premise string | hypothesis string | label int64 |
|---|---|---|
| No. | Type | FamilyName | #ofImg |
| --- | --- | --- | --- |
| 1 | Worm | Allaple.L | 1591 | | | 2 | Worm | Allaple.A | 2949 |
| --- | --- | --- | --- |
| 3 | Worm | Yuner.A | 800 |
| 4 | PWS | lolyda.AA1 | 213 |
| 5 | PWS | lolyda.AA2 | 184 |
| 6 | PWS | lolyda.AA3 | 123 |
| 7 | Trojan | C2Lop.P | 146 |
| 8 | Trojan | C2Lop.gen!G | 200 |
| 9 | Dialer | Instantaccess | 431 |
| 10 | TrojanDownloader | Swizzor.gen!I | 132 |
| 11 | TrojanDownloader | Swizzor.gen!E | 128 |
| 12 | Worm | VB.AT | 408 |
| 13 | Rogue | Fakerean | 381 |
| 14 | Trojan | Alueron.gen!J | 198 |
| 15 | Trojan | Malex.gen!J | 136 |
| 16 | PWS | Lolyda.AT | 159 |
| 17 | Dialer | Adialer.C | 125 |
| 18 | TrojanDownloader | Wintrim.BX | 97 |
| 19 | Dialer | Dialplatform.B | 177 |
| 20 | TrojanDownloader | Dontovo.A | 162 |
| 21 | TrojanDownloader | Obfuscator.AD | 142 |
| 22 | Backdoor | Agent.FYI | 116 |
| 23 | Worm:AutoIT | Autorun.K | 106 |
| 24 | Backdoor | Rbot!gen | 158 |
| 25 | Trojan | Skintrim.N | 80 | | 1 |
| No. | Type | FamilyName | #ofImg |
| --- | --- | --- | --- |
| 1 | Worm | Allaple.L | 1591 | | | Malware<br>family | # | Description |
| --- | --- | --- |
| Avzhan | 3458 | CommercialDDoSbot |
| Darkness | 1878 | CommercialDDoSbot |
| Ddoser | 502 | CommercialDDoSbot |
| jkddos | 333 | ComercialDDoSbot |
| N0ise | 431 | CommericalDDoSbot |
| ShadyRAT | 1287 | targetedgovandcorps |
| DNSCalc | 403 | targetedUSdefensecompanies |
| Lurid | 399 | initiallytargetedNGOs |
| Getkys | 953 | targetsmedicalsector |
| ZeroAccess | 568 | Rootkit,monetizedbyclick-<br>fraud |
| Zeus | 1975 | Banking,targetscredentials | | 0 |
| No. | Type | FamilyName | #ofImg |
| --- | --- | --- | --- |
| 1 | Worm | Allaple.L | 1591 |
| 2 | Worm | Allaple.A | 2949 |
| 3 | Worm | Yuner.A | 800 |
| 4 | PWS | lolyda.AA1 | 213 |
| 5 | PWS | lolyda.AA2 | 184 |
| 6 | PWS | lolyda.AA3 | 123 |
| 7 | Trojan | C2Lop.P | 146 |
| 8 | Trojan | C2Lop.gen!G | 200 |
| 9 | Dialer | Instantaccess | 431 | | | 10 | TrojanDownloader | Swizzor.gen!I | 132 |
| --- | --- | --- | --- |
| 11 | TrojanDownloader | Swizzor.gen!E | 128 |
| 12 | Worm | VB.AT | 408 |
| 13 | Rogue | Fakerean | 381 |
| 14 | Trojan | Alueron.gen!J | 198 |
| 15 | Trojan | Malex.gen!J | 136 |
| 16 | PWS | Lolyda.AT | 159 |
| 17 | Dialer | Adialer.C | 125 |
| 18 | TrojanDownloader | Wintrim.BX | 97 |
| 19 | Dialer | Dialplatform.B | 177 |
| 20 | TrojanDownloader | Dontovo.A | 162 |
| 21 | TrojanDownloader | Obfuscator.AD | 142 |
| 22 | Backdoor | Agent.FYI | 116 |
| 23 | Worm:AutoIT | Autorun.K | 106 |
| 24 | Backdoor | Rbot!gen | 158 |
| 25 | Trojan | Skintrim.N | 80 | | 1 |
| No. | Type | FamilyName | #ofImg |
| --- | --- | --- | --- |
| 1 | Worm | Allaple.L | 1591 |
| 2 | Worm | Allaple.A | 2949 |
| 3 | Worm | Yuner.A | 800 |
| 4 | PWS | lolyda.AA1 | 213 |
| 5 | PWS | lolyda.AA2 | 184 |
| 6 | PWS | lolyda.AA3 | 123 |
| 7 | Trojan | C2Lop.P | 146 |
| 8 | Trojan | C2Lop.gen!G | 200 |
| 9 | Dialer | Instantaccess | 431 | | | N0ise | 431 | CommericalDDoSbot |
| --- | --- | --- |
| ShadyRAT | 1287 | targetedgovandcorps |
| DNSCalc | 403 | targetedUSdefensecompanies |
| Lurid | 399 | initiallytargetedNGOs |
| Getkys | 953 | targetsmedicalsector |
| ZeroAccess | 568 | Rootkit,monetizedbyclick-<br>fraud |
| Zeus | 1975 | Banking,targetscredentials | | 0 |
| Method | Pedestrians | Cyclists | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Easy | Mod | Hard | Easy | Mod | Hard | |
| FasterR-CNN | 78.35 | 65.91 | 61.19 | 71.41 | 62.81 | 55.44 |
| 3DOP | 82.36 | 67.46 | 64.71 | 80.17 | 68.81 | 61.36 |
| IVA | 83.03 | 70.63 | 64.68 | 77.63 | 67.36 | 59.62 | | | GN | 80.73 | 71.55 | 64.82 | - | - | - |
| --- | --- | --- | --- | --- | --- | --- |
| SubCNN | 83.17 | 71.34 | 66.36 | 77.82 | 70.77 | 62.71 |
| SDP+RPN | 79.98 | 70.20 | 64.84 | 81.05 | 73.08 | 64.88 |
| MS-CNN | 83.70 | 73.62 | 68.28 | 82.34 | 74.45 | 64.91 |
| RRC | 84.14 | 75.33 | 70.39 | 84.96 | 76.47 | 65.46 |
| Ours | 87.69 | 79.75 | 74.56 | 86.06 | 78.21 | 69.47 | | 1 |
| Method | Pedestrians | Cyclists | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Easy | Mod | Hard | Easy | Mod | Hard | |
| FasterR-CNN | 78.35 | 65.91 | 61.19 | 71.41 | 62.81 | 55.44 |
| 3DOP | 82.36 | 67.46 | 64.71 | 80.17 | 68.81 | 61.36 |
| IVA | 83.03 | 70.63 | 64.68 | 77.63 | 67.36 | 59.62 | | | Methods | Easy | Moderate | Hard |
| --- | --- | --- | --- |
| Car | | | |
| SelectiveSearch | 58.17 | 42.12 | 37.62 |
| EdgeBoxes | 81.40 | 61.84 | 55.68 |
| RPN | 98.84 | 97.37 | 95.31 |
| Ours | 99.27 | 96.28 | 93.14 |
| Pedestrian | | | |
| SelectiveSearch | 68.95 | 57.65 | 52.57 |
| EdgeBoxes | 86.15 | 71.88 | 65.39 |
| RPN | 98.88 | 91.69 | 88.64 |
| Ours | 99.44 | 93.46 | 91.02 |
| Cyclist | | | |
| SelectiveSearch | 57.05 | 49.59 | 49.44 |
| EdgeBoxes | 56.11 | 46.52 | 45.72 |
| RPN | 96.55 | 91.80 | 89.41 |
| Ours | 99.67 | 93.03 | 91.64 | | 0 |
| Method | Pedestrians | Cyclists | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Easy | Mod | Hard | Easy | Mod | Hard | |
| FasterR-CNN | 78.35 | 65.91 | 61.19 | 71.41 | 62.81 | 55.44 | | | 3DOP | 82.36 | 67.46 | 64.71 | 80.17 | 68.81 | 61.36 |
| --- | --- | --- | --- | --- | --- | --- |
| IVA | 83.03 | 70.63 | 64.68 | 77.63 | 67.36 | 59.62 |
| GN | 80.73 | 71.55 | 64.82 | - | - | - |
| SubCNN | 83.17 | 71.34 | 66.36 | 77.82 | 70.77 | 62.71 |
| SDP+RPN | 79.98 | 70.20 | 64.84 | 81.05 | 73.08 | 64.88 |
| MS-CNN | 83.70 | 73.62 | 68.28 | 82.34 | 74.45 | 64.91 |
| RRC | 84.14 | 75.33 | 70.39 | 84.96 | 76.47 | 65.46 |
| Ours | 87.69 | 79.75 | 74.56 | 86.06 | 78.21 | 69.47 | | 1 |
| Method | Pedestrians | Cyclists | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Easy | Mod | Hard | Easy | Mod | Hard | |
| FasterR-CNN | 78.35 | 65.91 | 61.19 | 71.41 | 62.81 | 55.44 | | | SelectiveSearch | 68.95 | 57.65 | 52.57 |
| --- | --- | --- | --- |
| EdgeBoxes | 86.15 | 71.88 | 65.39 |
| RPN | 98.88 | 91.69 | 88.64 |
| Ours | 99.44 | 93.46 | 91.02 |
| Cyclist | | | |
| SelectiveSearch | 57.05 | 49.59 | 49.44 |
| EdgeBoxes | 56.11 | 46.52 | 45.72 |
| RPN | 96.55 | 91.80 | 89.41 |
| Ours | 99.67 | 93.03 | 91.64 | | 0 |
| instance | sizeoptprfails | sizeoptprfails | sizeoptprfails |
| --- | --- | --- | --- |
| rbg010a<br>rbg016a<br>rbg016b<br>rbg017.2<br>rbg017<br>rbg017a<br>rbg019a<br>rbg019b<br>rbg019c<br>rbg019d<br>rbg020a<br>rbg021.2<br>rbg021.3<br>rbg021.4<br>rbg021.5<br>rbg021.6<br>rbg021.7<br>rbg021.8<br>rbg021.9<br>rbg021<br>rbg027a | 0.81127<br>0.761437<br>0.621454<br>0.38012<br>0.5319112<br>0.640110<br>0.890117<br>0.681383<br>0.5214186<br>0.91025<br>0.78013<br>0.500223<br>0.4815106<br>0.4714152<br>0.4913160<br>0.41128k<br>0.4013518<br>0.391313k<br>0.391313k<br>0.5214186<br>0.440315 | 0.94015<br>0.880241<br>0.720354<br>0.49019<br>0.661570<br>0.720113<br>0.980127<br>0.781385<br>0.6013137<br>0.97016<br>0.84013<br>0.590148<br>0.5514185<br>0.530333<br>0.5502103<br>0.4812233<br>0.490291<br>0.4812518<br>0.4812574<br>0.6013137<br>0.590235 | 0.99017<br>0.930244<br>0.840243<br>0.570114<br>0.790347<br>0.800142<br>10130<br>0.870171<br>0.6812158<br>1016<br>0.89015<br>0.660166<br>0.6203158<br>0.610340<br>0.6102125<br>0.5902110<br>0.590170<br>0.560188<br>0.5601108<br>0.6812158<br>0.660153 |
