premise string | hypothesis string | label int64 |
|---|---|---|
| g(p,..p)(Γ)m1m | TPLM | LSM |
| --- | --- | --- |
| ave | ave | | | | 2.05 | 0.57 | 1.52 |
| --- | --- | --- |
| 1.69 | 0.44 | 0.79 |
| 1.53 | 0.40 | 0.59 |
| 1.48 | 0.39 | 0.51 | | 1 |
| g(p,..p)(Γ)m1m | TPLM | LSM |
| --- | --- | --- |
| ave | ave | | | | | M1 | M2 | M3 | M4 | CE | M5 |
| --- | --- | --- | --- | --- | --- | --- |
| O1 | 0.763 | 0.775 | 0.694 | 0.602 | 0.701 | 0.534 |
| O2 | 1.05 | 1.02 | 0.894 | 0.838 | 0.908 | 0.752 |
| O3 | 0.781 | 0.693 | 0.674 | 0.571 | 0.561 | 0.549 |
| O4 | 0.310 | 0.307 | 0.265 | 0.238 | 0.236 | 0.212 |
| O5 | 0.344 | 0.321 | ... | 0 |
| g(p,..p)(Γ)m1m | TPLM | LSM |
| --- | --- | --- |
| ave | ave | |
| 2.05 | 0.57 | 1.52 | | | 1.69 | 0.44 | 0.79 |
| --- | --- | --- |
| 1.53 | 0.40 | 0.59 |
| 1.48 | 0.39 | 0.51 | | 1 |
| g(p,..p)(Γ)m1m | TPLM | LSM |
| --- | --- | --- |
| ave | ave | |
| 2.05 | 0.57 | 1.52 | | | O5 | 0.344 | 0.321 | 0.297 | 0.256 | 0.251 | 0.231 |
| --- | --- | --- | --- | --- | --- | --- |
| O6 | 0.732 | 0.714 | 0.593 | 0.576 | 0.585 | 0.541 | | 0 |
| Negative | Positive | Neutral | TotalMentions | |
| --- | --- | --- | --- | --- |
| PSD | 69723 | 121 | 37133 | 106977 |
| PS | 28660 | 225 | 15326 | 44211 | | | CDS | 41935 | 51 | 17554 | 59540 |
| --- | --- | --- | --- | --- |
| CDU | 2445 | 79 | 5604 | 8128 |
| BE | 9603 | 306 | 4214 | 14123 | | 1 |
| Negative | Positive | Neutral | TotalMentions | |
| --- | --- | --- | --- | --- |
| PSD | 69723 | 121 | 37133 | 106977 |
| PS | 28660 | 225 | 15326 | 44211 | | | | BL | SL | SR | BH | SH | Ins |
| --- | --- | --- | --- | --- | --- | --- |
| BL | 17 | 5 | 1 | - | - | 10 |
| SL | 4 | 24 | 2 | - | 1 | 19 |
| SR | 3 | - | 29 | - | 1 | 44 |
| BH | - | 1 | - | 20 | 1 | 19 |
| SH | 1 | - | - | 1 | 23 | 32 |
| Del | - | 1 | - | - | - | - |
| Total | 25 | 31 | 32 | 21 | 26 | 124 | | 0 |
| Negative | Positive | Neutral | TotalMentions | |
| --- | --- | --- | --- | --- |
| PSD | 69723 | 121 | 37133 | 106977 |
| PS | 28660 | 225 | 15326 | 44211 |
| CDS | 41935 | 51 | 17554 | 59540 | | | CDU | 2445 | 79 | 5604 | 8128 |
| --- | --- | --- | --- | --- |
| BE | 9603 | 306 | 4214 | 14123 | | 1 |
| Negative | Positive | Neutral | TotalMentions | |
| --- | --- | --- | --- | --- |
| PSD | 69723 | 121 | 37133 | 106977 |
| PS | 28660 | 225 | 15326 | 44211 |
| CDS | 41935 | 51 | 17554 | 59540 | | | SL | 4 | 24 | 2 | - | 1 | 19 |
| --- | --- | --- | --- | --- | --- | --- |
| SR | 3 | - | 29 | - | 1 | 44 |
| BH | - | 1 | - | 20 | 1 | 19 |
| SH | 1 | - | - | 1 | 23 | 32 |
| Del | - | 1 | - | - | - | - |
| Total | 25 | 31 | 32 | 21 | 26 | 124 | | 0 |
| FW | Mult.<br>inF(P) | Occurrences<br>incorpus | p1<br>(cid:101) | p2<br>(cid:101) |
| --- | --- | --- | --- | --- |
| | 95617 | 215306 | 0.36 | 0.36 |
| , | 3239 | 9945 | 0.50 | 0.43 |
| the | 2577 | 8383 | 0.40 | 0.46 |
| a | 1948 | 6057 | 0.40 | 0.49 |
| of | 1335 | 6048 | 0.34 | 0.46 |
| and | 1290 | 6143 | 0.45... | | as | 211 | 1662 | 0.48 | 0.39 |
| --- | --- | --- | --- | --- |
| for | 178 | 1340 | 0.47 | 0.39 |
| its | 163 | 1294 | 0.29 | 0.56 |
| you | 136 | 1054 | 0.43 | 0.36 |
| this | 120 | 1076 | 0.32 | 0.51 |
| are | 101 | 732 | 0.38 | 0.54 |
| on | 96 | 870 | 0.49 | 0.36 |
| has | 92 | 692 | 0.52 | 0.35 |
| The | 87 | 3... | 1 |
| FW | Mult.<br>inF(P) | Occurrences<br>incorpus | p1<br>(cid:101) | p2<br>(cid:101) |
| --- | --- | --- | --- | --- |
| | 95617 | 215306 | 0.36 | 0.36 |
| , | 3239 | 9945 | 0.50 | 0.43 |
| the | 2577 | 8383 | 0.40 | 0.46 |
| a | 1948 | 6057 | 0.40 | 0.49 |
| of | 1335 | 6048 | 0.34 | 0.46 |
| and | 1290 | 6143 | 0.45... | | FW | Mult.<br>inF(P) | Occurrences<br>incorpus | p1<br>(cid:101) | p2<br>(cid:101) |
| --- | --- | --- | --- | --- |
| | 151778 | 535729 | 0.29 | 0.29 |
| the | 13113 | 35792 | 0.37 | 0.42 |
| , | 9865 | 27186 | 0.44 | 0.39 |
| to | 5590 | 16807 | 0.40 | 0.38 |
| of | 3526 | 18548 | 0.28 | 0.35 |
| a | 2596 | 8343 |... | 0 |
| FW | Mult.<br>inF(P) | Occurrences<br>incorpus | p1<br>(cid:101) | p2<br>(cid:101) |
| --- | --- | --- | --- | --- |
| | 95617 | 215306 | 0.36 | 0.36 |
| , | 3239 | 9945 | 0.50 | 0.43 |
| the | 2577 | 8383 | 0.40 | 0.46 |
| a | 1948 | 6057 | 0.40 | 0.49 |
| of | 1335 | 6048 | 0.34 | 0.46 |
| and | 1290 | 6143 | 0.45... | | with | 212 | 1479 | 0.45 | 0.44 |
| --- | --- | --- | --- | --- |
| as | 211 | 1662 | 0.48 | 0.39 |
| for | 178 | 1340 | 0.47 | 0.39 |
| its | 163 | 1294 | 0.29 | 0.56 |
| you | 136 | 1054 | 0.43 | 0.36 |
| this | 120 | 1076 | 0.32 | 0.51 |
| are | 101 | 732 | 0.38 | 0.54 |
| on | 96 | 870 | 0.49 | 0.36 |
| has | 92 ... | 1 |
| FW | Mult.<br>inF(P) | Occurrences<br>incorpus | p1<br>(cid:101) | p2<br>(cid:101) |
| --- | --- | --- | --- | --- |
| | 95617 | 215306 | 0.36 | 0.36 |
| , | 3239 | 9945 | 0.50 | 0.43 |
| the | 2577 | 8383 | 0.40 | 0.46 |
| a | 1948 | 6057 | 0.40 | 0.49 |
| of | 1335 | 6048 | 0.34 | 0.46 |
| and | 1290 | 6143 | 0.45... | | of | 3526 | 18548 | 0.28 | 0.35 |
