | --- | --- | --- |
| Twonorm | 7400 | 2 | 20 |
| Waveform | 5000 | 3 | 21 | | 0 |
| TypeSize | Seq/STLSeqQS | ForkSURandfork |
| --- | --- | --- |
| 10000000<br>100000000<br>Random1000000000<br>8388607<br>33554431<br>134217727 | 1.2221.341<br>13.23213.492<br>131.266144.100<br>1.0161.113<br>4.4014.745<br>17.53718.405 | 0.2924.21.200<br>2.5855.18.442<br>24.6985.341.073<br>0.2683.81.126<br>0.7755.73.890<br>3.2495.48.504 |
| 10000000<br>100000000<br>Gauss1000000000<br>8388607<br>33554431<br>134217727 | 1.2341.331<br>11.86112.945<br>119.297129.859<br>1.0271.105<br>4.4074.197<br>15.82417.178 | 0.2554.81.481<br>2.4544.89.870<br>22.1495.487.425<br>0.2274.51.045<br>0.8375.34.592<br>2.7045.913.898 | | | 10000000<br>100000000<br>1000000000<br>Buckets8388607<br>33554431<br>134217727 | 1.1311.229<br>12.35012.771<br>122.627135.454<br>0.9271.010<br>4.1094.493<br>16.42917.091 | 0.2135.31.386<br>1.7776.910.155<br>18.9046.592.137<br>0.1715.41.104<br>0.6216.64.041<br>1.9608.412.782 |
| --- | --- | --- |
| 10000000<br>100000000<br>Staggered1000000000<br>8388607<br>33554431<br>134217727 | 1.1411.287<br>12.15012.460<br>115.845131.236<br>0.9631.126<br>4.1114.512<br>16.21716.838 | 0.2474.60.840<br>1.5747.710.318<br>19.6725.978.962<br>0.3223.00.934<br>0.5697.22.774<br>2.2307.312.705 | | 1 |
| TypeSize | Seq/STLSeqQS | ForkSURandfork |
| --- | --- | --- |
| 10000000<br>100000000<br>Random1000000000<br>8388607<br>33554431<br>134217727 | 1.2221.341<br>13.23213.492<br>131.266144.100<br>1.0161.113<br>4.4014.745<br>17.53718.405 | 0.2924.21.200<br>2.5855.18.442<br>24.6985.341.073<br>0.2683.81.126<br>0.7755.73.890<br>3.2495.48.504 |
| 10000000<br>100000000<br>Gauss1000000000<br>8388607<br>33554431<br>134217727 | 1.2341.331<br>11.86112.945<br>119.297129.859<br>1.0271.105<br>4.4074.197<br>15.82417.178 | 0.2554.81.481<br>2.4544.89.870<br>22.1495.487.425<br>0.2274.51.045<br>0.8375.34.592<br>2.7045.913.898 | | | TypeSize | Seq/STLSeqQS | ForkSURandfork |
| --- | --- | --- |
| 10000000<br>100000000<br>Random1000000000<br>8388607<br>33554431<br>134217727 | 1.4791.620<br>13.31913.742<br>107.080117.963<br>1.4471.580<br>4.8635.265<br>15.88816.617 | 0.3883.81.818<br>2.8914.613.607<br>20.2875.350.679<br>0.7741.91.772<br>0.9035.45.690<br>3.1035.112.115 |
| 10000000<br>100000000<br>Gauss1000000000<br>8388607<br>33554431<br>134217727 | 1.2521.354<br>11.92312.971<br>119.464130.255<br>1.0291.112<br>4.4084.236<br>15.88817.263 | 0.2754.61.621<br>2.5164.714.972<br>22.2885.4106.658<br>0.2474.21.353<br>0.8705.15.492<br>2.7715.719.774 |
| 10000000<br>100000000<br>Buckets1000000000<br>8388607<br>33554431<br>134217727 | 1.1311.233<br>12.37312.801<br>122.822135.833<br>0.9691.057<br>4.1114.505<br>16.48417.154 | 0.2414.71.517<br>1.8186.815.136<br>19.2146.4121.967<br>0.1865.21.244<br>0.6626.24.774<br>2.0388.117.203 |