| average | 0.570.673.051725 | 0.660.382.14114 | 0.740.101.5769 |
| ratio=0.25ratio=0.3ratio=0.35 | | | | | | instance | sizeoptprfails | sizeoptprfails | sizeoptprfails |
| --- | --- | --- | --- |
| rbg010a<br>rbg016a<br>rbg016b<br>rbg017.2<br>rbg017<br>rbg017a<br>rbg019a<br>rbg019b<br>rbg019c<br>rbg019d<br>rbg020a<br>rbg021.2<br>rbg021.3<br>rbg021.4<br>rbg021.5<br>rbg021.6<br>rbg021.7<br>rbg021.8<br>rbg021.9<br>rbg021<br>rbg027a | 1018<br>10149<br>0.970136<br>0.740131<br>0.950258<br>0.9301143<br>10130<br>0.970172<br>0.8202106<br>1016<br>0.99015<br>0.8001185<br>0.7802128<br>0.7402114<br>0.7401193<br>0.7301132<br>0.710171<br>0.710189<br>0.7101115<br>0.8202106<br>0.8301245 | 1018<br>10149<br>0.990138<br>0.840120<br>0.990156<br>0.9701165<br>10130<br>10172<br>0.9201112<br>1016<br>1015<br>0.9101227<br>0.9002142<br>0.880167<br>0.8801172<br>0.8901145<br>0.820178<br>0.830191<br>0.8301121<br>0.9201112<br>0.9001407 | 1018<br>10149<br>10138<br>0.900120<br>10156<br>101236<br>10130<br>10172<br>0.9501119<br>1016<br>1015<br>0.9501240<br>0.9401129<br>0.940170<br>0.9401173<br>0.9501148<br>0.890178<br>0.900195<br>0.9001122<br>0.9501119<br>0.96011k |
| average | 0.8501.2492 | 0.9301.05101 | 0.9601139 | | 1 |
| instance | sizeoptprfails | sizeoptprfails | sizeoptprfails |
| --- | --- | --- | --- |
| rbg010a<br>rbg016a<br>rbg016b<br>rbg017.2<br>rbg017<br>rbg017a<br>rbg019a<br>rbg019b<br>rbg019c<br>rbg019d<br>rbg020a<br>rbg021.2<br>rbg021.3<br>rbg021.4<br>rbg021.5<br>rbg021.6<br>rbg021.7<br>rbg021.8<br>rbg021.9<br>rbg021<br>rbg027a | 0.81127<br>0.761437<br>0.621454<br>0.38012<br>0.5319112<br>0.640110<br>0.890117<br>0.681383<br>0.5214186<br>0.91025<br>0.78013<br>0.500223<br>0.4815106<br>0.4714152<br>0.4913160<br>0.41128k<br>0.4013518<br>0.391313k<br>0.391313k<br>0.5214186<br>0.440315 | 0.94015<br>0.880241<br>0.720354<br>0.49019<br>0.661570<br>0.720113<br>0.980127<br>0.781385<br>0.6013137<br>0.97016<br>0.84013<br>0.590148<br>0.5514185<br>0.530333<br>0.5502103<br>0.4812233<br>0.490291<br>0.4812518<br>0.4812574<br>0.6013137<br>0.590235 | 0.99017<br>0.930244<br>0.840243<br>0.570114<br>0.790347<br>0.800142<br>10130<br>0.870171<br>0.6812158<br>1016<br>0.89015<br>0.660166<br>0.6203158<br>0.610340<br>0.6102125<br>0.5902110<br>0.590170<br>0.560188<br>0.5601108<br>0.6812158<br>0.660153 |
| average | 0.570.673.051725 | 0.660.382.14114 | 0.740.101.5769 |
| ratio=0.25ratio=0.3ratio=0.35 | | | | | | baseline | weakly | weakly<br>cleaned |
| --- | --- | --- |
| 48.3 | 8.5 | 15.9 |
| 77.0<br>77.8<br>78.4<br>78.4 | 62.8<br>62.2<br>65.0<br>65.0 | 64.8<br>61.9<br>63.0<br>62.7 |
| 78.5<br>78.5<br>- | 63.7<br>64.9<br>- | 62.5<br>68.0<br>66.9 |
| 80.1<br>- | 66.8<br>- | 68.9<br>68.5 | | 0 |
| instance | sizeoptprfails | sizeoptprfails | sizeoptprfails |
| --- | --- | --- | --- |
| rbg010a<br>rbg016a<br>rbg016b<br>rbg017.2<br>rbg017<br>rbg017a<br>rbg019a<br>rbg019b<br>rbg019c<br>rbg019d<br>rbg020a<br>rbg021.2<br>rbg021.3<br>rbg021.4<br>rbg021.5<br>rbg021.6<br>rbg021.7<br>rbg021.8<br>rbg021.9<br>rbg021<br>rbg027a | 0.81127<br>0.761437<br>0.621454<br>0.38012<br>0.5319112<br>0.640110<br>0.890117<br>0.681383<br>0.5214186<br>0.91025<br>0.78013<br>0.500223<br>0.4815106<br>0.4714152<br>0.4913160<br>0.41128k<br>0.4013518<br>0.391313k<br>0.391313k<br>0.5214186<br>0.440315 | 0.94015<br>0.880241<br>0.720354<br>0.49019<br>0.661570<br>0.720113<br>0.980127<br>0.781385<br>0.6013137<br>0.97016<br>0.84013<br>0.590148<br>0.5514185<br>0.530333<br>0.5502103<br>0.4812233<br>0.490291<br>0.4812518<br>0.4812574<br>0.6013137<br>0.590235 | 0.99017<br>0.930244<br>0.840243<br>0.570114<br>0.790347<br>0.800142<br>10130<br>0.870171<br>0.6812158<br>1016<br>0.89015<br>0.660166<br>0.6203158<br>0.610340<br>0.6102125<br>0.5902110<br>0.590170<br>0.560188<br>0.5601108<br>0.6812158<br>0.660153 | | | average | 0.570.673.051725 | 0.660.382.14114 | 0.740.101.5769 |
| --- | --- | --- | --- |
| ratio=0.25ratio=0.3ratio=0.35 | | | |
| instance | sizeoptprfails | sizeoptprfails | sizeoptprfails |
| rbg010a<br>rbg016a<br>rbg016b<br>rbg017.2<br>rbg017<br>rbg017a<br>rbg019a<br>rbg019b<br>rbg019c<br>rbg019d<br>rbg020a<br>rbg021.2<br>rbg021.3<br>rbg021.4<br>rbg021.5<br>rbg021.6<br>rbg021.7<br>rbg021.8<br>rbg021.9<br>rbg021<br>rbg027a | 1018<br>10149<br>0.970136<br>0.740131<br>0.950258<br>0.9301143<br>10130<br>0.970172<br>0.8202106<br>1016<br>0.99015<br>0.8001185<br>0.7802128<br>0.7402114<br>0.7401193<br>0.7301132<br>0.710171<br>0.710189<br>0.7101115<br>0.8202106<br>0.8301245 | 1018<br>10149<br>0.990138<br>0.840120<br>0.990156<br>0.9701165<br>10130<br>10172<br>0.9201112<br>1016<br>1015<br>0.9101227<br>0.9002142<br>0.880167<br>0.8801172<br>0.8901145<br>0.820178<br>0.830191<br>0.8301121<br>0.9201112<br>0.9001407 | 1018<br>10149<br>10138<br>0.900120<br>10156<br>101236<br>10130<br>10172<br>0.9501119<br>1016<br>1015<br>0.9501240<br>0.9401129<br>0.940170<br>0.9401173<br>0.9501148<br>0.890178<br>0.900195<br>0.9001122<br>0.9501119<br>0.96011k |
| average | 0.8501.2492 | 0.9301.05101 | 0.9601139 | | 1 |
| instance | sizeoptprfails | sizeoptprfails | sizeoptprfails |
| --- | --- | --- | --- |
| rbg010a<br>rbg016a<br>rbg016b<br>rbg017.2<br>rbg017<br>rbg017a<br>rbg019a<br>rbg019b<br>rbg019c<br>rbg019d<br>rbg020a<br>rbg021.2<br>rbg021.3<br>rbg021.4<br>rbg021.5<br>rbg021.6<br>rbg021.7<br>rbg021.8<br>rbg021.9<br>rbg021<br>rbg027a | 0.81127<br>0.761437<br>0.621454<br>0.38012<br>0.5319112<br>0.640110<br>0.890117<br>0.681383<br>0.5214186<br>0.91025<br>0.78013<br>0.500223<br>0.4815106<br>0.4714152<br>0.4913160<br>0.41128k<br>0.4013518<br>0.391313k<br>0.391313k<br>0.5214186<br>0.440315 | 0.94015<br>0.880241<br>0.720354<br>0.49019<br>0.661570<br>0.720113<br>0.980127<br>0.781385<br>0.6013137<br>0.97016<br>0.84013<br>0.590148<br>0.5514185<br>0.530333<br>0.5502103<br>0.4812233<br>0.490291<br>0.4812518<br>0.4812574<br>0.6013137<br>0.590235 | 0.99017<br>0.930244<br>0.840243<br>0.570114<br>0.790347<br>0.800142<br>10130<br>0.870171<br>0.6812158<br>1016<br>0.89015<br>0.660166<br>0.6203158<br>0.610340<br>0.6102125<br>0.5902110<br>0.590170<br>0.560188<br>0.5601108<br>0.6812158<br>0.660153 | | | 77.0<br>77.8<br>78.4<br>78.4 | 62.8<br>62.2<br>65.0<br>65.0 | 64.8<br>61.9<br>63.0<br>62.7 |
| --- | --- | --- |
| 78.5<br>78.5<br>- | 63.7<br>64.9<br>- | 62.5<br>68.0<br>66.9 |
| 80.1<br>- | 66.8<br>- | 68.9<br>68.5 | | 0 |
| category | model | AP3D | APloc |
| --- | --- | --- | --- |
| easymoderatehard | easymoderatehard | | | | | Car | global-no-im<br>dense<br>final | 55.6839.8533.71<br>74.7761.4251.88<br>77.9263.0053.27 | 72.3555.4247.41<br>47.2128.8726.99<br>49.3429.4226.98 |