| --- | --- | --- | --- | --- |
| a | 2596 | 8343 | 0.41 | 0.41 |
| and | 2529 | 13954 | 0.39 | 0.41 |
| in | 2106 | 11109 | 0.48 | 0.28 |
| that | 1675 | 8052 | 0.37 | 0.38 |
| is | 1212 | 8572 | 0.33 | 0.32 |
| be | 1016 | 4761 | 0.28 | 0.48 |
| for | 844 | 5515 | 0.40 | 0.37 |
| t... | 0 |
| Learningconcept | t-testp-value | NullHypothesis | KS-testp-value | NullHypothesis |
| --- | --- | --- | --- | --- |
| binoculars | 0.0059 | Reject | 0.1009 | Accept | | | career | 0.044 | Reject | 0.0254 | Reject |
| --- | --- | --- | --- | --- |
| champion | 0.492 | Accept | 0.6275 | Accept |
| conflict | 0.002 | Reject | 0.0088 | Reject |
| deciduous | 2.07×10 | Reject | 1.76×10 | Reject |
| dozen | 0.00023 | Reject | 0.0021 | Reject |
| half | 0.006 | Reject | 0.0089 | Reject |
| hi... | 1 |
| Learningconcept | t-testp-value | NullHypothesis | KS-testp-value | NullHypothesis |
| --- | --- | --- | --- | --- |
| binoculars | 0.0059 | Reject | 0.1009 | Accept | | | Model | TripAdvisorData | OpenTableData | | |
| --- | --- | --- | --- | --- |
| | | | | |
| OrdinalAspectBias | -557.08 | 1.00 | -493.79 | 1.03 |
| ContinuousAspectBias | -1050.32 | 3.13 | -560.14 | 2.21 |
| OrdinalNoBias | -689.76 | 1.47 | -546.25 | 1.95 |
| ContinuousNoBias | -1904.64 | 3.52 | -651.16 | 2.39... | 0 |
| Learningconcept | t-testp-value | NullHypothesis | KS-testp-value | NullHypothesis |
| --- | --- | --- | --- | --- |
| binoculars | 0.0059 | Reject | 0.1009 | Accept |
| career | 0.044 | Reject | 0.0254 | Reject |
| champion | 0.492 | Accept | 0.6275 | Accept |
| conflict | 0.002 | Reject | 0.0088 | Reject |
| deciduo... | | sculpture | 0.002 | Reject | 0.0004 | Reject |
| --- | --- | --- | --- | --- |
| subtraction | 0.002 | Reject | 0.0002 | Reject |
| tool | 0.075 | Reject | 0.0259 | Reject |
| veterinarian | 0.056 | Reject | 0.1206 | Accept | | 1 |
| Learningconcept | t-testp-value | NullHypothesis | KS-testp-value | NullHypothesis |
| --- | --- | --- | --- | --- |
| binoculars | 0.0059 | Reject | 0.1009 | Accept |
| career | 0.044 | Reject | 0.0254 | Reject |
| champion | 0.492 | Accept | 0.6275 | Accept |
| conflict | 0.002 | Reject | 0.0088 | Reject |
| deciduo... | | ContinuousNoBias | -1904.64 | 3.52 | -651.16 | 2.39 |
| --- | --- | --- | --- | --- |
| OrdinalGlobalBias | -2438.52 | 2.85 | -570.28 | 2.37 |
| ContinuousGlobalBias | -2632.95 | 3.91 | -595.62 | 2.41 | | 0 |
| D1 | D2 | D3 |
| --- | --- | --- |
| L1lossRMSEPDAR | L1lossRMSEPDAR | L1lossRMSEPDAR |
| 0.00960.01910.1635 | 0.00980.01930.1677 | 0.00970.01920.1611 | | | 0.00930.01880.1594 | 0.00950.0190.1641 | 0.00940.01890.1578 |
| --- | --- | --- |
| 0.00910.01850.1549 | 0.00940.01890.1604 | 0.00920.01870.1549 |
| 0.00910.01860.1557 | 0.00940.01890.1601 | 0.00920.01870.1552 |
| 0.0090.01840.1533 | 0.00920.01870.1585 | 0.00910.01850.1537 | | 1 |
| D1 | D2 | D3 |
| --- | --- | --- |
| L1lossRMSEPDAR | L1lossRMSEPDAR | L1lossRMSEPDAR |
| 0.00960.01910.1635 | 0.00980.01930.1677 | 0.00970.01920.1611 | | | D1 | D2 | D3 |
| --- | --- | --- |
| L1lossRMSEPDAR | L1lossRMSEPDAR | L1lossRMSEPDAR |
| 0.00960.01920.1801 | 0.00960.01920.1806 | 0.00950.01910.1758 |
| 0.00960.01910.1713 | 0.00970.01920.1726 | 0.00950.01910.1668 |
| 0.00930.01880.1662 | 0.00940.01890.1686 | 0.00930.01880.1633 |
| 0.00910.01850.1549 | 0.00940.0189... | 0 |
| D1 | D2 | D3 |
| --- | --- | --- |
| L1lossRMSEPDAR | L1lossRMSEPDAR | L1lossRMSEPDAR | | | 0.00960.01910.1635 | 0.00980.01930.1677 | 0.00970.01920.1611 |
| --- | --- | --- |
| 0.00930.01880.1594 | 0.00950.0190.1641 | 0.00940.01890.1578 |
| 0.00910.01850.1549 | 0.00940.01890.1604 | 0.00920.01870.1549 |
| 0.00910.01860.1557 | 0.00940.01890.1601 | 0.00920.01870.1552 |
| 0.0090.01840.1533 | 0.00920.01870.1585 ... | 1 |
| D1 | D2 | D3 |
| --- | --- | --- |
| L1lossRMSEPDAR | L1lossRMSEPDAR | L1lossRMSEPDAR | | | 0.00960.01920.1801 | 0.00960.01920.1806 | 0.00950.01910.1758 |
| --- | --- | --- |
| 0.00960.01910.1713 | 0.00970.01920.1726 | 0.00950.01910.1668 |
| 0.00930.01880.1662 | 0.00940.01890.1686 | 0.00930.01880.1633 |
| 0.00910.01850.1549 | 0.00940.01890.1604 | 0.00920.01870.1549 |
| 0.00910.01850.1509 | 0.00940.01890.157... | 0 |
| Train.data | Eval.data | smooth? | mAP | AUC |
| --- | --- | --- | --- | --- |
| COCO | COCO | - | 0.83 | 0.84 |
| COCO<br>COCO | YT-BB<br>YT-BB | no<br>yes | 0.77<br>0.77 | 0.78<br>0.78 | | | YT-BB<br>YT-BB | YT-BB<br>YT-BB | no<br>yes | 0.93<br>0.95 | 0.94<br>0.96 |
| --- | --- | --- | --- | --- |
| YT-BB | COCO | - | 0.66 | 0.67 | | 1 |
| Train.data | Eval.data | smooth? | mAP | AUC |
| --- | --- | --- | --- | --- |
| COCO | COCO | - | 0.83 | 0.84 |
| COCO<br>COCO | YT-BB<br>YT-BB | no<br>yes | 0.77<br>0.77 | 0.78<br>0.78 | | | | scale | One-shot-independent | One-shot-greedy | CascadeTrimming | Trim-Train |
| --- | --- | --- | --- | --- | --- |
| Param. | - | 58,544 | 58,544 | 58,544 | 58,544 |