| 10000000<br>100000000<br>Staggered1000000000<br>8388607<br>33554431<br>134217727 | 1.1511.301<br>12.18112.498<br>116.734131.596<br>0.9711.140<br>4.1164.527<br>16.28116.941 | 0.2794.11.509<br>1.6187.514.449<br>20.0675.8100.270<br>0.3392.91.330<br>0.6236.65.042<br>2.2997.117.563 | | 0 |
| TypeSize | Seq/STLSeqQS | ForkSURandfork |
| --- | --- | --- |
| 10000000<br>100000000<br>Random1000000000<br>8388607<br>33554431<br>134217727 | 1.2221.341<br>13.23213.492<br>131.266144.100<br>1.0161.113<br>4.4014.745<br>17.53718.405 | 0.2924.21.200<br>2.5855.18.442<br>24.6985.341.073<br>0.2683.81.126<br>0.7755.73.890<br>3.2495.48.504 | | | 10000000<br>100000000<br>Gauss1000000000<br>8388607<br>33554431<br>134217727 | 1.2341.331<br>11.86112.945<br>119.297129.859<br>1.0271.105<br>4.4074.197<br>15.82417.178 | 0.2554.81.481<br>2.4544.89.870<br>22.1495.487.425<br>0.2274.51.045<br>0.8375.34.592<br>2.7045.913.898 |
| --- | --- | --- |
| 10000000<br>100000000<br>1000000000<br>Buckets8388607<br>33554431<br>134217727 | 1.1311.229<br>12.35012.771<br>122.627135.454<br>0.9271.010<br>4.1094.493<br>16.42917.091 | 0.2135.31.386<br>1.7776.910.155<br>18.9046.592.137<br>0.1715.41.104<br>0.6216.64.041<br>1.9608.412.782 |
| 10000000<br>100000000<br>Staggered1000000000<br>8388607<br>33554431<br>134217727 | 1.1411.287<br>12.15012.460<br>115.845131.236<br>0.9631.126<br>4.1114.512<br>16.21716.838 | 0.2474.60.840<br>1.5747.710.318<br>19.6725.978.962<br>0.3223.00.934<br>0.5697.22.774<br>2.2307.312.705 | | 1 |
| TypeSize | Seq/STLSeqQS | ForkSURandfork |
| --- | --- | --- |
| 10000000<br>100000000<br>Random1000000000<br>8388607<br>33554431<br>134217727 | 1.2221.341<br>13.23213.492<br>131.266144.100<br>1.0161.113<br>4.4014.745<br>17.53718.405 | 0.2924.21.200<br>2.5855.18.442<br>24.6985.341.073<br>0.2683.81.126<br>0.7755.73.890<br>3.2495.48.504 | | | 10000000<br>100000000<br>Gauss1000000000<br>8388607<br>33554431<br>134217727 | 1.2521.354<br>11.92312.971<br>119.464130.255<br>1.0291.112<br>4.4084.236<br>15.88817.263 | 0.2754.61.621<br>2.5164.714.972<br>22.2885.4106.658<br>0.2474.21.353<br>0.8705.15.492<br>2.7715.719.774 |
| --- | --- | --- |
| 10000000<br>100000000<br>Buckets1000000000<br>8388607<br>33554431<br>134217727 | 1.1311.233<br>12.37312.801<br>122.822135.833<br>0.9691.057<br>4.1114.505<br>16.48417.154 | 0.2414.71.517<br>1.8186.815.136<br>19.2146.4121.967<br>0.1865.21.244<br>0.6626.24.774<br>2.0388.117.203 |
| 10000000<br>100000000<br>Staggered1000000000<br>8388607<br>33554431<br>134217727 | 1.1511.301<br>12.18112.498<br>116.734131.596<br>0.9711.140<br>4.1164.527<br>16.28116.941 | 0.2794.11.509<br>1.6187.514.449<br>20.0675.8100.270<br>0.3392.91.330<br>0.6236.65.042<br>2.2997.117.563 | | 0 |