| --- | --- | --- | --- |
| Pedestrian | global-no-im<br>dense<br>final | 3.072.583.58<br>31.9626.8222.59<br>33.3628.0423.38 | 3.072.582.14<br>37.0831.7127.04<br>37.9132.3527.35 |
| Cyclist | global-no-im<br>dense<br>final | 4.612.583.58<br>47.2128.8726.99<br>49.3429.4226.98 | 6.933.764.7<br>51.4531.6529.59<br>54.0232.7730.19 | | 1 |
| category | model | AP3D | APloc |
| --- | --- | --- | --- |
| easymoderatehard | easymoderatehard | | | | | Mode | Count | α | (cid:96)(km)0 | (cid:96)(km) | σ |
| --- | --- | --- | --- | --- | --- |
| I.AllModes | 52973 | 2.13 | 29.40 | 9.99 | 1313.79 |
| A.Walk | 14303 | 3.99 | 6.37 | 1.37 | 3.77 |
| B.Bicycle | 5581 | 2.72 | 6.37 | 3.47 | 30.06 |
| C.Auto.Driver | 18484 | 2.29 | 39.90 | 13.06 | 1331.84 |
| D.PublicTrans. | 6944 | 1.97 | 27.98 | 16.34 | 2875.92 |
| Auto.Passenger | 7658 | 2.00 | 24.32 | 17.69 | 2949.11 | | 0 |
| category | model | AP3D | APloc |
| --- | --- | --- | --- |
| easymoderatehard | easymoderatehard | | |
| Car | global-no-im<br>dense<br>final | 55.6839.8533.71<br>74.7761.4251.88<br>77.9263.0053.27 | 72.3555.4247.41<br>47.2128.8726.99<br>49.3429.4226.98 | | | Pedestrian | global-no-im<br>dense<br>final | 3.072.583.58<br>31.9626.8222.59<br>33.3628.0423.38 | 3.072.582.14<br>37.0831.7127.04<br>37.9132.3527.35 |
| --- | --- | --- | --- |
| Cyclist | global-no-im<br>dense<br>final | 4.612.583.58<br>47.2128.8726.99<br>49.3429.4226.98 | 6.933.764.7<br>51.4531.6529.59<br>54.0232.7730.19 | | 1 |
| category | model | AP3D | APloc |
| --- | --- | --- | --- |
| easymoderatehard | easymoderatehard | | |
| Car | global-no-im<br>dense<br>final | 55.6839.8533.71<br>74.7761.4251.88<br>77.9263.0053.27 | 72.3555.4247.41<br>47.2128.8726.99<br>49.3429.4226.98 | | | D.PublicTrans. | 6944 | 1.97 | 27.98 | 16.34 | 2875.92 |
| --- | --- | --- | --- | --- | --- |
| Auto.Passenger | 7658 | 2.00 | 24.32 | 17.69 | 2949.11 | | 0 |
| Filter | ITDCS | MFCS | IGB | GB |
| --- | --- | --- | --- | --- |
| Canfil1 | 0.78 | 2.44 | 0.89 | 55.73 |
| Canfil2 | 0.47 | 2.17 | 0.66 | 49.33 |
| Canfil3 | 1.01 | 8.10 | 3.16 | • |
| Canfil4 | 0.99 | 2.24 | 0.62 | 26.10 |
| Canfil5 | 0.58 | 2.80 | 3.00 | • |
| Canfil6 | 0.58 | 2.14 | 2.81 | • |
| Canfil7 | 0.16 | 0.35 | 0.27 | 16.64 | | | Canfil8 | 0.26 | 5.81 | 0.34 | 33.35 |
| --- | --- | --- | --- | --- |
| Canfil9 | 6.83 | 75.62 | 8.54 | • |
| Canfil10 | 0.70 | 3.04 | 4.87 | • | | 1 |
| Filter | ITDCS | MFCS | IGB | GB |
| --- | --- | --- | --- | --- |
| Canfil1 | 0.78 | 2.44 | 0.89 | 55.73 |
| Canfil2 | 0.47 | 2.17 | 0.66 | 49.33 |
| Canfil3 | 1.01 | 8.10 | 3.16 | • |
| Canfil4 | 0.99 | 2.24 | 0.62 | 26.10 |
| Canfil5 | 0.58 | 2.80 | 3.00 | • |
| Canfil6 | 0.58 | 2.14 | 2.81 | • |
| Canfil7 | 0.16 | 0.35 | 0.27 | 16.64 | | | K | PCA | NMF | SNMF | SSC | LRR | MFC10 | MFC20 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| 2 | 0.51 | 0.80 | 1.00 | 0.98 | 1.00 | 1.00 | 1.00 |
| 4 | 0.35 | 0.59 | 0.63 | 0.88 | 0.86 | 0.85 | 0.89 |
| 6 | 0.30 | 0.72 | 0.57 | 0.84 | 0.82 | 0.84 | 0.86 |
| 8 | 0.20 | 0.37 | 0.48 | 0.76 | 0.74 | 0.69 | 0.76 |
| 10 | 0.23 | 0.45 | 0.41 | 0.74 | 0.71 | 0.68 | 0.75 |
| 12 | 0.22 | 0.37 | 0.41 | 0.67 | 0.70 | 0.70 | 0.70 |
| 14 | 0.18 | 0.36 | 0.39 | 0.64 | 0.68 | 0.77 | 0.72 |
| 16 | 0.18 | 0.37 | 0.39 | 0.63 | 0.67 | 0.72 | 0.73 |
| 18 | 0.15 | 0.35 | 0.35 | 0.63 | 0.68 | 0.74 | 0.74 |
| 20 | 0.15 | 0.37 | 0.37 | 0.60 | 0.66 | 0.72 | 0.72 |
| Avg. | 0.25 | 0.47 | 0.49 | 0.74 | 0.75 | 0.77 | 0.79 | | 0 |
| Filter | ITDCS | MFCS | IGB | GB |
| --- | --- | --- | --- | --- |
| Canfil1 | 0.78 | 2.44 | 0.89 | 55.73 |
| Canfil2 | 0.47 | 2.17 | 0.66 | 49.33 |
| Canfil3 | 1.01 | 8.10 | 3.16 | • | | | Canfil4 | 0.99 | 2.24 | 0.62 | 26.10 |
| --- | --- | --- | --- | --- |
| Canfil5 | 0.58 | 2.80 | 3.00 | • |
| Canfil6 | 0.58 | 2.14 | 2.81 | • |
| Canfil7 | 0.16 | 0.35 | 0.27 | 16.64 |
| Canfil8 | 0.26 | 5.81 | 0.34 | 33.35 |
| Canfil9 | 6.83 | 75.62 | 8.54 | • |
| Canfil10 | 0.70 | 3.04 | 4.87 | • | | 1 |
| Filter | ITDCS | MFCS | IGB | GB |
| --- | --- | --- | --- | --- |
| Canfil1 | 0.78 | 2.44 | 0.89 | 55.73 |
| Canfil2 | 0.47 | 2.17 | 0.66 | 49.33 |
| Canfil3 | 1.01 | 8.10 | 3.16 | • | | | 16 | 0.18 | 0.37 | 0.39 | 0.63 | 0.67 | 0.72 | 0.73 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| 18 | 0.15 | 0.35 | 0.35 | 0.63 | 0.68 | 0.74 | 0.74 |
| 20 | 0.15 | 0.37 | 0.37 | 0.60 | 0.66 | 0.72 | 0.72 |
| Avg. | 0.25 | 0.47 | 0.49 | 0.74 | 0.75 | 0.77 | 0.79 | | 0 |
| CNSMeasure | Mean<br>AUC | MeanAUC<br>Change | MaxAUC<br>Increase | #Classes<br>Increase | #Classes<br>withAUC<br>increase>0.05 | MaxAUC<br>Decrease |
| --- | --- | --- | --- | --- | --- | --- |
| Original.cont | 0.7878 | | | | | |
| FS.cont | 0.726 | -0.0618 | 0.0807 | 11 | 3 | 0.2357 |
| TOM.cont | 0.7664 | -0.0213 | 0.116 | 28 | 8 | 0.1663 |
| HC.cont | 0.8119 | 0.0242 | 0.1976 | 68 | 21 | 0.0822 |
| Original.binary | 0.7741 | -0.0137 | 0.0929 | 47 | 5 | 0.2482 |
| Jaccard | 0.7285 | -0.0592 | 0.0869 | 11 | 3 | 0.235 |
| Pvalue | 0.5597 | -0.2281 | 0.0509 | 2 | 1 | 0.4996 |
| FS.binary | 0.6204 | -0.1673 | 0.0738 | 3 | 1 | 0.4229 | | | TOM.binary | 0.7735 | -0.0143 | 0.2327 | 44 | 6 | 0.1913 |
| --- | --- | --- | --- | --- | --- | --- |
| HC.binary | 0.7833 | -0.0044 | 0.1311 | 44 | 14 | 0.1357 | | 1 |
| CNSMeasure | Mean<br>AUC | MeanAUC<br>Change | MaxAUC<br>Increase | #Classes<br>Increase | #Classes<br>withAUC<br>increase>0.05 | MaxAUC<br>Decrease |
| --- | --- | --- | --- | --- | --- | --- |
| Original.cont | 0.7878 | | | | | |
| FS.cont | 0.726 | -0.0618 | 0.0807 | 11 | 3 | 0.2357 |
| TOM.cont | 0.7664 | -0.0213 | 0.116 | 28 | 8 | 0.1663 |
| HC.cont | 0.8119 | 0.0242 | 0.1976 | 68 | 21 | 0.0822 |
| Original.binary | 0.7741 | -0.0137 | 0.0929 | 47 | 5 | 0.2482 |
| Jaccard | 0.7285 | -0.0592 | 0.0869 | 11 | 3 | 0.235 |
| Pvalue | 0.5597 | -0.2281 | 0.0509 | 2 | 1 | 0.4996 |
| FS.binary | 0.6204 | -0.1673 | 0.0738 | 3 | 1 | 0.4229 | | | CNSMeasure | Mean<br>AUC | MeanAUC<br>Change | MaxAUC<br>Increase | #Classes<br>Increase | #Classes<br>withAUC<br>increase>0.05 | MaxAUC<br>Decrease |
| --- | --- | --- | --- | --- | --- | --- |
| Original.cont | 0.7944 | | | | | |
| FS.cont | 0.7941 | −0.0003 | 0.0846 | 83 | 3 | 0.0662 |
| TOM.cont | 0.8034 | 0.0089 | 0.0636 | 105 | 2 | 0.1782 |
| HC.cont | 0.8266 | 0.0281 | 0.2244 | 109 | 34 | 0.1199 |
| Original.binary | 0.7847 | −0.0097 | 0.0502 | 48 | 1 | 0.2222 |
| Jaccard | 0.7291 | −0.0653 | 0.2738 | 28 | 18 | 0.4759 |
| Pvalue | 0.6374 | −0.1570 | 0.1740 | 5 | 3 | 0.5691 |
| FS.binary | 0.6750 | −0.1195 | 0.1740 | 5 | 1 | 0.4945 |
| TOM.binary | 0.7365 | −0.0579 | 0.3332 | 23 | 9 | 0.3227 |
| HC.binary | 0.7578 | −0.0367 | 0.2989 | 35 | 25 | 0.3773 | | 0 |
| CNSMeasure | Mean<br>AUC | MeanAUC<br>Change | MaxAUC<br>Increase | #Classes<br>Increase | #Classes<br>withAUC<br>increase>0.05 | MaxAUC<br>Decrease |