| Set5 | 2<br>3<br>4 | 37.20/0.9546/0.012<br>33.24/0.9161/0.012<br>31.02/0.8802/0.013 | 37.18/0.9549/0.012<br>33.21/0.9158/0.012<br>31.05/0.8805/0... | 0 |
| Train.data | Eval.data | smooth? | mAP | AUC |
| --- | --- | --- | --- | --- |
| COCO | COCO | - | 0.83 | 0.84 | | | COCO<br>COCO | YT-BB<br>YT-BB | no<br>yes | 0.77<br>0.77 | 0.78<br>0.78 |
| --- | --- | --- | --- | --- |
| YT-BB<br>YT-BB | YT-BB<br>YT-BB | no<br>yes | 0.93<br>0.95 | 0.94<br>0.96 |
| YT-BB | COCO | - | 0.66 | 0.67 | | 1 |
| Train.data | Eval.data | smooth? | mAP | AUC |
| --- | --- | --- | --- | --- |
| COCO | COCO | - | 0.83 | 0.84 | | | Set14 | 2<br>3<br>4 | 32.80/0.9096/0.022<br>29.70/0.8270/0.022<br>27.91/0.7633/0.022 | 32.76/0.9100/0.021<br>29.68/0.8266/0.022<br>27.91/0.7639/0.022 | 33.23/0.9115/0.022<br>29.78/0.8308/0.022<br>28.06/0.7664/0.022 | 33.00/0.9105/0.021<br>29.72/0.8290/0.022<br>27.97/0.7650/0.022 |
| --- | --- | --- | --- | --- | --- ... | 0 |
| # | Features | Description |
| --- | --- | --- |
| 1 | TF | Termfrequencyofwintheshorttext |
| 2 | IDF | Inversedocumentfrequencyofwinthewholecollection |
| 3 | SF | Numberofsentencesintheshorttextthatcontainw |
| 4 | First | Whetherwexistsinthefirstsentence | | | 5 | Last | Whetherwexistsinthelastsentence |
| --- | --- | --- |
| 6 | NE | Whetherwisanamedentity(NE) |
| 7 | NEFirst | WhetherwisNEinthefirstsentence |
| 8 | NELast | WhetherwisNEinthelastsentence |
| 9 | POS | Partofspeechofw | | 1 |
| # | Features | Description |
| --- | --- | --- |
| 1 | TF | Termfrequencyofwintheshorttext |
| 2 | IDF | Inversedocumentfrequencyofwinthewholecollection |
| 3 | SF | Numberofsentencesintheshorttextthatcontainw |
| 4 | First | Whetherwexistsinthefirstsentence | | | Featureindex | Description |
| --- | --- |
| 1 | Whetherthecandidateisinthesamesentencewiththeconnective |
| 2 | Connectiveword |
| 3 | Down-caseconnectiveword |
| 4 | Candidateword |
| 5 | Beforeoraftertheconnectiveword |
| 6 | Connectivewhereinthesentence(beginning,middle,end) |
| 7 | 2,6 |
| 8 | Headtoconnectiveth... | 0 |
| # | Features | Description |
| --- | --- | --- |
| 1 | TF | Termfrequencyofwintheshorttext |
| 2 | IDF | Inversedocumentfrequencyofwinthewholecollection |
| 3 | SF | Numberofsentencesintheshorttextthatcontainw |
| 4 | First | Whetherwexistsinthefirstsentence |
| 5 | Last | Whetherwexistsinthelastsentence | | | 6 | NE | Whetherwisanamedentity(NE) |
| --- | --- | --- |
| 7 | NEFirst | WhetherwisNEinthefirstsentence |
| 8 | NELast | WhetherwisNEinthelastsentence |
| 9 | POS | Partofspeechofw | | 1 |
| # | Features | Description |
| --- | --- | --- |
| 1 | TF | Termfrequencyofwintheshorttext |
| 2 | IDF | Inversedocumentfrequencyofwinthewholecollection |
| 3 | SF | Numberofsentencesintheshorttextthatcontainw |
| 4 | First | Whetherwexistsinthefirstsentence |
| 5 | Last | Whetherwexistsinthelastsentence | | | 9 | Collapsedpathwithoutpart-of-speech |
| --- | --- |
| 10 | Thelengthof8 |
| 11 | Dependencypathfromargumenttoconnective |
| 12 | Typeofconnective | | 0 |
| | LMR | PD | AMR | MP |
| --- | --- | --- | --- | --- |
| OLS | 29 | 27 | 22 | 5.4 |
| NN | 9.2 | 20 | 7.9 | 3.9 |
| GP-SSLK1/2 | 7.2 | 12 | 7 | 1.8 | | | GP-SSLK3/2 | 7.5 | 11 | 4.8 | 1.4 |
| --- | --- | --- | --- | --- |
| GP-SSLK∞ | 6.3 | 6.3 | 4.8 | 1.3 | | 1 |
| | LMR | PD | AMR | MP |
| --- | --- | --- | --- | --- |
| OLS | 29 | 27 | 22 | 5.4 |
| NN | 9.2 | 20 | 7.9 | 3.9 |
| GP-SSLK1/2 | 7.2 | 12 | 7 | 1.8 | | | | SDR(dB) | SIR(dB) | SAR(dB) | | | |
| --- | --- | --- | --- | --- | --- | --- |
| | MDLD | GaussSep | MDLD | GaussSep | MDLD | GaussSep |
| Dev3Female3 | 6.02 | 16.93 | 23.84 | 22.43 | 6.17 | 18.40 |
| Example3×5 | 3.91 | 9.94 | 17.92 | 15.21 | 4.17 | 11.68 |
| Example4×8 | 2.24 | -18.63 | 16.4 | -17.58 | 2.52... | 0 |
| | LMR | PD | AMR | MP |
| --- | --- | --- | --- | --- |
| OLS | 29 | 27 | 22 | 5.4 |
| NN | 9.2 | 20 | 7.9 | 3.9 | | | GP-SSLK1/2 | 7.2 | 12 | 7 | 1.8 |
| --- | --- | --- | --- | --- |
| GP-SSLK3/2 | 7.5 | 11 | 4.8 | 1.4 |
| GP-SSLK∞ | 6.3 | 6.3 | 4.8 | 1.3 | | 1 |
| | LMR | PD | AMR | MP |
| --- | --- | --- | --- | --- |
| OLS | 29 | 27 | 22 | 5.4 |
| NN | 9.2 | 20 | 7.9 | 3.9 | | | Dev3Female3 | 6.02 | 16.93 | 23.84 | 22.43 | 6.17 | 18.40 |
| --- | --- | --- | --- | --- | --- | --- |
| Example3×5 | 3.91 | 9.94 | 17.92 | 15.21 | 4.17 | 11.68 |
| Example4×8 | 2.24 | -18.63 | 16.4 | -17.58 | 2.52 | 9.39 | | 0 |
| Parameter | |
| --- | --- |
| Audioresamplingfreq. | 16KHz | | | BandsofMel-spectrogram | 80 |
| --- | --- |
| Hoplength | 400 |
| Convolutionlayers,channels,filter,strides | 1,64,20×5,8×2 |
| Recurrentlayersize | 128 |
| Fullyconnectedsize | 128 |
| Dropoutprobability | 0.9 |
| LearningRate | 10 |
| Maxgradientnorm | 100 |
| Gradientclippingmax.value | 5 | | 1 |
| Parameter | |
| --- | --- |
| Audioresamplingfreq. | 16KHz | | | Parameter | Single-Speaker | VCTK | LibriSpeech |
| --- | --- | --- | --- |
| FFTSize | 4096 | 4096 | 4096 |
| FFTWindowSize/Shift | 2400/600 | 2400/600 | 1600/400 |
| AudioSampleRate | 48000 | 48000 | 16000 |
