premise string | hypothesis string | label int64 |
|---|---|---|
| Model | Size | Valid | Test |
| --- | --- | --- | --- |
| Existingresults | | | |
| UnregularzedLSTM<br>NR-dropout<br>Zoneout<br>VariationalLSTM<br>CharCNN<br>PointerSentinel-LSTM<br>LSTM+continuouscachepointer<br>VariationalLSTM+augmentedloss<br>VariationalRHN<br>NASCell<br>4-layerskipconnectionLSTM<br>AWD-LSTMw/ofinetune<br>AWD-LSTM(Baseline) | 7M<br>66M<br>66M<br>19M<br>21M<br>51M<br>-<br>51M<br>23M<br>54M<br>24M<br>24M<br>24M | 120.7<br>82.2<br>-<br>-<br>72.4<br>-<br>-<br>71.1<br>67.9<br>-<br>60.9<br>60.7<br>60.0 | 114.5<br>78.4<br>77.4<br>73.4<br>78.9<br>70.9<br>72.1<br>68.5<br>65.4<br>62.4<br>58.3<br>58.8<br>57.3 | | | Oursystem | | | |
| --- | --- | --- | --- |
| SharpenedSigmoidAWD-LSTMw/ofinetune<br>SharpenedSigmoidAWD-LSTM<br>2<br>G-LSTMw/ofinetune<br>2<br>G-LSTM | 24M<br>24M<br>24M<br>24M | 61.6<br>59.9<br>60.4<br>58.5 | 59.4<br>57.5<br>58.2<br>56.1 |
| +continuouscachepointer | | | |
| AWD-LSTM+continuouscachepointer<br>SharpenedSigmoidAWD-LSTM+continuouscachepointer<br>2<br>G-LSTM+continuouscachepointer | 24M<br>24M<br>24M | 53.9<br>53.9<br>52.9 | 52.8<br>53.2<br>52.1 | | 1 |
| Model | Size | Valid | Test |
| --- | --- | --- | --- |
| Existingresults | | | |
| UnregularzedLSTM<br>NR-dropout<br>Zoneout<br>VariationalLSTM<br>CharCNN<br>PointerSentinel-LSTM<br>LSTM+continuouscachepointer<br>VariationalLSTM+augmentedloss<br>VariationalRHN<br>NASCell<br>4-layerskipconnectionLSTM<br>AWD-LSTMw/ofinetune<br>AWD-LSTM(Baseline) | 7M<br>66M<br>66M<br>19M<br>21M<br>51M<br>-<br>51M<br>23M<br>54M<br>24M<br>24M<br>24M | 120.7<br>82.2<br>-<br>-<br>72.4<br>-<br>-<br>71.1<br>67.9<br>-<br>60.9<br>60.7<br>60.0 | 114.5<br>78.4<br>77.4<br>73.4<br>78.9<br>70.9<br>72.1<br>68.5<br>65.4<br>62.4<br>58.3<br>58.8<br>57.3 | | | Architecture | | |
| --- | --- | --- |
| Model | Parameter | Value |
| Chr,Wrd<br>Mt<br>Chr,Wrd,Mt<br>Chr,Wrd,Mt<br>Chr,Wrd,Mt<br>Wrd<br>Chr<br>Chr,Wrd,Mt | BiLSTMlayers<br>BiLSTMlayers<br>BiLSTMsize<br>DropoutLSTMs<br>DropoutMLP<br>Dropoutembeddings<br>Dropoutembeddings<br>Nonlinearact.(MLP) | 3<br>1<br>400<br>0.33<br>0.33<br>0.33<br>0.05<br>ELU |
| Initialization | | |
| Model<br>Wrd<br>Chr<br>Chr,Wrd,Mt | Parameter<br>embeddings<br>embeddings<br>MLP | Value<br>Zero<br>Gaussian<br>Gaussian |