| --- | --- | --- | --- | --- | --- | --- |
| Original.cont | 0.7878 | | | | | |
| FS.cont | 0.726 | -0.0618 | 0.0807 | 11 | 3 | 0.2357 |
| TOM.cont | 0.7664 | -0.0213 | 0.116 | 28 | 8 | 0.1663 |
| HC.cont | 0.8119 | 0.0242 | 0.1976 | 68 | 21 | 0.0822 |
| Original.binary | 0.7741 | -0.0137 | 0.0929 | 47 | 5 | 0.2482 |
| Jaccard | 0.7285 | -0.0592 | 0.0869 | 11 | 3 | 0.235 |
| Pvalue | 0.5597 | -0.2281 | 0.0509 | 2 | 1 | 0.4996 | | | FS.binary | 0.6204 | -0.1673 | 0.0738 | 3 | 1 | 0.4229 |
| --- | --- | --- | --- | --- | --- | --- |
| TOM.binary | 0.7735 | -0.0143 | 0.2327 | 44 | 6 | 0.1913 |
| HC.binary | 0.7833 | -0.0044 | 0.1311 | 44 | 14 | 0.1357 | | 1 |
| CNSMeasure | Mean<br>AUC | MeanAUC<br>Change | MaxAUC<br>Increase | #Classes<br>Increase | #Classes<br>withAUC<br>increase>0.05 | MaxAUC<br>Decrease |
| --- | --- | --- | --- | --- | --- | --- |
| Original.cont | 0.7878 | | | | | |
| FS.cont | 0.726 | -0.0618 | 0.0807 | 11 | 3 | 0.2357 |
| TOM.cont | 0.7664 | -0.0213 | 0.116 | 28 | 8 | 0.1663 |
| HC.cont | 0.8119 | 0.0242 | 0.1976 | 68 | 21 | 0.0822 |
| Original.binary | 0.7741 | -0.0137 | 0.0929 | 47 | 5 | 0.2482 |
| Jaccard | 0.7285 | -0.0592 | 0.0869 | 11 | 3 | 0.235 |
| Pvalue | 0.5597 | -0.2281 | 0.0509 | 2 | 1 | 0.4996 | | | Pvalue | 0.6374 | −0.1570 | 0.1740 | 5 | 3 | 0.5691 |
| --- | --- | --- | --- | --- | --- | --- |
| FS.binary | 0.6750 | −0.1195 | 0.1740 | 5 | 1 | 0.4945 |
| TOM.binary | 0.7365 | −0.0579 | 0.3332 | 23 | 9 | 0.3227 |
| HC.binary | 0.7578 | −0.0367 | 0.2989 | 35 | 25 | 0.3773 | | 0 |
| NumberofVertices |
| --- |
| 5M |
| 41M |
| 34M |
| 134M |
| 101M | | | 0.5M |
| --- |
| 1M |
| 2M | | 1 |
| NumberofVertices |
| --- |
| 5M |
| 41M |
| 34M |
| 134M |
| 101M | | | No.ofbuses | 14-bus | 57-bus | 118-bus |
| --- | --- | --- | --- |
| No.oflines | 20 | 80 | 186 |
| Totalno.ofmeasurements | 20 | 80 | 180 |
| No.ofinjectmeasurements | 8 | 30 | 70 |
| No.offlowmeasurements | 12 | 50 | 110 |
| No.ofunmeasuredlines | 1 | 2 | 7 | | 0 |
| NumberofVertices |
| --- |
| 5M |
| 41M |
| 34M |
| 134M | | | 101M |
| --- |
| 0.5M |
| 1M |
| 2M | | 1 |
| NumberofVertices |
| --- |
| 5M |
| 41M |
| 34M |
| 134M | | | Totalno.ofmeasurements | 20 | 80 | 180 |
| --- | --- | --- | --- |
| No.ofinjectmeasurements | 8 | 30 | 70 |
| No.offlowmeasurements | 12 | 50 | 110 |
| No.ofunmeasuredlines | 1 | 2 | 7 | | 0 |
| STPair | ClassificationModel | Accuracy |
| --- | --- | --- |
| (big,City) | DT | 0.925 |
| (experienced,Athlete) | RBF-SVM | 0.80 | | | (cute,Animal) | RBF-SVM/RF/DT | 0.685 |
| --- | --- | --- |
| (old,Building) | RBF-SVM | 0.89 |
| (popular,Film) | DT | 0.79 | | 1 |
| STPair | ClassificationModel | Accuracy |
| --- | --- | --- |
| (big,City) | DT | 0.925 |
| (experienced,Athlete) | RBF-SVM | 0.80 | | | Model | Sensitivity | Specificity | Accuracy |
| --- | --- | --- | --- |
| SVM(best) | 0.8259 | 0.8324 | 0.8291 |
| LR(best) | 0.7121 | 0.6879 | 0.6991 |
| RF(best) | 0.6901 | 0.6850 | 0.6861 |
| RNNs(best) | 0.9886 | 0.9836 | 0.9763 | | 0 |
| STPair | ClassificationModel | Accuracy |
| --- | --- | --- |
| (big,City) | DT | 0.925 |
| (experienced,Athlete) | RBF-SVM | 0.80 |
| (cute,Animal) | RBF-SVM/RF/DT | 0.685 | | | (old,Building) | RBF-SVM | 0.89 |
| --- | --- | --- |
| (popular,Film) | DT | 0.79 | | 1 |
| STPair | ClassificationModel | Accuracy |
| --- | --- | --- |
| (big,City) | DT | 0.925 |
| (experienced,Athlete) | RBF-SVM | 0.80 |
| (cute,Animal) | RBF-SVM/RF/DT | 0.685 | | | LR(best) | 0.7121 | 0.6879 | 0.6991 |
| --- | --- | --- | --- |
| RF(best) | 0.6901 | 0.6850 | 0.6861 |
| RNNs(best) | 0.9886 | 0.9836 | 0.9763 | | 0 |
| HigherBetter | | | |
| --- | --- | --- | --- |
| Pct.<1.25 | Pct.<1.25 | Pct.<1.25 | MeanAbsoluteError |
| 80.55 | 94.65 | 98.26 | 0.399 | | | 79.88 | 94.45 | 98.15 | 0.411 |
| --- | --- | --- | --- |
| 78.70 | 94.06 | 98.13 | 0.419 |
| 78.72 | 94.13 | 98.08 | 0.423 |
| 80.17 | 94.74 | 98.27 | 0.401 |
| 79.26 | 94.19 | 98.07 | 0.422 | | 1 |
| HigherBetter | | | |
| --- | --- | --- | --- |
| Pct.<1.25 | Pct.<1.25 | Pct.<1.25 | MeanAbsoluteError |
| 80.55 | 94.65 | 98.26 | 0.399 | | | HigherBetter | | | |
| --- | --- | --- | --- |
| Pct.<1.25 | Pct.<1.25 | Pct.<1.25 | MeanAbsoluteError |
| 80.55 | 94.65 | 98.26 | 0.399 |
| 80.39 | 94.67 | 98.31 | 0.400 |
| 79.88 | 94.45 | 98.15 | 0.411 |
| 79.69 | 94.28 | 98.09 | 0.411 | | 0 |
| HigherBetter | | | |
| --- | --- | --- | --- |
| Pct.<1.25 | Pct.<1.25 | Pct.<1.25 | MeanAbsoluteError |
| 80.55 | 94.65 | 98.26 | 0.399 |
| 79.88 | 94.45 | 98.15 | 0.411 |
| 78.70 | 94.06 | 98.13 | 0.419 | | | 78.72 | 94.13 | 98.08 | 0.423 |
| --- | --- | --- | --- |
| 80.17 | 94.74 | 98.27 | 0.401 |
| 79.26 | 94.19 | 98.07 | 0.422 | | 1 |
| HigherBetter | | | |
| --- | --- | --- | --- |
| Pct.<1.25 | Pct.<1.25 | Pct.<1.25 | MeanAbsoluteError |
| 80.55 | 94.65 | 98.26 | 0.399 |
| 79.88 | 94.45 | 98.15 | 0.411 |
| 78.70 | 94.06 | 98.13 | 0.419 | | | 80.55 | 94.65 | 98.26 | 0.399 |
| --- | --- | --- | --- |
| 80.39 | 94.67 | 98.31 | 0.400 |
| 79.88 | 94.45 | 98.15 | 0.411 |
| 79.69 | 94.28 | 98.09 | 0.411 | | 0 |
| | noFBsPCAdenoising | FBsPCAdenoising |
| --- | --- | --- |
| RFA/K-means | 0.09 | 0.48 | | | MSA/MRA | 0.87 | 0.95 |
| --- | --- | --- |
| EMAN2 | 0.45 | 0.76 |
| Xmipp | 0.68 | 0.96 | | 1 |
| | noFBsPCAdenoising | FBsPCAdenoising |
| --- | --- | --- |
| RFA/K-means | 0.09 | 0.48 | | | | RFA/K-means | MSA/MRA | Relion | EMAN2 | Xmipp | ASPIRE |
| --- | --- | --- | --- | --- | --- | --- |
| SNR=1/50 | 0.45 | 0.97 | 0.79 | 0.74 | 0.83 | 1.00 |
| SNR=1/100 | 0.09 | 0.87 | 0.70 | 0.45 | 0.68 | 0.99 |
| SNR=1/150 | 0.07 | 0.67 | 0.52 | 0.13 | 0.48 | 0.90 |
| Timing(hrs) | 1.5 | 7.5 | 16 | 12 | 42 | 0.5 | | 0 |
| | noFBsPCAdenoising | FBsPCAdenoising |
| --- | --- | --- |
| RFA/K-means | 0.09 | 0.48 |
| MSA/MRA | 0.87 | 0.95 | | | EMAN2 | 0.45 | 0.76 |
| --- | --- | --- |
| Xmipp | 0.68 | 0.96 | | 1 |
| | noFBsPCAdenoising | FBsPCAdenoising |
| --- | --- | --- |
| RFA/K-means | 0.09 | 0.48 |
| MSA/MRA | 0.87 | 0.95 | | | SNR=1/100 | 0.09 | 0.87 | 0.70 | 0.45 | 0.68 | 0.99 |
| --- | --- | --- | --- | --- | --- | --- |
| SNR=1/150 | 0.07 | 0.67 | 0.52 | 0.13 | 0.48 | 0.90 |
| Timing(hrs) | 1.5 | 7.5 | 16 | 12 | 42 | 0.5 | | 0 |
| Dataset | Type | #Nodes | #Edges |
| --- | --- | --- | --- |
| DBLP-2011 | undirected | 1.0M | 6.7M |
| Pokec | directed | 1.6M | 30.6M |
| LiveJournal | undirected | 4.8M | 69M | | | Orkut | undirected | 3.1M | 117M |
| --- | --- | --- | --- |
| Twitter-2010 | directed | 42M | 1.5B |
| UK-2007-05 | directed | 106M | 3.7B | | 1 |
| Dataset | Type | #Nodes | #Edges |
| --- | --- | --- | --- |
| DBLP-2011 | undirected | 1.0M | 6.7M |
| Pokec | directed | 1.6M | 30.6M |
| LiveJournal | undirected | 4.8M | 69M | | | Dataset | Type | #Nodes | #Edges |
| --- | --- | --- | --- |
| Pokec | directed | 1.6M | 30.6M |
| LiveJournal | undirected | 4.8M | 69M |