| ReductionFactorr | 4 | 4 | 4 |
| MelBands | 80 | 80 | 80 |
| SharpeningFactor | 1.4 | 1.4 | 1.4 |
| Charac... | 0 |
| Parameter | |
| --- | --- |
| Audioresamplingfreq. | 16KHz |
| BandsofMel-spectrogram | 80 |
| Hoplength | 400 |
| Convolutionlayers,channels,filter,strides | 1,64,20×5,8×2 |
| Recurrentlayersize | 128 |
| Fullyconnectedsize | 128 | | | Dropoutprobability | 0.9 |
| --- | --- |
| LearningRate | 10 |
| Maxgradientnorm | 100 |
| Gradientclippingmax.value | 5 | | 1 |
| Parameter | |
| --- | --- |
| Audioresamplingfreq. | 16KHz |
| BandsofMel-spectrogram | 80 |
| Hoplength | 400 |
| Convolutionlayers,channels,filter,strides | 1,64,20×5,8×2 |
| Recurrentlayersize | 128 |
| Fullyconnectedsize | 128 | | | FFTWindowSize/Shift | 2400/600 | 2400/600 | 1600/400 |
| --- | --- | --- | --- |
| AudioSampleRate | 48000 | 48000 | 16000 |
| ReductionFactorr | 4 | 4 | 4 |
| MelBands | 80 | 80 | 80 |
| SharpeningFactor | 1.4 | 1.4 | 1.4 |
| CharacterEmbeddingDim. | 256 | 256 | 256 |
| EncoderLayers/Conv.Width/Channels | 7/5/64 | 7... | 0 |
| Code | Extractions | SD,L=1 | HD,L=3 | SD,L=3 | SD,L=3,m=3 |
| --- | --- | --- | --- | --- | --- |
| (3,1,[6]) | 10.000.000 | 3.98e-02 | 6.59e-01 | 2.24e-02 | 5.70e-05 |
| (3,1,[7]) | 10.000.000 | 1.73e-02 | 5.93e-01 | 9.43e-03 | 6.00e-06 |
| (3,1,[8]) | 10.000.000 | 9.72e-03 | 5.09e-01 | 5.14e-03 | 1.00e-06 | | | (3,1,[9]) | 10.000.000 | 5.07e-03 | 4.28e-01 | 2.65e-03 | <1e-07 |
| --- | --- | --- | --- | --- | --- |
| (3,1,[10]) | 10.000.000 | 2.30e-03 | 3.39e-01 | 1.17e-03 | <1e-07 | | 1 |
| Code | Extractions | SD,L=1 | HD,L=3 | SD,L=3 | SD,L=3,m=3 |
| --- | --- | --- | --- | --- | --- |
| (3,1,[6]) | 10.000.000 | 3.98e-02 | 6.59e-01 | 2.24e-02 | 5.70e-05 |
| (3,1,[7]) | 10.000.000 | 1.73e-02 | 5.93e-01 | 9.43e-03 | 6.00e-06 |
| (3,1,[8]) | 10.000.000 | 9.72e-03 | 5.09e-01 | 5.14e-03 | 1.00e-06 | | | Extraction<br>Methods | Seqsize=10,000 | | |
| --- | --- | --- | --- |
| α=0.10 | α=0.05 | α=0.01 | |
| | 35.64 | 23.93 | 9.04 |
| | 58.51 | 54.26 | 45.74 |
| | 47.87 | 27.66 | 0.00 |
| | 51.60 | 36.70 | 13.83 |
| | 65.43 | 61.17 | 48.40 |
| | 64.89 | 64.89 | 47.87 |
| | 71.28 | 70.21 | 59.57 |
| MRE-IPI | ... | 0 |
| Code | Extractions | SD,L=1 | HD,L=3 | SD,L=3 | SD,L=3,m=3 |
| --- | --- | --- | --- | --- | --- |
| (3,1,[6]) | 10.000.000 | 3.98e-02 | 6.59e-01 | 2.24e-02 | 5.70e-05 |
| (3,1,[7]) | 10.000.000 | 1.73e-02 | 5.93e-01 | 9.43e-03 | 6.00e-06 | | | (3,1,[8]) | 10.000.000 | 9.72e-03 | 5.09e-01 | 5.14e-03 | 1.00e-06 |
| --- | --- | --- | --- | --- | --- |
| (3,1,[9]) | 10.000.000 | 5.07e-03 | 4.28e-01 | 2.65e-03 | <1e-07 |
| (3,1,[10]) | 10.000.000 | 2.30e-03 | 3.39e-01 | 1.17e-03 | <1e-07 | | 1 |
| Code | Extractions | SD,L=1 | HD,L=3 | SD,L=3 | SD,L=3,m=3 |
| --- | --- | --- | --- | --- | --- |
| (3,1,[6]) | 10.000.000 | 3.98e-02 | 6.59e-01 | 2.24e-02 | 5.70e-05 |
| (3,1,[7]) | 10.000.000 | 1.73e-02 | 5.93e-01 | 9.43e-03 | 6.00e-06 | | | | 58.51 | 54.26 | 45.74 |
| --- | --- | --- | --- |
| | 47.87 | 27.66 | 0.00 |
| | 51.60 | 36.70 | 13.83 |
| | 65.43 | 61.17 | 48.40 |
| | 64.89 | 64.89 | 47.87 |
| | 71.28 | 70.21 | 59.57 |
| MRE-IPI | 85.11 | 85.11 | 76.60 |
| Extraction<br>Methods | Seqsize=1,000,000 | | |
| α=0.10 | α=0.05 | α=0.01 | |
|... | 0 |
| LM | #succ<br>words | dev | eval | | |
| --- | --- | --- | --- | --- | --- |
| Vit | CN | Vit | CN | | |
| ng4 | - | 24.46 | 24.20 | 24.68 | 24.44 | | | +uni-rnn | - | 22.49 | 22.33 | 22.53 | 22.30 |
| --- | --- | --- | --- | --- | --- |
| +su-rnn | 1<br>3 | 22.32<br>21.97? | 22.13<br>21.77 | 22.20<br>21.70? | 22.09<br>21.53 | | 1 |
| LM | #succ<br>words | dev | eval | | |
| --- | --- | --- | --- | --- | --- |
| Vit | CN | Vit | CN | | |
| ng4 | - | 24.46 | 24.20 | 24.68 | 24.44 | | | LM | #succ<br>words | dev | eval | | |
| --- | --- | --- | --- | --- | --- |
| Vit | CN | Vit | CN | | |
| ng4 | | 25.00 | 24.19 | 25.19 | 24.44 |
| +uni-rnn | | 23.11 | 22.33 | 22.95 | 22.30 |
| +su-rnn | 1<br>3 | 22.92<br>22.67 | 22.12<br>21.77 | 22.77<br>22.40 | 22.11<br>21.53 | | 0 |
| LM | #succ<br>words | dev | eval | | |
| --- | --- | --- | --- | --- | --- |
| Vit | CN | Vit | CN | | |
| ng4 | - | 24.46 | 24.20 | 24.68 | 24.44 | | | +uni-rnn | - | 22.49 | 22.33 | 22.53 | 22.30 |
| --- | --- | --- | --- | --- | --- |
| +su-rnn | 1<br>3 | 22.32<br>21.97? | 22.13<br>21.77 | 22.20<br>21.70? | 22.09<br>21.53 | | 1 |
| LM | #succ<br>words | dev | eval | | |
| --- | --- | --- | --- | --- | --- |
| Vit | CN | Vit | CN | | |
| ng4 | - | 24.46 | 24.20 | 24.68 | 24.44 | | | ng4 | | 25.00 | 24.19 | 25.19 | 24.44 |
| --- | --- | --- | --- | --- | --- |
| +uni-rnn | | 23.11 | 22.33 | 22.95 | 22.30 |
| +su-rnn | 1<br>3 | 22.92<br>22.67 | 22.12<br>21.77 | 22.77<br>22.40 | 22.11<br>21.53 | | 0 |
| Algorithm | nData=5 | | |
| --- | --- | --- | --- |
| recall | precision | F1 | |
| He-Geng | 0.60±0.09 | 1.00±0.00 | 0.7467±0.07 |
| Baseline | 0.9667±0.07 | 0.9286±0.08 | 0.9434±0.04 |