| Training | | |
| Model | Parameter | Value |
| Chr,Wrd,Mt<br>Chr,Wrd,Mt<br>Chr,Wrd,Mt<br>Chr,Wrd,Mt<br>Chr,Wrd,Mt<br>Chr,Wrd,Mt<br>Chr,Wrd,Mt | Optimizer<br>Loss<br>Learningrate<br>Decay<br>Adamepsilon<br>beta1<br>beta2 | Adam<br>Crossentropy<br>0.002<br>0.999994<br>1e-08<br>0.9<br>0.999 | | 0 |
| Model | Size | Valid | Test |
| --- | --- | --- | --- |
| Existingresults | | | |
| UnregularzedLSTM<br>NR-dropout<br>Zoneout<br>VariationalLSTM<br>CharCNN<br>PointerSentinel-LSTM<br>LSTM+continuouscachepointer<br>VariationalLSTM+augmentedloss<br>VariationalRHN<br>NASCell<br>4-layerskipconnectionLSTM<br>AWD-LSTMw/ofinetune<br>AWD-LSTM(Baseline) | 7M<br>66M<br>66M<br>19M<br>21M<br>51M<br>-<br>51M<br>23M<br>54M<br>24M<br>24M<br>24M | 120.7<br>82.2<br>-<br>-<br>72.4<br>-<br>-<br>71.1<br>67.9<br>-<br>60.9<br>60.7<br>60.0 | 114.5<br>78.4<br>77.4<br>73.4<br>78.9<br>70.9<br>72.1<br>68.5<br>65.4<br>62.4<br>58.3<br>58.8<br>57.3 |
| Oursystem | | | |
| SharpenedSigmoidAWD-LSTMw/ofinetune<br>SharpenedSigmoidAWD-LSTM<br>2<br>G-LSTMw/ofinetune<br>2<br>G-LSTM | 24M<br>24M<br>24M<br>24M | 61.6<br>59.9<br>60.4<br>58.5 | 59.4<br>57.5<br>58.2<br>56.1 | | | +continuouscachepointer | | | |
| --- | --- | --- | --- |
| AWD-LSTM+continuouscachepointer<br>SharpenedSigmoidAWD-LSTM+continuouscachepointer<br>2<br>G-LSTM+continuouscachepointer | 24M<br>24M<br>24M | 53.9<br>53.9<br>52.9 | 52.8<br>53.2<br>52.1 | | 1 |
| Model | Size | Valid | Test |
| --- | --- | --- | --- |
| Existingresults | | | |
| UnregularzedLSTM<br>NR-dropout<br>Zoneout<br>VariationalLSTM<br>CharCNN<br>PointerSentinel-LSTM<br>LSTM+continuouscachepointer<br>VariationalLSTM+augmentedloss<br>VariationalRHN<br>NASCell<br>4-layerskipconnectionLSTM<br>AWD-LSTMw/ofinetune<br>AWD-LSTM(Baseline) | 7M<br>66M<br>66M<br>19M<br>21M<br>51M<br>-<br>51M<br>23M<br>54M<br>24M<br>24M<br>24M | 120.7<br>82.2<br>-<br>-<br>72.4<br>-<br>-<br>71.1<br>67.9<br>-<br>60.9<br>60.7<br>60.0 | 114.5<br>78.4<br>77.4<br>73.4<br>78.9<br>70.9<br>72.1<br>68.5<br>65.4<br>62.4<br>58.3<br>58.8<br>57.3 |
| Oursystem | | | |