| Orkut | undirected | 3.1M | 117M |
| Twitter-2010 | directed | 42M | 1.5B | | 0 |
| Dataset | Type | #Nodes | #Edges |
| --- | --- | --- | --- |
| DBLP-2011 | undirected | 1.0M | 6.7M |
| Pokec | directed | 1.6M | 30.6M |
| LiveJournal | undirected | 4.8M | 69M | | | Orkut | undirected | 3.1M | 117M |
| --- | --- | --- | --- |
| Twitter-2010 | directed | 42M | 1.5B |
| UK-2007-05 | directed | 106M | 3.7B | | 1 |
| Dataset | Type | #Nodes | #Edges |
| --- | --- | --- | --- |
| DBLP-2011 | undirected | 1.0M | 6.7M |
| Pokec | directed | 1.6M | 30.6M |
| LiveJournal | undirected | 4.8M | 69M | | | LiveJournal | undirected | 4.8M | 69M |
| --- | --- | --- | --- |
| Orkut | undirected | 3.1M | 117M |
| Twitter-2010 | directed | 42M | 1.5B | | 0 |
| | CIFAR-10 | CIFAR-100 | ImageNet32 |
| --- | --- | --- | --- |
| Student | 7.46 | 28.52 | 48.2 | | | Teacher | 4.19 | 20.62 | 38.41 |
| --- | --- | --- | --- |
| KD(T=1)<br>KD(T=2)<br>KD(T=5)<br>KD(T=10) | 7.27<br>7.3<br>7.02<br>6.94 | 28.62<br>28.33<br>27.06<br>27.07 | 49.37<br>49.48<br>49.63<br>51.12 |
| Ours | 6.09 | 25.75 | 47.39 | | 1 |
| | CIFAR-10 | CIFAR-100 | ImageNet32 |
| --- | --- | --- | --- |
| Student | 7.46 | 28.52 | 48.2 | | | | σ | 10 | 20 | 30 | 40 | 50 | 60 | 70 | 80 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Dataset | Method | | | | | | | | |
| TID2008 | K-SVD<br>SURE-GMM<br>BM3D<br>NL-Bayes<br>Ours | 34.74<br>34.79<br>35.17<br>35.06<br>35.11 | 30.87<br>31.22<br>31.46<br>31.51<br>31.43 | 28.97<br>29.23<br>29.28<br>29.31<br>29.26 | 27.89<br>27.91<br>28.02<br>28.04<br>28.07 | 26.04<br>26.53<br>26.66<br>26.67<br>26.74 | 24.92<br>24.89<br>25.39<br>25.43<br>25.38 | 24.45<br>24.78<br>25.14<br>25.11<br>25.19 | 23.80<br>23.81<br>24.66<br>24.51<br>24.71 |
| BSDS500 | K-SVD<br>SURE-GMM<br>BM3D<br>NL-Bayes<br>Ours | 34.24<br>34.22<br>34.72<br>34.69<br>34.71 | 30.69<br>31.01<br>31.19<br>31.09<br>31.11 | 28.66<br>29.02<br>29.11<br>29.09<br>29.06 | 27.69<br>27.68<br>27.51<br>27.53<br>27.85 | 25.93<br>26.23<br>26.56<br>26.48<br>26.61 | 25.10<br>25.22<br>25.68<br>25.66<br>25.64 | 24.22<br>24.56<br>24.92<br>24.79<br>24.94 | 23.46<br>23.58<br>24.39<br>24.41<br>24.47 |
| | | | | | | | | | |
| TID2008 | K-SVD<br>SURE-GMM<br>BM3D<br>NL-Bayes<br>Ours | 0.947<br>0.944<br>0.968<br>0.962<br>0.958 | 0.930<br>0.935<br>0.938<br>0.934<br>0.933 | 0.900<br>0.904<br>0.912<br>0.916<br>0.912 | 0.861<br>0.868<br>0.874<br>0.875<br>0.877 | 0.841<br>0.848<br>0.856<br>0.860<br>0.862 | 0.817<br>0.818<br>0.828<br>0.827<br>0.829 | 0.798<br>0.807<br>0.816<br>0.818<br>0.816 | 0.775<br>0.787<br>0.800<br>0.794<br>0.802 |
| BSDS500 | K-SVD<br>SURE-GMM<br>BM3D<br>NL-Bayes<br>Ours | 0.938<br>0.939<br>0.961<br>0.953<br>0.956 | 0.925<br>0.923<br>0.931<br>0.926<br>0.929 | 0.897<br>0.899<br>0.907<br>0.908<br>0.910 | 0.856<br>0.859<br>0.867<br>0.866<br>0.866 | 0.830<br>0.833<br>0.848<br>0.849<br>0.851 | 0.822<br>0.827<br>0.835<br>0.834<br>0.836 | 0.790<br>0.793<br>0.806<br>0.810<br>0.811 | 0.766<br>0.774<br>0.792<br>0.793<br>0.798 | | 0 |
| | CIFAR-10 | CIFAR-100 | ImageNet32 |
| --- | --- | --- | --- |
| Student | 7.46 | 28.52 | 48.2 |
| Teacher | 4.19 | 20.62 | 38.41 | | | KD(T=1)<br>KD(T=2)<br>KD(T=5)<br>KD(T=10) | 7.27<br>7.3<br>7.02<br>6.94 | 28.62<br>28.33<br>27.06<br>27.07 | 49.37<br>49.48<br>49.63<br>51.12 |
| --- | --- | --- | --- |
| Ours | 6.09 | 25.75 | 47.39 | | 1 |
| | CIFAR-10 | CIFAR-100 | ImageNet32 |
| --- | --- | --- | --- |
| Student | 7.46 | 28.52 | 48.2 |
| Teacher | 4.19 | 20.62 | 38.41 | | | BSDS500 | K-SVD<br>SURE-GMM<br>BM3D<br>NL-Bayes<br>Ours | 34.24<br>34.22<br>34.72<br>34.69<br>34.71 | 30.69<br>31.01<br>31.19<br>31.09<br>31.11 | 28.66<br>29.02<br>29.11<br>29.09<br>29.06 | 27.69<br>27.68<br>27.51<br>27.53<br>27.85 | 25.93<br>26.23<br>26.56<br>26.48<br>26.61 | 25.10<br>25.22<br>25.68<br>25.66<br>25.64 | 24.22<br>24.56<br>24.92<br>24.79<br>24.94 | 23.46<br>23.58<br>24.39<br>24.41<br>24.47 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | | | | | | | | | |
| TID2008 | K-SVD<br>SURE-GMM<br>BM3D<br>NL-Bayes<br>Ours | 0.947<br>0.944<br>0.968<br>0.962<br>0.958 | 0.930<br>0.935<br>0.938<br>0.934<br>0.933 | 0.900<br>0.904<br>0.912<br>0.916<br>0.912 | 0.861<br>0.868<br>0.874<br>0.875<br>0.877 | 0.841<br>0.848<br>0.856<br>0.860<br>0.862 | 0.817<br>0.818<br>0.828<br>0.827<br>0.829 | 0.798<br>0.807<br>0.816<br>0.818<br>0.816 | 0.775<br>0.787<br>0.800<br>0.794<br>0.802 |
| BSDS500 | K-SVD<br>SURE-GMM<br>BM3D<br>NL-Bayes<br>Ours | 0.938<br>0.939<br>0.961<br>0.953<br>0.956 | 0.925<br>0.923<br>0.931<br>0.926<br>0.929 | 0.897<br>0.899<br>0.907<br>0.908<br>0.910 | 0.856<br>0.859<br>0.867<br>0.866<br>0.866 | 0.830<br>0.833<br>0.848<br>0.849<br>0.851 | 0.822<br>0.827<br>0.835<br>0.834<br>0.836 | 0.790<br>0.793<br>0.806<br>0.810<br>0.811 | 0.766<br>0.774<br>0.792<br>0.793<br>0.798 | | 0 |
| 1 | 3 |
| --- | --- |
| 2 | 5 |
| 3 | 10 |
| 4 | 27 |
| 5 | 119 | | | 6 | 1113 |
| --- | --- |
| 7 | 29375 |
| 8 | 2730166 | | 1 |
| 1 | 3 |
| --- | --- |
| 2 | 5 |
| 3 | 10 |
| 4 | 27 |
| 5 | 119 | | | 1 | 2 | 3 | 4 | 5 | 4 | 5 | 6 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| 9 | 8 | 9 | 10 | 11 | 12 | 13 | 14 |
| 17 | 16 | 17 | 15 | 16 | 17 | 18 | 19 |
| 20 | 21 | 22 | 23 | 24 | 25 | 24 | 25 |
| 28 | 29 | 28 | 29 | 30 | 31 | 32 | 1 | | 0 |
| 1 | 3 |
| --- | --- |
| 2 | 5 |
| 3 | 10 | | | 4 | 27 |
| --- | --- |
| 5 | 119 |
| 6 | 1113 |
| 7 | 29375 |
| 8 | 2730166 | | 1 |
| 1 | 3 |
| --- | --- |
| 2 | 5 |
| 3 | 10 | | | 17 | 16 | 17 | 15 | 16 | 17 | 18 | 19 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| 20 | 21 | 22 | 23 | 24 | 25 | 24 | 25 |
| 28 | 29 | 28 | 29 | 30 | 31 | 32 | 1 | | 0 |
| AverageErrorinKeyframe | | |
| --- | --- | --- |
| ClassName | Number | Position |
| BaseballPitch | ±1.73 | ±0.455 |
| Basket.Dunk | ±1.64 | ±0.640 |
| Billiards | ±2.18 | ±1.300 |
| CleanandJerk | ±2.27 | ±1.202 |
| CliffDiving | ±2.45 | ±0.627 |
| CricketBowl. | ±2.45 | ±1.14 |
| CricketShot | ±1.27 | ±0.828 |
| Diving | ±2.00 | ±0.907 |
| FrisbeeCatch | ±1.73 | ±0.546 |
| GolfSwing | ±2.45 | ±0.752 |
| Hamm.Throw | ±1.73 | ±1.223 |
| HighJump | ±1.73 | ±0.434 |
| JavelinThrow | ±2.45 | ±0.555 |
| LongJump | ±2.27 | ±0.611 |
| PoleVault | ±2.64 | ±1.139 |
| Shotput | ±2.00 | ±0.564 |
| SoccerPenalty | ±2.09 | ±0.712 | | | TennisSwing | ±1.64 | ±0.554 |
| --- | --- | --- |
| ThrowDiscus | ±2.09 | ±0.642 |
| Volley.Spike | ±1.54 | ±0.633 |
| Averageaccuracy | ±2.02 | ±0.773 | | 1 |
| AverageErrorinKeyframe | | |
| --- | --- | --- |
| ClassName | Number | Position |
| BaseballPitch | ±1.73 | ±0.455 |
| Basket.Dunk | ±1.64 | ±0.640 |
| Billiards | ±2.18 | ±1.300 |
| CleanandJerk | ±2.27 | ±1.202 |
| CliffDiving | ±2.45 | ±0.627 |
| CricketBowl. | ±2.45 | ±1.14 |
| CricketShot | ±1.27 | ±0.828 |
| Diving | ±2.00 | ±0.907 |
| FrisbeeCatch | ±1.73 | ±0.546 |
| GolfSwing | ±2.45 | ±0.752 |
| Hamm.Throw | ±1.73 | ±1.223 |