| MIMB | 0.9667±0.07 | 0.9429±0.07 | 0.9510±0.04 |
| | nData=10 | | | | | He-Geng | 0.667±0.08 | 1.00±0.00 | 0.7967±0.06 |
| --- | --- | --- | --- |
| Baseline | 1.00±0.00 | 0.9095±0.11 | 0.9492±0.07 |
| MIMB | 0.95±0.08 | 0.9381±0.08 | 0.9421±0.06 | | 1 |
| Algorithm | nData=5 | | |
| --- | --- | --- | --- |
| recall | precision | F1 | |
| He-Geng | 0.60±0.09 | 1.00±0.00 | 0.7467±0.07 |
| Baseline | 0.9667±0.07 | 0.9286±0.08 | 0.9434±0.04 |
| MIMB | 0.9667±0.07 | 0.9429±0.07 | 0.9510±0.04 |
| | nData=10 | | | | | Algorithm | nData=5 | | |
| --- | --- | --- | --- |
| recall | precision | F1 | |
| He-Geng | 0.66±0.10 | 1.00±0.00 | 0.7917±0.07 |
| Baseline | 1.00±0.00 | 0.8667±0.07 | 0.9273±0.04 |
| MIMB | 0.94±0.10 | 1.00±0.00 | 0.9667±0.05 |
| | nData=10 | | |
| He-Geng | 0.70±0.11 | 0.95±0.16 | 0.7990±0.11 |
| Baseline ... | 0 |
| Algorithm | nData=5 | | |
| --- | --- | --- | --- |
| recall | precision | F1 | |
| He-Geng | 0.60±0.09 | 1.00±0.00 | 0.7467±0.07 |
| Baseline | 0.9667±0.07 | 0.9286±0.08 | 0.9434±0.04 |
| MIMB | 0.9667±0.07 | 0.9429±0.07 | 0.9510±0.04 | | | | nData=10 | | |
| --- | --- | --- | --- |
| He-Geng | 0.667±0.08 | 1.00±0.00 | 0.7967±0.06 |
| Baseline | 1.00±0.00 | 0.9095±0.11 | 0.9492±0.07 |
| MIMB | 0.95±0.08 | 0.9381±0.08 | 0.9421±0.06 | | 1 |
| Algorithm | nData=5 | | |
| --- | --- | --- | --- |
| recall | precision | F1 | |
| He-Geng | 0.60±0.09 | 1.00±0.00 | 0.7467±0.07 |
| Baseline | 0.9667±0.07 | 0.9286±0.08 | 0.9434±0.04 |
| MIMB | 0.9667±0.07 | 0.9429±0.07 | 0.9510±0.04 | | | | nData=10 | | |
| --- | --- | --- | --- |
| He-Geng | 0.70±0.11 | 0.95±0.16 | 0.7990±0.11 |
| Baseline | 1.00±0.00 | 0.8298±0.14 | 0.9008±0.09 |
| MIMB | 0.84±0.08 | 0.96±0.12 | 0.8661±0.08 | | 0 |
| Featur | DB1A | DB2A | DB3A | DB4A |
| --- | --- | --- | --- | --- |
| MCCS | 20.1K | 11.6 | 12.6 | 9.75 |
| MCCo | 13.2 | 10.4 | 12.4 | 5.71 |
| MCCf | 11.8 | 9.21 | 9.78 | 5.25 |
| MCCe | 11.9 | 8.28 | 8.71 | 5.71 |
| MCCco | 12.9 | 10.9 | 11.92 | 5.92 | | | MCCcf | 13.1 | 10.03 | 11.92 | 5.57 |
| --- | --- | --- | --- | --- |
| MCCce | 13.4 | 10.85 | 13.57 | 7.64 | | 1 |
| Featur | DB1A | DB2A | DB3A | DB4A |
| --- | --- | --- | --- | --- |
| MCCS | 20.1K | 11.6 | 12.6 | 9.75 |
| MCCo | 13.2 | 10.4 | 12.4 | 5.71 |
| MCCf | 11.8 | 9.21 | 9.78 | 5.25 |
| MCCe | 11.9 | 8.28 | 8.71 | 5.71 |
| MCCco | 12.9 | 10.9 | 11.92 | 5.92 | | | Featur | DB1A | DB2A | DB3A | DB4A |
| --- | --- | --- | --- | --- |
| MCCS | 6.07K | 5.75 | 4.42 | 3.57 |
| MCCo | 5.21 | 6.38 | 6.00 | 3.75 |
| MCCf | 4.32 | 6.00 | 6.15 | 2.68 |
| MCCe | 4.25 | 6.78 | 6.72 | 3.20 |
| MCCco | 3.85 | 5.35 | 3.78 | 2.38 |
| MCCcf | 4.00 | 5.71 | 5.63 | 2.39 |
| MCCce | 4.24 | 6.46 | ... | 0 |
| Featur | DB1A | DB2A | DB3A | DB4A |
| --- | --- | --- | --- | --- |
| MCCS | 20.1K | 11.6 | 12.6 | 9.75 | | | MCCo | 13.2 | 10.4 | 12.4 | 5.71 |
| --- | --- | --- | --- | --- |
| MCCf | 11.8 | 9.21 | 9.78 | 5.25 |
| MCCe | 11.9 | 8.28 | 8.71 | 5.71 |
| MCCco | 12.9 | 10.9 | 11.92 | 5.92 |
| MCCcf | 13.1 | 10.03 | 11.92 | 5.57 |
| MCCce | 13.4 | 10.85 | 13.57 | 7.64 | | 1 |
| Featur | DB1A | DB2A | DB3A | DB4A |
| --- | --- | --- | --- | --- |
| MCCS | 20.1K | 11.6 | 12.6 | 9.75 | | | MCCe | 4.25 | 6.78 | 6.72 | 3.20 |
| --- | --- | --- | --- | --- |
| MCCco | 3.85 | 5.35 | 3.78 | 2.38 |
| MCCcf | 4.00 | 5.71 | 5.63 | 2.39 |
| MCCce | 4.24 | 6.46 | 6.74 | 3.07 | | 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 | | | 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 |
| Size,QP | Proposedmethod | Methodin |
| --- | --- | --- |
| 64×64,22 | 0.72 | 0.70 |
| 128×128,22 | 0.88 | 0.87 |
| 64×64,32 | 0.95 | 0.72 |
| 128×128,32 | 0.98 | 0.85 | | | 64×64,42 | 0.50 | 0.64 |
| --- | --- | --- |
| 128×128,42 | 0.79 | 0.85 |
| Average | 0.80 | 0.77 | | 1 |
| Size,QP | Proposedmethod | Methodin |
| --- | --- | --- |
| 64×64,22 | 0.72 | 0.70 |
| 128×128,22 | 0.88 | 0.87 |
| 64×64,32 | 0.95 | 0.72 |
| 128×128,32 | 0.98 | 0.85 | | | 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 |
| Size,QP | Proposedmethod | Methodin |
| --- | --- | --- |
| 64×64,22 | 0.72 | 0.70 |
| 128×128,22 | 0.88 | 0.87 |
| 64×64,32 | 0.95 | 0.72 | | | 128×128,32 | 0.98 | 0.85 |
| --- | --- | --- |
| 64×64,42 | 0.50 | 0.64 |
| 128×128,42 | 0.79 | 0.85 |
| Average | 0.80 | 0.77 | | 1 |
| Size,QP | Proposedmethod | Methodin |
| --- | --- | --- |
| 64×64,22 | 0.72 | 0.70 |
| 128×128,22 | 0.88 | 0.87 |
| 64×64,32 | 0.95 | 0.72 | | | 128×128,42 | 0.84 | 0.89 |
| --- | --- | --- |
| Average | 0.85 | 0.84 | | 0 |
| QuantitativeMeasures | PSNR | SAM | ERGAS |
| --- | --- | --- | --- |
| Bicubic | 33.0236 | 0.1248 | 126.0507 | | | NRAM | 33.1197 | 0.1297 | 124.3686 |
| --- | --- | --- | --- |
| SparseRepresentation | 35.7409 | 0.1651 | 117.4637 |
| NuclearNormPenalty | 36.9567 | 0.0843 | 95.0166 |
| MCPPenalty | 37.8732 | 0.0720 | 88.5562 | | 1 |
| QuantitativeMeasures | PSNR | SAM | ERGAS |
| --- | --- | --- | --- |
| Bicubic | 33.0236 | 0.1248 | 126.0507 | | | Measure | Method | σ=0 | σ=4 | σ=6 | σ=8 | σ=12 |