| SharpenedSigmoidAWD-LSTMw/ofinetune<br>SharpenedSigmoidAWD-LSTM<br>2<br>G-LSTMw/ofinetune<br>2<br>G-LSTM | 24M<br>24M<br>24M<br>24M | 61.6<br>59.9<br>60.4<br>58.5 | 59.4<br>57.5<br>58.2<br>56.1 | | | Chr,Wrd<br>Mt<br>Chr,Wrd,Mt<br>Chr,Wrd,Mt<br>Chr,Wrd,Mt<br>Wrd<br>Chr<br>Chr,Wrd,Mt | BiLSTMlayers<br>BiLSTMlayers<br>BiLSTMsize<br>DropoutLSTMs<br>DropoutMLP<br>Dropoutembeddings<br>Dropoutembeddings<br>Nonlinearact.(MLP) | 3<br>1<br>400<br>0.33<br>0.33<br>0.33<br>0.05<br>ELU |
| --- | --- | --- |
| Initialization | | |
| Model<br>Wrd<br>Chr<br>Chr,Wrd,Mt | Parameter<br>embeddings<br>embeddings<br>MLP | Value<br>Zero<br>Gaussian<br>Gaussian |
| Training | | |
| Model | Parameter | Value |
| Chr,Wrd,Mt<br>Chr,Wrd,Mt<br>Chr,Wrd,Mt<br>Chr,Wrd,Mt<br>Chr,Wrd,Mt<br>Chr,Wrd,Mt<br>Chr,Wrd,Mt | Optimizer<br>Loss<br>Learningrate<br>Decay<br>Adamepsilon<br>beta1<br>beta2 | Adam<br>Crossentropy<br>0.002<br>0.999994<br>1e-08<br>0.9<br>0.999 | | 0 |
| 32 | 64(2filters) | 64(4filters) | 64(InvConv) |
| --- | --- | --- | --- |
| | 3<br>[64×1] | | |
| 3<br>[32×1] | Conv(3)<br>3<br>[32×32] | | | | | Conv(3)<br>3<br>[16×32] | Conv(3)<br>3<br>[16×48] | | |
| --- | --- | --- | --- |
| Conv(3)<br>3<br>[8×48] | Conv(3)<br>3<br>[8×64] | | |
| Conv(3)<br>3<br>[4×64] | Conv(3)<br>3<br>[4×80] | | |
| FC<br>[1024] | FC<br>[1024] | | |
| FC<br>[1024] | FC<br>[1024] | | |
| FC<br>3<br>[4×80] | FC<br>3<br>[4×96] | | |
| Deconv(2)<br>3<br>[8×64] | Deconv(2)<br>3<br>[8×80] | | |
| Conv(3)→l1<br>3<br>[8×64] | Conv(3)<br>3<br>[8×80] | | |
| OGNProp<br>3<br>OGNConv(2)→l2<br>3<br>[16×48] | 3<br>Deconv(2)<br>3<br>[16×64] | | |
| OGNProp<br>3<br>OGNConv(2)→l3<br>3<br>[32×32] | 3<br>Conv(3)→l1<br>3<br>[16×64] | | |
| | OGNProp<br>3<br>OGNConv(2)→l2<br>3<br>[32×48] | OGNProp<br>3<br>OGNConv(4)→l2<br>3<br>[32×48] | OGNProp<br>3<br>OGNConv(2)<br>3<br>[32×48]<br>3<br>OGNConv*(3)→l2<br>3<br>[32×48] |
| | OGNProp<br>3<br>OGNConv(2)→l3<br>3<br>[64×32] | OGNProp<br>3<br>OGNConv(4)→l3<br>3<br>[64×32] | OGNProp<br>3<br>OGNConv(2)<br>3<br>[64×32]<br>3<br>OGNConv*(3)→l3<br>3<br>[64×32] | | 1 |
| 32 | 64(2filters) | 64(4filters) | 64(InvConv) |
| --- | --- | --- | --- |
| | 3<br>[64×1] | | |
| 3<br>[32×1] | Conv(3)<br>3<br>[32×32] | | | | | [137×137×3] |
| --- |
| Conv(7×7)<br>[69×69×32] |
| Conv(3×3)<br>[35×35×32] |
| Conv(3×3)<br>[18×18×64] |
| Conv(3×3)<br>[9×9×64] |
| Conv(3×3)<br>[5×5×128] |
| FC<br>[1024] |
| FC<br>[1024] |
| FC<br>3<br>[4×c] | | 0 |