| HighJump | ±1.73 | ±0.434 |
| JavelinThrow | ±2.45 | ±0.555 |
| LongJump | ±2.27 | ±0.611 |
| PoleVault | ±2.64 | ±1.139 |
| Shotput | ±2.00 | ±0.564 |
| SoccerPenalty | ±2.09 | ±0.712 | | | Action | Bloometal. | LRBM |
| --- | --- | --- |
| Fighting | 70.46 | 97.09 |
| Golf | 83.37 | 81.82 |
| Tennis | 56.44 | 84.38 |
| Bowling | 80.78 | 61.54 |
| FPS | 53.57 | 95.52 |
| Driving | 84.24 | 100.00 |
| Misc | 78.21 | 95.24 |
| Avg. | 72.44 | 87.94 | | 0 |
| AverageErrorinKeyframe | | |
| --- | --- | --- |
| ClassName | Number | Position |
| BaseballPitch | ±1.73 | ±0.455 |
| Basket.Dunk | ±1.64 | ±0.640 | | | Billiards | ±2.18 | ±1.300 |
| --- | --- | --- |
| CleanandJerk | ±2.27 | ±1.202 |
| CliffDiving | ±2.45 | ±0.627 |
| CricketBowl. | ±2.45 | ±1.14 |
| CricketShot | ±1.27 | ±0.828 |
| Diving | ±2.00 | ±0.907 |
| FrisbeeCatch | ±1.73 | ±0.546 |
| GolfSwing | ±2.45 | ±0.752 |
| Hamm.Throw | ±1.73 | ±1.223 |
| HighJump | ±1.73 | ±0.434 |
| JavelinThrow | ±2.45 | ±0.555 |
| LongJump | ±2.27 | ±0.611 |
| PoleVault | ±2.64 | ±1.139 |
| Shotput | ±2.00 | ±0.564 |
| SoccerPenalty | ±2.09 | ±0.712 |
| TennisSwing | ±1.64 | ±0.554 |
| ThrowDiscus | ±2.09 | ±0.642 |
| Volley.Spike | ±1.54 | ±0.633 |
| Averageaccuracy | ±2.02 | ±0.773 | | 1 |
| AverageErrorinKeyframe | | |
| --- | --- | --- |
| ClassName | Number | Position |
| BaseballPitch | ±1.73 | ±0.455 |
| Basket.Dunk | ±1.64 | ±0.640 | | | Bowling | 80.78 | 61.54 |
| --- | --- | --- |
| FPS | 53.57 | 95.52 |
| Driving | 84.24 | 100.00 |
| Misc | 78.21 | 95.24 |
| Avg. | 72.44 | 87.94 | | 0 |
| | ExtractedURLsFilteredURLs<br>(HTMLassetsandself-linkingURLsremoved) |
| --- | --- |
| China | 33,082,2172,098,264 |
| Indonesia | 12,580,357835,395 |
| Iran | 15,381,8731,868,852 | | | Turkey | 19,250,931913,213 |
| --- | --- |
| Totals: | 80,295,3785,715,724 | | 1 |
| | ExtractedURLsFilteredURLs<br>(HTMLassetsandself-linkingURLsremoved) |
| --- | --- |
| China | 33,082,2172,098,264 |
| Indonesia | 12,580,357835,395 |
| Iran | 15,381,8731,868,852 | | | | Counts |
| --- | --- |
| UniqueURLsCrawled | 1,113,653 |
| UniqueDomainsCrawled | 329,575 |
| UniqueFilteredURLs | 115,337 |
| UniquePoisoneddomains | 1355 |
| FilteredURLs/1000URLscrawled | 103.57 |
| Poisoneddomains/1000domainscrawled | 4.11 | | 0 |
| | ExtractedURLsFilteredURLs<br>(HTMLassetsandself-linkingURLsremoved) |
| --- | --- |
| China | 33,082,2172,098,264 |
| Indonesia | 12,580,357835,395 |
| Iran | 15,381,8731,868,852 | | | Turkey | 19,250,931913,213 |
| --- | --- |
| Totals: | 80,295,3785,715,724 | | 1 |
| | ExtractedURLsFilteredURLs<br>(HTMLassetsandself-linkingURLsremoved) |
| --- | --- |
| China | 33,082,2172,098,264 |
| Indonesia | 12,580,357835,395 |
| Iran | 15,381,8731,868,852 | | | FilteredURLs/1000URLscrawled | 103.57 |
| --- | --- |
| Poisoneddomains/1000domainscrawled | 4.11 | | 0 |
| | Relation | Text |
| --- | --- | --- |
| Path#1 | mother | Rebeccagavebirthtotwinsons,EsauandJacob,... | | | Path#2 | haschild | ...Isaac’smarriagetoRebecca,bywhomhehastwosons,Esauandjacob,... |
| --- | --- | --- |
| Test | spouse | ...IsaacandRebeccaandthefemaleandmaleevilspirits... |
| Path#1 | sharesborderwith | ...inSomalia,...soldiersandmarinesstationedinneighboringDjibouti... |
| Path#2 | sharesborderwith | ...EthiopiahavehadtheeffectofmakingneighboringDjibouti... |
| Test | sharesborderwith | Thenextday,Ethiopiastruck,itsmilitarypushingdeepintoSomalia... | | 1 |
| | Relation | Text |
| --- | --- | --- |
| Path#1 | mother | Rebeccagavebirthtotwinsons,EsauandJacob,... | | | 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 |
| | Relation | Text |
| --- | --- | --- |
| Path#1 | mother | Rebeccagavebirthtotwinsons,EsauandJacob,... |
| Path#2 | haschild | ...Isaac’smarriagetoRebecca,bywhomhehastwosons,Esauandjacob,... |
| Test | spouse | ...IsaacandRebeccaandthefemaleandmaleevilspirits... |
| Path#1 | sharesborderwith | ...inSomalia,...soldiersandmarinesstationedinneighboringDjibouti... | | | Path#2 | sharesborderwith | ...EthiopiahavehadtheeffectofmakingneighboringDjibouti... |
| --- | --- | --- |
| Test | sharesborderwith | Thenextday,Ethiopiastruck,itsmilitarypushingdeepintoSomalia... | | 1 |
| | Relation | Text |
| --- | --- | --- |
| Path#1 | mother | Rebeccagavebirthtotwinsons,EsauandJacob,... |
| Path#2 | haschild | ...Isaac’smarriagetoRebecca,bywhomhehastwosons,Esauandjacob,... |
| Test | spouse | ...IsaacandRebeccaandthefemaleandmaleevilspirits... |
| Path#1 | sharesborderwith | ...inSomalia,...soldiersandmarinesstationedinneighboringDjibouti... | | | Gobot,Gbot | 58 | VS,INService | 17 |
| --- | --- | --- | --- |
| Horst,CMQ | 48 | Zhelatin,ASH | 53 |
| Hupigon,ARR | 33 | Zlob,Puper | 64 | | 0 |
| FineTuningLevel | F16⊕F19featureaccuracy | F22featureaccuracy |
| --- | --- | --- |
| F22=9<br>F22=500 | 65.46<br>69.36 | 66.01<br>62.56 | | | F22=1000 | 69.36 | 62.56 |
| --- | --- | --- |
| F22=2000 | 60.34 | 58.79 |
| †<br>F22=1000 | 72.20 | 58.52 | | 1 |
| FineTuningLevel | F16⊕F19featureaccuracy | F22featureaccuracy |
| --- | --- | --- |
| F22=9<br>F22=500 | 65.46<br>69.36 | 66.01<br>62.56 | | | Fine-tunelevel | F16⊕F19FeatureVector | F19FeatureVector | F22FeatureVector | | | |
| --- | --- | --- | --- | --- | --- | --- |
| MeanLength | Mean | Length | Mean | Length | | |
| F19=2048<br>F19=4096 | 64.46<br>70.71 | 6144<br>8192 | 65.34<br>70.79 | 2048<br>4096 | 63.83<br>70.58 | 1000<br>1000 |
| F19=8192<br>F19=6144<br>F19=5120 | 70.00<br>72.30<br>70.21 | 12288<br>10240<br>9216 | 70.16<br>72.22<br>69.95 | 8192<br>6144<br>5120 | 67.98<br>72.30<br>68.19 | 1000<br>1000<br>1000 |
| F19=7168 | 69.29 | 11264 | 69.16 | 71.68 | 70.42 | 1000 | | 0 |
| FineTuningLevel | F16⊕F19featureaccuracy | F22featureaccuracy |
| --- | --- | --- |
| F22=9<br>F22=500 | 65.46<br>69.36 | 66.01<br>62.56 |
| F22=1000 | 69.36 | 62.56 | | | F22=2000 | 60.34 | 58.79 |
| --- | --- | --- |
| †<br>F22=1000 | 72.20 | 58.52 | | 1 |
| FineTuningLevel | F16⊕F19featureaccuracy | F22featureaccuracy |
| --- | --- | --- |
| F22=9<br>F22=500 | 65.46<br>69.36 | 66.01<br>62.56 |
| F22=1000 | 69.36 | 62.56 | | | F19=2048<br>F19=4096 | 64.46<br>70.71 | 6144<br>8192 | 65.34<br>70.79 | 2048<br>4096 | 63.83<br>70.58 | 1000<br>1000 |
| --- | --- | --- | --- | --- | --- | --- |
| F19=8192<br>F19=6144<br>F19=5120 | 70.00<br>72.30<br>70.21 | 12288<br>10240<br>9216 | 70.16<br>72.22<br>69.95 | 8192<br>6144<br>5120 | 67.98<br>72.30<br>68.19 | 1000<br>1000<br>1000 |
| F19=7168 | 69.29 | 11264 | 69.16 | 71.68 | 70.42 | 1000 | | 0 |
| N | Listofreferences |
| --- | --- |
| 0 | “0”,“no”,“zero” | | | 1 | “1”,“a”,“one” |
| --- | --- |
| 2 | “2”,“two”,“acoupleof” |
| 3 | “3”,“three” |
| 4 | “4”,“four” |
| 5 | “5”,“five” |
| 6 | “6”,“six” |
| 7 | “7”,“seven” |
| 8 | “8”,“eight” |
| 9 | “9”,“nine” |
| 10 | “10”,“ten” |
| 11 | “11”,“eleven” |
| 12 | “12”,“twelve” |
| 13 | “13”,“thirteen” |
| 14 | “14”,“fourteen” |