| --- | --- | --- | --- | --- | --- | --- |
| PSNR | Bicubic | 33.08 | 32.99 | 32.75 | 32.50 | 31.88 |
| ScSR | 34.00 | 33.95 | 33.92 | 33.90 | 33.86 | |
| MCcSR | 34.14 | 34.11 | 34.09 | 34.09 | 34.07 | |
| SSIM | Bicubic | 0.745 | 0.731 | 0.698 | 0.672 | 0.619 |
|... | 0 |
| QuantitativeMeasures | PSNR | SAM | ERGAS |
| --- | --- | --- | --- |
| Bicubic | 33.0236 | 0.1248 | 126.0507 |
| NRAM | 33.1197 | 0.1297 | 124.3686 |
| SparseRepresentation | 35.7409 | 0.1651 | 117.4637 | | | NuclearNormPenalty | 36.9567 | 0.0843 | 95.0166 |
| --- | --- | --- | --- |
| MCPPenalty | 37.8732 | 0.0720 | 88.5562 | | 1 |
| QuantitativeMeasures | PSNR | SAM | ERGAS |
| --- | --- | --- | --- |
| Bicubic | 33.0236 | 0.1248 | 126.0507 |
| NRAM | 33.1197 | 0.1297 | 124.3686 |
| SparseRepresentation | 35.7409 | 0.1651 | 117.4637 | | | MCcSR | 34.14 | 34.11 | 34.09 | 34.09 | 34.07 | |
| --- | --- | --- | --- | --- | --- | --- |
| SSIM | Bicubic | 0.745 | 0.731 | 0.698 | 0.672 | 0.619 |
| ScSR | 0.774 | 0.772 | 0.766 | 0.761 | 0.752 | |
| MCcSR | 0.785 | 0.783 | 0.780 | 0.775 | 0.768 | |
| SCIELAB | Bicubic | 2.79E4 | 2.92E4 | 4.40E4 | 5.25E4 | 6... | 0 |
| Method | Sintel | Driving | FlyingThings3D | Monkaa | KITTI2015 | Parameters | Speed |
| --- | --- | --- | --- | --- | --- | --- | --- |
| DispNet | 5.38 | 15.62 | 2.02 | 5.99 | 2.19 | 38.4M | 16.67Hz | | | SGM | 19.62 | 40.19 | 8.70 | 20.16 | 7.21 | - | 0.91Hz |
| --- | --- | --- | --- | --- | --- | --- | --- |
| MC-CNN-fast | 11.94 | 19.58 | 4.09 | 6.71 | - | 0.6M | 1.25Hz |
| DenseMapNet | 4.41 | 6.56 | 5.07 | 4.45 | 2.52 | 0.29M | >30Hz | | 1 |
| Method | Sintel | Driving | FlyingThings3D | Monkaa | KITTI2015 | Parameters | Speed |
| --- | --- | --- | --- | --- | --- | --- | --- |
| DispNet | 5.38 | 15.62 | 2.02 | 5.99 | 2.19 | 38.4M | 16.67Hz | | | Network | nC | Smin | R@50 | R@100 | Model | Speed | Network | nC | Smin | R@50 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| PNet | 1 | 16 | 0.9604 | 0.9712 | 28KB | 25.17FPS | APN24 | 3 | 16 | 0.9920 |
| PNet | 1 | 20 | 0.9557 | 0.9700 | 28KB | 33.75FPS | APN24 | 3 | 20 | 0.9898 |
| PNet |... | 0 |
| Method | Sintel | Driving | FlyingThings3D | Monkaa | KITTI2015 | Parameters | Speed |
| --- | --- | --- | --- | --- | --- | --- | --- |
| DispNet | 5.38 | 15.62 | 2.02 | 5.99 | 2.19 | 38.4M | 16.67Hz | | | SGM | 19.62 | 40.19 | 8.70 | 20.16 | 7.21 | - | 0.91Hz |
| --- | --- | --- | --- | --- | --- | --- | --- |
| MC-CNN-fast | 11.94 | 19.58 | 4.09 | 6.71 | - | 0.6M | 1.25Hz |
| DenseMapNet | 4.41 | 6.56 | 5.07 | 4.45 | 2.52 | 0.29M | >30Hz | | 1 |
| Method | Sintel | Driving | FlyingThings3D | Monkaa | KITTI2015 | Parameters | Speed |
| --- | --- | --- | --- | --- | --- | --- | --- |
| DispNet | 5.38 | 15.62 | 2.02 | 5.99 | 2.19 | 38.4M | 16.67Hz | | | APN24 | 1 | 20 | 0.9860 | 0.9882 | 360KB | 32.63FPS | APN12 | 2 | 20 | 0.9484 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| APN24 | 1 | 24 | 0.9825 | 0.9856 | 360KB | 43.39FPS | APN12 | 2 | 24 | 0.9354 |
| APN24 | 2 | 16 | 0.9907 | 0.9946 | 360KB | 20.82FPS | APN24(S) | 2 | 16 | 0.9760 |
| A... | 0 |
| Agree1 | |
| --- | --- |
| Method | AccuracyF1RecallPrecision | | | Emo-Based<br>PBLGA<br>TFIDF<br>BOW | 0,60230,48960,38140,6833<br>0,49070,01790,00930,2500<br>0,51400,65790,93490,5076<br>0,52090,65440,90700,5118 |
| --- | --- |
| Emo-Based<br>PBLGA<br>TFIDF<br>BOW | 0,60000,50000,39390,6842<br>0,49230,01490,00760,5000<br>0,53850,65120,84850,5283<br>0,54230,64690,82580,5317 |
| Emo-... | 1 |
| Agree1 | |
| --- | --- |
| Method | AccuracyF1RecallPrecision | | | Image | Method | CSr | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| 0.02 | 0.04 | 0.06 | 0.08 | 0.10 | | |
| Barbara | BM3D-CS<br>TVAL3<br>NLR-CS<br>D-AMP<br>Ours | 16.44,0.389<br>21.32,0.588<br>16.79,0.400<br>15.08,0.354<br>26.15,0.812 | 18.03,0.422<br>22.58,0.620<br>18.90,0.433<br>17.76,0.417<br>27.2... | 0 |
| Agree1 | |
| --- | --- |
| Method | AccuracyF1RecallPrecision |
| Emo-Based<br>PBLGA<br>TFIDF<br>BOW | 0,60230,48960,38140,6833<br>0,49070,01790,00930,2500<br>0,51400,65790,93490,5076<br>0,52090,65440,90700,5118 | | | Emo-Based<br>PBLGA<br>TFIDF<br>BOW | 0,60000,50000,39390,6842<br>0,49230,01490,00760,5000<br>0,53850,65120,84850,5283<br>0,54230,64690,82580,5317 |
| --- | --- |
| Emo-Based<br>PBLGA<br>TFIDF<br>BOW | 0,60750,53410,45450,6475<br>0,51250,05800,03030,6667<br>0,50750,63590,86870,5015<br>0,51250,63140,84340,5045 |
| Emo-... | 1 |
| Agree1 | |
| --- | --- |
| Method | AccuracyF1RecallPrecision |
| Emo-Based<br>PBLGA<br>TFIDF<br>BOW | 0,60230,48960,38140,6833<br>0,49070,01790,00930,2500<br>0,51400,65790,93490,5076<br>0,52090,65440,90700,5118 | | | Parrots | BM3D-CS<br>TVAL3<br>NLR-CS<br>D-AMP<br>Ours | 16.62,0.506<br>21.11,0.714<br>17.39,0.550<br>16.89,0.520<br>28.28,0.899 | 19.32,0.613<br>22.90,0.722<br>20.84,0.681<br>19.55,0.619<br>28.88,0.893 | 23.070.693<br>23.47,0.714<br>24.95,0.782<br>22.62,0.684<br>29.22,0.890 | 25.04,0.761<br>24.38,0.770<br>28.18,0.835... | 0 |
