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 |
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| | 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 |
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