| 15 | “15”,“fifteen” |
| 16 | “16”,“sixteen” | | 1 |
| N | Listofreferences |
| --- | --- |
| 0 | “0”,“no”,“zero” | | | | WordCounts | | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| | Original | Reproduction | | | | |
| Lexicons | Positive | Negative | Positive | PositiveLowered | Negative | NegativeLowered |
| MPQA | 2289 | 4114 | 2298 | 2298 | 4148 | 4148 |
| HL | 2003 | 4780 | 2003 | 2003 | 4780 | 4780 |
| NRC | 2231 | 3243 | 2231 | 2231 | 3243 | 3243 |
| MPQA&HL | 2706 | 5069 | 2725 | 2725 | 5080 | 5076 |
| Allthree | 3940 | 6490 | 4016 | 4016 | 6530 | 6526 | | 0 |
| N | Listofreferences |
| --- | --- |
| 0 | “0”,“no”,“zero” |
| 1 | “1”,“a”,“one” | | | 2 | “2”,“two”,“acoupleof” |
| --- | --- |
| 3 | “3”,“three” |
| 4 | “4”,“four” |
| 5 | “5”,“five” |
| 6 | “6”,“six” |
| 7 | “7”,“seven” |
| 8 | “8”,“eight” |
| 9 | “9”,“nine” |
| 10 | “10”,“ten” |
| 11 | “11”,“eleven” |
| 12 | “12”,“twelve” |
| 13 | “13”,“thirteen” |
| 14 | “14”,“fourteen” |
| 15 | “15”,“fifteen” |
| 16 | “16”,“sixteen” | | 1 |
| N | Listofreferences |
| --- | --- |
| 0 | “0”,“no”,“zero” |
| 1 | “1”,“a”,“one” | | | HL | 2003 | 4780 | 2003 | 2003 | 4780 | 4780 |
| --- | --- | --- | --- | --- | --- | --- |
| NRC | 2231 | 3243 | 2231 | 2231 | 3243 | 3243 |
| MPQA&HL | 2706 | 5069 | 2725 | 2725 | 5080 | 5076 |
| Allthree | 3940 | 6490 | 4016 | 4016 | 6530 | 6526 | | 0 |
| Reference/System | PR | (P+R)/2F |
| --- | --- | --- |
| AverageIndividualParser<br>BestIndividualParser | 87.6187.83<br>89.6189.73 | 87.7287.72<br>89.6789.67 | | | ParserSwitchingOracle<br>MaximumPrecisionOracle | 93.7893.87<br>100.0095.91 | 93.8293.82<br>97.9597.91 |
| --- | --- | --- |
| SimilaritySwitching<br>BayesSwitching | 90.0490.81<br>90.7890.70 | 90.4390.43<br>90.7490.74 |
| ConstituentVoting<br>Na¨ıveBayes | 92.4290.10<br>92.4290.10 | 91.2691.25<br>91.2691.25 | | 1 |
| Reference/System | PR | (P+R)/2F |
| --- | --- | --- |
| AverageIndividualParser<br>BestIndividualParser | 87.6187.83<br>89.6189.73 | 87.7287.72<br>89.6789.67 | | | Reference/System | PR | (P+R)/2F |
| --- | --- | --- |
| AverageIndividualParser<br>BestIndividualParser | 84.5580.91<br>89.6189.73 | 82.7382.69<br>89.6789.67 |
| ParserSwitchingOracle<br>MaximumPrecisionOracle | 93.9293.88<br>100.0096.66 | 93.9093.90<br>98.3398.30 |
| SimilaritySwitching<br>BayesSwitching | 89.9090.89<br>90.9490.70 | 90.4090.39<br>90.8290.82 |
| ConstituentVoting<br>Na¨ıveBayes | 89.7891.80<br>92.4290.10 | 90.7990.78<br>91.2691.25 | | 0 |
| Reference/System | PR | (P+R)/2F |
| --- | --- | --- |
| AverageIndividualParser<br>BestIndividualParser | 87.6187.83<br>89.6189.73 | 87.7287.72<br>89.6789.67 | | | ParserSwitchingOracle<br>MaximumPrecisionOracle | 93.7893.87<br>100.0095.91 | 93.8293.82<br>97.9597.91 |
| --- | --- | --- |
| SimilaritySwitching<br>BayesSwitching | 90.0490.81<br>90.7890.70 | 90.4390.43<br>90.7490.74 |
| ConstituentVoting<br>Na¨ıveBayes | 92.4290.10<br>92.4290.10 | 91.2691.25<br>91.2691.25 | | 1 |
| Reference/System | PR | (P+R)/2F |
| --- | --- | --- |
| AverageIndividualParser<br>BestIndividualParser | 87.6187.83<br>89.6189.73 | 87.7287.72<br>89.6789.67 | | | SimilaritySwitching<br>BayesSwitching | 89.9090.89<br>90.9490.70 | 90.4090.39<br>90.8290.82 |
| --- | --- | --- |
| ConstituentVoting<br>Na¨ıveBayes | 89.7891.80<br>92.4290.10 | 90.7990.78<br>91.2691.25 | | 0 |
| Binary-to-Binary | Binary-to-Stream | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| InputLevels/<br>StreamLength | Array<br>Multiplier | | | SISM | SCSM | | | AISM |
| 8 | 408 | 318 | 226 | 198 | 306 | 510 | 370 | 376 |
| 16 | 688 | 430 | 314 | 262 | 394 | 670 | 506 | 1272 |
| 32 | 1040 | 550 | 414 | 326 | 482 | 838 | 654 | 4600 |
| 64 | 1464 | 678 | 526 | 390 | 570 | 1014 | 814 | 17400 | | | 128 | 1960 | 814 | 650 | 454 | 658 | 1198 | 986 | 67576 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 256 | 2528 | 958 | 786 | 518 | 746 | 1390 | 1170 | 266232 | | 1 |
| Binary-to-Binary | Binary-to-Stream | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| InputLevels/<br>StreamLength | Array<br>Multiplier | | | SISM | SCSM | | | AISM |
| 8 | 408 | 318 | 226 | 198 | 306 | 510 | 370 | 376 |
| 16 | 688 | 430 | 314 | 262 | 394 | 670 | 506 | 1272 |
| 32 | 1040 | 550 | 414 | 326 | 482 | 838 | 654 | 4600 |
| 64 | 1464 | 678 | 526 | 390 | 570 | 1014 | 814 | 17400 | | | n | n-k | m | q | d | t | r’ | r | GVR | Singleton | pk(bits) | sign(bits) | LP | Dual | DS | DA |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 16 | 8 | 18 | 2 | 2 | 2 | 4 | 6 | 5 | 8 | 57600 | 8640 | 130 | 1096 | 400 | 776 |
| 16 | 8 | 18 | 2 | 2 | 2 | 4 | 6 | 5 | 8 | 11520 | 1728 | 110 | 233 | 80 | 168 |
| 16 | 8 | 18 | 2 | 2 | 2 | 4 | 6 | 5 | 8 | 23040 | 3456 | 120 | 448 | 160 | 320 |
| 20 | 10 | 24 | 2 | 2 | 3 | 5 | 8 | 6 | 10 | 24960 | 3008 | 190 | 370 | 104 | 226 |
| 27 | 9 | 20 | 2 | 3 | 2 | 3 | 5 | 4 | 7 | 23328 | 1470 | 170 | 187 | 120 | 129 |
| 48 | 12 | 40 | 2 | 4 | 5 | 3 | 8 | 6 | 10 | 78720 | 2976 | ¿600 | 340 | 164 | 114 |
| 50 | 10 | 42 | 2 | 5 | 5(2) | 2 | 7 | 5 | 9 | 70560 | 2800 | ¿600 | 240 | 180 | 104 | | 0 |
| Binary-to-Binary | Binary-to-Stream | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| InputLevels/<br>StreamLength | Array<br>Multiplier | | | SISM | SCSM | | | AISM |
| 8 | 408 | 318 | 226 | 198 | 306 | 510 | 370 | 376 |
| 16 | 688 | 430 | 314 | 262 | 394 | 670 | 506 | 1272 |
| 32 | 1040 | 550 | 414 | 326 | 482 | 838 | 654 | 4600 |
| 64 | 1464 | 678 | 526 | 390 | 570 | 1014 | 814 | 17400 | | | 128 | 1960 | 814 | 650 | 454 | 658 | 1198 | 986 | 67576 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 256 | 2528 | 958 | 786 | 518 | 746 | 1390 | 1170 | 266232 | | 1 |
| Binary-to-Binary | Binary-to-Stream | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| InputLevels/<br>StreamLength | Array<br>Multiplier | | | SISM | SCSM | | | AISM |
| 8 | 408 | 318 | 226 | 198 | 306 | 510 | 370 | 376 |
| 16 | 688 | 430 | 314 | 262 | 394 | 670 | 506 | 1272 |
| 32 | 1040 | 550 | 414 | 326 | 482 | 838 | 654 | 4600 |
| 64 | 1464 | 678 | 526 | 390 | 570 | 1014 | 814 | 17400 | | | 20 | 10 | 24 | 2 | 2 | 3 | 5 | 8 | 6 | 10 | 24960 | 3008 | 190 | 370 | 104 | 226 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 27 | 9 | 20 | 2 | 3 | 2 | 3 | 5 | 4 | 7 | 23328 | 1470 | 170 | 187 | 120 | 129 |
| 48 | 12 | 40 | 2 | 4 | 5 | 3 | 8 | 6 | 10 | 78720 | 2976 | ¿600 | 340 | 164 | 114 |
| 50 | 10 | 42 | 2 | 5 | 5(2) | 2 | 7 | 5 | 9 | 70560 | 2800 | ¿600 | 240 | 180 | 104 | | 0 |
| Dataset | Gnutella | Amazon | RoadNet-CA |
| --- | --- | --- | --- |
| #Nodes | 6K | 262K | 2.0M |
| #Edges | 21K | 1.2M | 2.8M |
| Averagedegree | 6.6 | 9.4 | 2.8 | | | LargestComponentsize | 6299 | 262K | 2.0M |
| --- | --- | --- | --- |
| Diameter | 9 | 32 | 849 | | 1 |
| Dataset | Gnutella | Amazon | RoadNet-CA |
| --- | --- | --- | --- |
| #Nodes | 6K | 262K | 2.0M |
| #Edges | 21K | 1.2M | 2.8M |