| α | U/ScontactsperunittimetoyieldUagents | 0.5-5 |
| --- | --- | --- |
| β | U/Scontactsperunittimetoyieldimmuneagents | 0.5 |
| γ | U/ScontactsperunittimeattransmissionrateγfromStoV | 0.2 | | | µ | V/ScontactsperunittimeattransmissionrateµfromStoU | 0.1 |
| --- | --- | --- |
| ξ | 1/ξtimeunitsanindividualremainsspreader | 1-30 |
| η | 1/ηtimeanindividualremainsviolent | 1-20 |
| κ | ContactratethattransmitsItoU | 0.5 |
| σ | U/UcontactratetransmittingthemtoV | 0.5 | | 1 |
| α | U/ScontactsperunittimetoyieldUagents | 0.5-5 |
| --- | --- | --- |
| β | U/Scontactsperunittimetoyieldimmuneagents | 0.5 |
| γ | U/ScontactsperunittimeattransmissionrateγfromStoV | 0.2 | | | Symbol | Meaning |
| --- | --- |
| n | Numberofpatterns |
| p | Numberofinputs(features)inapattern |
| m | Numberofcolumns |
| q | Numberofproximalsynapsespercolumn |
| φ+ | Permanenceincrementamount |
| φ− | Permanencedecrementamount |
| φσ | Windowofpermanenceinitialization |
| ρs | Proximalsynapseactivationtreshol... | 0 |
| α | U/ScontactsperunittimetoyieldUagents | 0.5-5 |
| --- | --- | --- |
| β | U/Scontactsperunittimetoyieldimmuneagents | 0.5 |
| γ | U/ScontactsperunittimeattransmissionrateγfromStoV | 0.2 |
| µ | V/ScontactsperunittimeattransmissionrateµfromStoU | 0.1 |
| ξ | 1/ξtimeunitsanindividualremainsspreader | 1-30 | | | η | 1/ηtimeanindividualremainsviolent | 1-20 |
| --- | --- | --- |
| κ | ContactratethattransmitsItoU | 0.5 |
| σ | U/UcontactratetransmittingthemtoV | 0.5 | | 1 |
| α | U/ScontactsperunittimetoyieldUagents | 0.5-5 |
| --- | --- | --- |
| β | U/Scontactsperunittimetoyieldimmuneagents | 0.5 |
| γ | U/ScontactsperunittimeattransmissionrateγfromStoV | 0.2 |
| µ | V/ScontactsperunittimeattransmissionrateµfromStoU | 0.1 |
| ξ | 1/ξtimeunitsanindividualremainsspreader | 1-30 | | | m | Numberofcolumns |
| --- | --- |
| q | Numberofproximalsynapsespercolumn |
| φ+ | Permanenceincrementamount |
| φ− | Permanencedecrementamount |
| φσ | Windowofpermanenceinitialization |
| ρs | Proximalsynapseactivationtreshold |
| ρd | Proximaldendritesegmentactivationtreshold |
| ρc | Desiredcolumnactivitylevel ... | 0 |
| Function | Score<br>onQH | Score<br>onQL |
| --- | --- | --- |
| Low1 | -9.08 | -4.03 |
| Low2 | -2.80 | 0.00 | | | SynRules | -13.08 | -12.78 |
| --- | --- | --- |
| SemColl | 24.32 | 3.38 |
| TOTAL | -0.64 | -13.34 | | 1 |
| Function | Score<br>onQH | Score<br>onQL |
| --- | --- | --- |
| Low1 | -9.08 | -4.03 |
| Low2 | -2.80 | 0.00 | | | Function | Score<br>onQH | Score<br>onQL |
| --- | --- | --- |
| Low1 | -9.08 | -4.03 |
| Low2 | -2.80 | 0.00 |
| SynRules | -13.08 | -12.78 |
| SemColl | 24.32 | 3.38 |
| TOTAL | -0.64 | -13.34 | | 0 |
| Function | Score<br>onQH | Score<br>onQL |
| --- | --- | --- |
| Low1 | -9.08 | -4.03 |
| Low2 | -2.80 | 0.00 |
| SynRules | -13.08 | -12.78 | | | SemColl | 24.32 | 3.38 |
| --- | --- | --- |
| TOTAL | -0.64 | -13.34 | | 1 |
| Function | Score<br>onQH | Score<br>onQL |
| --- | --- | --- |
| Low1 | -9.08 | -4.03 |
| Low2 | -2.80 | 0.00 |
| SynRules | -13.08 | -12.78 | | | SemColl | 24.32 | 3.38 |
| --- | --- | --- |
| TOTAL | -0.64 | -13.34 | | 0 |
| AUC | MSE | ACC | F1 |
| --- | --- | --- | --- |
| LinearRegression | | | |
| 0.684 | 0.039 | 0.813 | 0.53 | | | LogisticsRegression | | | |
| --- | --- | --- | --- |
| 0.745 | 0.171 | 0.75 | 0.6 |
| RandomForestRegression | | | |
| 0.701 | 0.035 | 0.82 | 0.56 |
| RandomForestClassifier | | | |
| 0.745 | 0.151 | 0.781 | 0.61 | | 1 |
| AUC | MSE | ACC | F1 |
| --- | --- | --- | --- |
| LinearRegression | | | |
| 0.684 | 0.039 | 0.813 | 0.53 | | | Model | M1,AGMIC | M2,AGMIC |
| --- | --- | --- |
| Task | 1/0,20/2 | 0/1,21/2 |
| PR | 0.9820.51 | 0.80.77 |
| RE | 10.53 | 0.810.87 |
| Acc | 0.9820.61 | 0.720.73 |
| AUC | 0.830.574 | 0.780.67 | | 0 |
| AUC | MSE | ACC | F1 |
| --- | --- | --- | --- |
| LinearRegression | | | |
| 0.684 | 0.039 | 0.813 | 0.53 | | | LogisticsRegression | | | |
| --- | --- | --- | --- |
| 0.745 | 0.171 | 0.75 | 0.6 |
| RandomForestRegression | | | |
| 0.701 | 0.035 | 0.82 | 0.56 |
| RandomForestClassifier | | | |
| 0.745 | 0.151 | 0.781 | 0.61 | | 1 |
| AUC | MSE | ACC | F1 |
| --- | --- | --- | --- |
| LinearRegression | | | |
| 0.684 | 0.039 | 0.813 | 0.53 | | | PR | 0.9820.51 | 0.80.77 |
| --- | --- | --- |
| RE | 10.53 | 0.810.87 |
| Acc | 0.9820.61 | 0.720.73 |
| AUC | 0.830.574 | 0.780.67 | | 0 |
| \|Ω\|<br>mnN | AR-BC-ADMM | P-BC-ADMM | TFOCS | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | | | | | | | |
| 0.01 | 215 | 217.98 | 266 | 271.72 | 400 | 334.08 | 543 | | | 0.02 | 180 | 180.96 | 210 | 217.24 | 400 | 338.10 | 344 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| 0.03 | 165 | 170.66 | 192 | 197.58 | 400 | 336.50 | 307 |
| 0.05 | 146 | 152.56 | 171 | 175.42 | 400 | 338.13 | 268 |
| 0.10 | 127 | 134.35 | 144 | 148.66 | 400 | 339.83 | 226 |
| 0.15 | 118 | 124.43 | 129 | ... | 1 |