| | Algorithm?? | Algorithm?? | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| n | ρ=0.1 | ρ=0.4 | ρ=0.7 | ρ=1.0 | ρ=0.1 | ρ=0.4 | ρ=0.7 | ρ=1.0 |
| 10 | 0.003 | 0.010 | 0.029 | 0.066 | 0.005 | 0.020 | 0.057 | 0.125 |
| 20 | 0.018 | 0.181 | 0.740 | 1.989 | 0.036 | 0.347 | 1.255 | 3.021 |
| 30 | 0.065 | 1.150 | 5.134 | 14.80 | 0.136 | 2.023 | 7.769 | 19.88 |
| 40 | 0.186 | 4.415 | 21.10 | 61.85 | 0.384 | 7.116 | 29.03 | 78.39 |
| 50 | 0.442 | 12.69 | 63.28 | 190.6 | 0.891 | 19.29 | 81.76 | 227.8 | | | 60 | 0.941 | 30.45 | 155.8 | 478.7 | 1.864 | 43.95 | 193.2 | 552.9 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 70 | 1.803 | 63.69 | 338.6 | 1054 | 3.452 | 88.57 | 403.8 | 1177 | | 1 |
| | Algorithm?? | Algorithm?? | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| n | ρ=0.1 | ρ=0.4 | ρ=0.7 | ρ=1.0 | ρ=0.1 | ρ=0.4 | ρ=0.7 | ρ=1.0 |
| 10 | 0.003 | 0.010 | 0.029 | 0.066 | 0.005 | 0.020 | 0.057 | 0.125 |
| 20 | 0.018 | 0.181 | 0.740 | 1.989 | 0.036 | 0.347 | 1.255 | 3.021 |
| 30 | 0.065 | 1.150 | 5.134 | 14.80 | 0.136 | 2.023 | 7.769 | 19.88 |
| 40 | 0.186 | 4.415 | 21.10 | 61.85 | 0.384 | 7.116 | 29.03 | 78.39 |
| 50 | 0.442 | 12.69 | 63.28 | 190.6 | 0.891 | 19.29 | 81.76 | 227.8 | | | 0 | 10 | 20 | 30 | 40 | 50 | 60 |
| --- | --- | --- | --- | --- | --- | --- |
| 9.3 | 7.6 | 5.9 | 4.3 | 3.0 | 2.0 | 1.2 |
| 38.2 | 31.1 | 24.4 | 18.3 | 13.1 | 8.8 | 5.5 |
| 86.7 | 70.4 | 55.2 | 41.4 | 29.7 | 19.9 | 12.4 |
| 155.4 | 125.9 | 98.9 | 74.4 | 53.5 | 36.1 | 22.5 |
| 326.0 | 264.5 | 207.6 | 156.2 | 111.9 | 75.7 | 47.1 | | 0 |
| | Algorithm?? | Algorithm?? | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| n | ρ=0.1 | ρ=0.4 | ρ=0.7 | ρ=1.0 | ρ=0.1 | ρ=0.4 | ρ=0.7 | ρ=1.0 |
| 10 | 0.003 | 0.010 | 0.029 | 0.066 | 0.005 | 0.020 | 0.057 | 0.125 |
| 20 | 0.018 | 0.181 | 0.740 | 1.989 | 0.036 | 0.347 | 1.255 | 3.021 | | | 30 | 0.065 | 1.150 | 5.134 | 14.80 | 0.136 | 2.023 | 7.769 | 19.88 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 40 | 0.186 | 4.415 | 21.10 | 61.85 | 0.384 | 7.116 | 29.03 | 78.39 |
| 50 | 0.442 | 12.69 | 63.28 | 190.6 | 0.891 | 19.29 | 81.76 | 227.8 |
| 60 | 0.941 | 30.45 | 155.8 | 478.7 | 1.864 | 43.95 | 193.2 | 552.9 |
| 70 | 1.803 | 63.69 | 338.6 | 1054 | 3.452 | 88.57 | 403.8 | 1177 | | 1 |
| | Algorithm?? | Algorithm?? | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| n | ρ=0.1 | ρ=0.4 | ρ=0.7 | ρ=1.0 | ρ=0.1 | ρ=0.4 | ρ=0.7 | ρ=1.0 |
| 10 | 0.003 | 0.010 | 0.029 | 0.066 | 0.005 | 0.020 | 0.057 | 0.125 |
| 20 | 0.018 | 0.181 | 0.740 | 1.989 | 0.036 | 0.347 | 1.255 | 3.021 | | | 86.7 | 70.4 | 55.2 | 41.4 | 29.7 | 19.9 | 12.4 |
| --- | --- | --- | --- | --- | --- | --- |
| 155.4 | 125.9 | 98.9 | 74.4 | 53.5 | 36.1 | 22.5 |
| 326.0 | 264.5 | 207.6 | 156.2 | 111.9 | 75.7 | 47.1 | | 0 |
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