| Averagedegree | 6.6 | 9.4 | 2.8 | | | Dataset | Type | #Nodes | #Edges |
| --- | --- | --- | --- |
| DBLP-2011 | undirected | 1.0M | 6.7M |
| Pokec | directed | 1.6M | 30.6M |
| LiveJournal | undirected | 4.8M | 69M |
| Orkut | undirected | 3.1M | 117M |
| Twitter-2010 | directed | 42M | 1.5B |
| UK-2007-05 | directed | 106M | 3.7B | | 0 |
| Dataset | Gnutella | Amazon | RoadNet-CA |
| --- | --- | --- | --- |
| #Nodes | 6K | 262K | 2.0M |
| #Edges | 21K | 1.2M | 2.8M | | | Averagedegree | 6.6 | 9.4 | 2.8 |
| --- | --- | --- | --- |
| LargestComponentsize | 6299 | 262K | 2.0M |
| Diameter | 9 | 32 | 849 | | 1 |
| Dataset | Gnutella | Amazon | RoadNet-CA |
| --- | --- | --- | --- |
| #Nodes | 6K | 262K | 2.0M |
| #Edges | 21K | 1.2M | 2.8M | | | Orkut | undirected | 3.1M | 117M |
| --- | --- | --- | --- |
| Twitter-2010 | directed | 42M | 1.5B |
| UK-2007-05 | directed | 106M | 3.7B | | 0 |
| Correlation | Gender | Ethnicity | | |
| --- | --- | --- | --- | --- |
| Dimension | Female | Asian | Caucasian | Afro-American |
| Agreeableness | -0.023 | -0.002 | 0.061** | -0.068** | | | Conscientiousness | 0.081** | 0.018 | 0.056** | -0.074** |
| --- | --- | --- | --- | --- |
| Extroversion | 0.207** | 0.039* | 0.039* | -0.068** |
| Neuroticism | 0.054* | -0.002 | 0.047* | -0.053** |
| Openness | 0.169** | 0.010 | 0.083** | -0.100** |
| Interview | 0.069** | 0.015 | 0.052* | -0.068** | | 1 |
| Correlation | Gender | Ethnicity | | |
| --- | --- | --- | --- | --- |
| Dimension | Female | Asian | Caucasian | Afro-American |
| Agreeableness | -0.023 | -0.002 | 0.061** | -0.068** | | | Dataset | Label | P | R | F1 | | | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| M1 | M2 | M3 | M4 | M1 | M2 | M3 | M4 | M1 | M2 | M3 | M4 | | |
| F+ | bully | 0.93 | 0.91 | 0.91 | 0.90 | 0.90 | 0.85 | 0.81 | 0.91 | 0.91 | 0.88 | 0.86 | 0.91 |
| T+ | racism<br>sexism | 0.93<br>0.92 | 0.91<br>0.84 | 0.92<br>0.88 | 0.90<br>0.88 | 0.94<br>0.92 | 0.80<br>0.93 | 0.95<br>0.94 | 0.96<br>0.92 | 0.93<br>0.92 | 0.85<br>0.88 | 0.93<br>0.92 | 0.93<br>0.90 |
| W+ | Attack | 0.92 | 0.70 | 0.90 | 0.87 | 0.83 | 0.54 | 0.81 | 0.86 | 0.88 | 0.61 | 0.85 | 0.87 | | 0 |
| Correlation | Gender | Ethnicity | | |
| --- | --- | --- | --- | --- |
| Dimension | Female | Asian | Caucasian | Afro-American | | | Agreeableness | -0.023 | -0.002 | 0.061** | -0.068** |
| --- | --- | --- | --- | --- |
| Conscientiousness | 0.081** | 0.018 | 0.056** | -0.074** |
| Extroversion | 0.207** | 0.039* | 0.039* | -0.068** |
| Neuroticism | 0.054* | -0.002 | 0.047* | -0.053** |
| Openness | 0.169** | 0.010 | 0.083** | -0.100** |
| Interview | 0.069** | 0.015 | 0.052* | -0.068** | | 1 |
| Correlation | Gender | Ethnicity | | |
| --- | --- | --- | --- | --- |
| Dimension | Female | Asian | Caucasian | Afro-American | | | F+ | bully | 0.93 | 0.91 | 0.91 | 0.90 | 0.90 | 0.85 | 0.81 | 0.91 | 0.91 | 0.88 | 0.86 | 0.91 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| T+ | racism<br>sexism | 0.93<br>0.92 | 0.91<br>0.84 | 0.92<br>0.88 | 0.90<br>0.88 | 0.94<br>0.92 | 0.80<br>0.93 | 0.95<br>0.94 | 0.96<br>0.92 | 0.93<br>0.92 | 0.85<br>0.88 | 0.93<br>0.92 | 0.93<br>0.90 |
| W+ | Attack | 0.92 | 0.70 | 0.90 | 0.87 | 0.83 | 0.54 | 0.81 | 0.86 | 0.88 | 0.61 | 0.85 | 0.87 | | 0 |
| Model | InceptionScore |
| --- | --- |
| (a)Upperbound | 4.44±1.91 |
| (b)ImprovedWGAN | 1.42±0.13 |
| (c)ConditionalGAN | 2.21±0.38 |
| (d)+SpectralNorm | 2.45±0.48 | | | (e)+HingeLoss | 2.49±0.51 |
| --- | --- |
| (f)+ProjectionDiscriminator | 2.61±0.41 |
| (g)+AuxiliaryClassifier | 2.83±0.53 | | 1 |
| Model | InceptionScore |
| --- | --- |
| (a)Upperbound | 4.44±1.91 |
| (b)ImprovedWGAN | 1.42±0.13 |
| (c)ConditionalGAN | 2.21±0.38 |
| (d)+SpectralNorm | 2.45±0.48 | | | Method | Inceptionscore |
| --- | --- |
| 3DShapeNets | 4.126±0.193 |
| 3D-GAN | 8.658±0.450 |
| 3DVAE | 11.015±0.420 |
| 3DDescriptorNet(ours) | 11.772±0.418 | | 0 |
| Model | InceptionScore |
| --- | --- |
| (a)Upperbound | 4.44±1.91 |
| (b)ImprovedWGAN | 1.42±0.13 |
| (c)ConditionalGAN | 2.21±0.38 |
| (d)+SpectralNorm | 2.45±0.48 |
| (e)+HingeLoss | 2.49±0.51 | | | (f)+ProjectionDiscriminator | 2.61±0.41 |
| --- | --- |
| (g)+AuxiliaryClassifier | 2.83±0.53 | | 1 |
| Model | InceptionScore |
| --- | --- |
| (a)Upperbound | 4.44±1.91 |
| (b)ImprovedWGAN | 1.42±0.13 |
| (c)ConditionalGAN | 2.21±0.38 |
| (d)+SpectralNorm | 2.45±0.48 |
| (e)+HingeLoss | 2.49±0.51 | | | 3DVAE | 11.015±0.420 |
| --- | --- |
| 3DDescriptorNet(ours) | 11.772±0.418 | | 0 |
| Set | Files | Words | Characters | Writers |
| --- | --- | --- | --- | --- |
| 1 | 5037 | 7670 | 40500 | 56 | | | 2 | 5090 | 7851 | 41515 | 37 |
| --- | --- | --- | --- | --- |
| 3 | 5031 | 7730 | 40544 | 39 |
| 4 | 4417 | 6671 | 35253 | 41 | | 1 |
| Set | Files | Words | Characters | Writers |
| --- | --- | --- | --- | --- |
| 1 | 5037 | 7670 | 40500 | 56 | | | Set | Files | Words | Characters | Writers |
| --- | --- | --- | --- | --- |
| 1 | 5037 | 7670 | 40500 | 56 |
| 2 | 5090 | 7851 | 41515 | 37 |
| 3 | 5031 | 7730 | 40544 | 39 |
| 4 | 4417 | 6671 | 35253 | 41 | | 0 |
| Set | Files | Words | Characters | Writers |
| --- | --- | --- | --- | --- |
| 1 | 5037 | 7670 | 40500 | 56 | | | 2 | 5090 | 7851 | 41515 | 37 |
| --- | --- | --- | --- | --- |
| 3 | 5031 | 7730 | 40544 | 39 |
| 4 | 4417 | 6671 | 35253 | 41 | | 1 |
| Set | Files | Words | Characters | Writers |
| --- | --- | --- | --- | --- |
| 1 | 5037 | 7670 | 40500 | 56 | | | 3 | 5031 | 7730 | 40544 | 39 |
| --- | --- | --- | --- | --- |
| 4 | 4417 | 6671 | 35253 | 41 | | 0 |
| Comparedmethods | Accuracy | Cross-viewintra-classdistance |
| --- | --- | --- |
| Alexnet | 52.4 | 5<br>1.27×10 | | | Alexnet+CV-EC | 66.56 | 3.74×10 |
| --- | --- | --- |
| Alexnet+CV-CL | 64.72 | 4.81×10 |
| Alexnet+Triplet | 60.8 | - |
| Alexnet+ICV-ECCL | 69.94 | 1.93×10 | | 1 |
| Comparedmethods | Accuracy | Cross-viewintra-classdistance |
| --- | --- | --- |
| Alexnet | 52.4 | 5<br>1.27×10 | | | Iterationstep | Accuracy | Cross-viewintra-classdistance |
| --- | --- | --- |
| Initialbaseline | 52.4 | 5<br>1.27×10 |
| 1stiterCV-EC | 66.56 | 3.74×10 |
| 1stiterCV-CL | 68.12 | 2.82×10 |
| 2nditerCV-EC | 69.33 | 1.96×10 |
| 2nditerCV-CL | 69.94 | 1.93×10 | | 0 |
| Comparedmethods | Accuracy | Cross-viewintra-classdistance |
| --- | --- | --- |
| Alexnet | 52.4 | 5<br>1.27×10 |
| Alexnet+CV-EC | 66.56 | 3.74×10 | | | Alexnet+CV-CL | 64.72 | 4.81×10 |
| --- | --- | --- |
| Alexnet+Triplet | 60.8 | - |
| Alexnet+ICV-ECCL | 69.94 | 1.93×10 | | 1 |
| Comparedmethods | Accuracy | Cross-viewintra-classdistance |
| --- | --- | --- |
| Alexnet | 52.4 | 5<br>1.27×10 |
| Alexnet+CV-EC | 66.56 | 3.74×10 | | | 1stiterCV-EC | 66.56 | 3.74×10 |
| --- | --- | --- |
| 1stiterCV-CL | 68.12 | 2.82×10 |
| 2nditerCV-EC | 69.33 | 1.96×10 |
| 2nditerCV-CL | 69.94 | 1.93×10 | | 0 |
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