| \|Ω\|<br>mnN | AR-BC-ADMM | P-BC-ADMM | TFOCS | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | | | | | | | |
| 0.01 | 215 | 217.98 | 266 | 271.72 | 400 | 334.08 | 543 | | | | m2 | m3 | m4 | m5 | m6 |
| --- | --- | --- | --- | --- | --- |
| Nsw | 9530 | 9530 | 9530 | 9530 | 9530 |
| N | 9159 | 9159 | 9159 | 9159 | 9159 |
| Ksw | 22305 | 43894 | 64161 | 83192 | 101104 |
| K | 14627 | 28494 | 41472 | 53596 | 64840 |
| Lsw | 3.59 | 2.92 | 2.70 | 2.55 | 2.45 |
| L | 6.42 | 4.73 | 4.12 | 3.7... | 0 |
| \|Ω\|<br>mnN | AR-BC-ADMM | P-BC-ADMM | TFOCS | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | | | | | | | |
| 0.01 | 215 | 217.98 | 266 | 271.72 | 400 | 334.08 | 543 |
| 0.02 | 180 | 180.96 | 210 | 217.24 | 400 | 338.10 | 344 |
| 0.03 | 165 | 170.66 | 192 | 197.58 | 400 | 336.50 | 307 |
| ... | | 0.15 | 118 | 124.43 | 129 | 133.76 | 400 | 341.33 | 211 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| 0.25 | 108 | 111.98 | 114 | 116.32 | 400 | 351.30 | 188 | | 1 |
| \|Ω\|<br>mnN | AR-BC-ADMM | P-BC-ADMM | TFOCS | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| | | | | | | | |
| 0.01 | 215 | 217.98 | 266 | 271.72 | 400 | 334.08 | 543 |
| 0.02 | 180 | 180.96 | 210 | 217.24 | 400 | 338.10 | 344 |
| 0.03 | 165 | 170.66 | 192 | 197.58 | 400 | 336.50 | 307 |
| ... | | Ksw | 22305 | 43894 | 64161 | 83192 | 101104 |
| --- | --- | --- | --- | --- | --- |
| K | 14627 | 28494 | 41472 | 53596 | 64840 |
| Lsw | 3.59 | 2.92 | 2.70 | 2.55 | 2.45 |
| L | 6.42 | 4.73 | 4.12 | 3.79 | 3.58 |
| Dsw | 16 | 9 | 7 | 6 | 6 |
| D | 26 | 15 | 11 | 10 | 8 |
| Csw | 0.15 | 0.55 | 0.63 | 0.66 | 0.68 |
|... | 0 |
| Numberofexamples |
| --- |
| 3611 | | | 83270 |
| --- |
| 66685 |
| 4402 | | 1 |
| Numberofexamples |
| --- |
| 3611 | | | NumberofApps | NumberofHLI |
| --- | --- |
| 176 | [1,49) |
| 13 | [49,97) |
| 2 | [97,145) |
| 0 | [145,193) |
| 3 | [193,241) | | 0 |
| Numberofexamples |
| --- |
| 3611 |
| 83270 | | | 66685 |
| --- |
| 4402 | | 1 |
| Numberofexamples |
| --- |
| 3611 |
| 83270 | | | 0 | [145,193) |
| --- | --- |
| 3 | [193,241) | | 0 |
| K | optimalregret | robustrevenue | robustwelfare | solditems | time |
| --- | --- | --- | --- | --- | --- |
| | x=10,x=500,∆=30 | | | | | | | 5<br>10<br>20<br>30<br>40<br>50 | 111.27<br>623.27<br>3116.27<br>7464.82<br>13324.82<br>18785.75 | 1452.45<br>3518.00<br>5687.00<br>6393.45<br>5505.18<br>5282.00 | 133.72<br>96.00<br>72.00<br>57.64<br>19.09<br>11.00 | 4.18<br>7.91<br>12.00<br>13.27<br>11.27<br>10.75 | 11.94<br>17.79<br>287.04<br>7565.10<br>10946.47<b... | 1 |
| K | optimalregret | robustrevenue | robustwelfare | solditems | time |
| --- | --- | --- | --- | --- | --- |
| | x=10,x=500,∆=30 | | | | | | | NumberofNodes | ConvergenceRate | OptimalGossipWeight |
| --- | --- | --- |
| 4 | 0.8 | 0.6 |
| 5 | 0.6 | 0.7 |
| 6 | 0.6 | 0.7 |
| 7 | 0.6 | 0.7 |
| 8 | 0.4 | 0.8 |
| 9 | 0.4 | 0.8 |
| 10 | 0.4 | 0.8 |
| 11 | 0.4 | 0.8 |
| 12 | 0.4 | 0.8 |
| 13 | 0.3034 | 0.8 |
| 14 | 0.2412 | 0.8 |
| 15 | 0.2015 | 0.8 |
| 16 | 0.2 ... | 0 |
| K | optimalregret | robustrevenue | robustwelfare | solditems | time |
| --- | --- | --- | --- | --- | --- |
| | x=10,x=500,∆=30 | | | | |
| 5<br>10<br>20<br>30<br>40<br>50 | 111.27<br>623.27<br>3116.27<br>7464.82<br>13324.82<br>18785.75 | 1452.45<br>3518.00<br>5687.00<br>6393.45<br>5505.18<br>5282.00 | 133.72<b... | | | x=10,x=500,∆=50 | | | | |
| --- | --- | --- | --- | --- | --- |
| 5<br>10<br>20<br>30<br>40<br>50 | 200.09<br>1148.73<br>5024.36<br>10534.55<br>16941.36<br>22709.09 | 1390.00<br>3037.36<br>4012.45<br>3660.55<br>2349.09<br>1876.00 | 84.18<br>116.18<br>50.18<br>15.55<br>9.54<br>0.45 | 3.73<br>6.91<br>8.45<br>7.5... | 1 |
| K | optimalregret | robustrevenue | robustwelfare | solditems | time |
| --- | --- | --- | --- | --- | --- |
| | x=10,x=500,∆=30 | | | | |
| 5<br>10<br>20<br>30<br>40<br>50 | 111.27<br>623.27<br>3116.27<br>7464.82<br>13324.82<br>18785.75 | 1452.45<br>3518.00<br>5687.00<br>6393.45<br>5505.18<br>5282.00 | 133.72<b... | | 19 | 0.2 | 0.9 |
| --- | --- | --- |
| 20 | 0.2 | 0.9 | | 0 |
| ModelandApproach | ABSq |
| --- | --- |
| M2+M5+M10+NETXGB | 0.0368 |
| VGG-PCA+M1+M5+M25+NETLOGXGB | 0.0338 | | | VGG-PCAMLP | 0.0287 |
| --- | --- |
| 3DCNN | 0.0284 | | 1 |
| ModelandApproach | ABSq |
| --- | --- |
| M2+M5+M10+NETXGB | 0.0368 |
| VGG-PCA+M1+M5+M25+NETLOGXGB | 0.0338 | | | Model | PredictionAccuracy |
| --- | --- |
| NIN | 0.8677 |
| VGG | 0.8914 |
| ResNet32 | 0.9181 |
| ResNet44 | 0.9243 |
| ResNet56 | 0.9272 |
| ResNet110 | 0.9399 | | 0 |
| ModelandApproach | ABSq |
| --- | --- |
| M2+M5+M10+NETXGB | 0.0368 |
| VGG-PCA+M1+M5+M25+NETLOGXGB | 0.0338 | | | VGG-PCAMLP | 0.0287 |
| --- | --- |
| 3DCNN | 0.0284 | | 1 |
| ModelandApproach | ABSq |
| --- | --- |
| M2+M5+M10+NETXGB | 0.0368 |
| VGG-PCA+M1+M5+M25+NETLOGXGB | 0.0338 | | | ResNet44 | 0.9243 |
| --- | --- |
| ResNet56 | 0.9272 |
| ResNet110 | 0.9399 | | 0 |
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