| 32 | 64(2filters) | 64(4filters) | 64(InvConv) |
| --- | --- | --- | --- |
| | 3<br>[64×1] | | |
| 3<br>[32×1] | Conv(3)<br>3<br>[32×32] | | | | | Conv(3)<br>3<br>[16×32] | Conv(3)<br>3<br>[16×48] | | |
| --- | --- | --- | --- |
| Conv(3)<br>3<br>[8×48] | Conv(3)<br>3<br>[8×64] | | |
| Conv(3)<br>3<br>[4×64] | Conv(3)<br>3<br>[4×80] | | |
| FC<br>[1024] | FC<br>[1024] | | |
| FC<br>[1024] | FC<br>[1024] | | |
| FC<br>3<br>[4×80] | FC<br>3<br>[4×96] | | |
| Deconv(2)<br>3<br>[8×64] | Deconv(2)<br>3<br>[8×80] | | |
| Conv(3)→l1<br>3<br>[8×64] | Conv(3)<br>3<br>[8×80] | | |
| OGNProp<br>3<br>OGNConv(2)→l2<br>3<br>[16×48] | 3<br>Deconv(2)<br>3<br>[16×64] | | |
| OGNProp<br>3<br>OGNConv(2)→l3<br>3<br>[32×32] | 3<br>Conv(3)→l1<br>3<br>[16×64] | | |
| | OGNProp<br>3<br>OGNConv(2)→l2<br>3<br>[32×48] | OGNProp<br>3<br>OGNConv(4)→l2<br>3<br>[32×48] | OGNProp<br>3<br>OGNConv(2)<br>3<br>[32×48]<br>3<br>OGNConv*(3)→l2<br>3<br>[32×48] |
| | OGNProp<br>3<br>OGNConv(2)→l3<br>3<br>[64×32] | OGNProp<br>3<br>OGNConv(4)→l3<br>3<br>[64×32] | OGNProp<br>3<br>OGNConv(2)<br>3<br>[64×32]<br>3<br>OGNConv*(3)→l3<br>3<br>[64×32] | | 1 |
| 32 | 64(2filters) | 64(4filters) | 64(InvConv) |
| --- | --- | --- | --- |
| | 3<br>[64×1] | | |
| 3<br>[32×1] | Conv(3)<br>3<br>[32×32] | | | | | FC<br>[1024] |
| --- |
| FC<br>3<br>[4×c] | | 0 |
| | P-average(mm) | D-average(mm) | R(pixels) |
| --- | --- | --- | --- |
| Plane1 | 5.802 | 2.015 | 1.512 |
| Plane2 | 5.166 | 4.117 | 1.215 | | | Plane3 | 3.002 | 3.481 | 0.405 |
| --- | --- | --- | --- |
| Plane4 | 2.479 | 0.483 | 1.171 |
| Plane5 | 7.632 | 14.022 | 2.117 | | 1 |
| | P-average(mm) | D-average(mm) | R(pixels) |
| --- | --- | --- | --- |
| Plane1 | 5.802 | 2.015 | 1.512 |
| Plane2 | 5.166 | 4.117 | 1.215 | | | | P-average(mm) | D-average(mm) | R(pixels) |
| --- | --- | --- | --- |
| Plane1 | 6.942 | 0.8080 | 2.716 |
| Plane2 | 4.206 | 3.7432 | 0.854 |
| Plane3 | 4.864 | 4.5740 | 1.656 |
| Plane4 | 1.640 | 0.1930 | 0.353 |
| Plane5 | 833.587 | 1482 | 17.741 | | 0 |
| | P-average(mm) | D-average(mm) | R(pixels) |
| --- | --- | --- | --- |
| Plane1 | 5.802 | 2.015 | 1.512 |
| Plane2 | 5.166 | 4.117 | 1.215 |
| Plane3 | 3.002 | 3.481 | 0.405 | | | Plane4 | 2.479 | 0.483 | 1.171 |
| --- | --- | --- | --- |
| Plane5 | 7.632 | 14.022 | 2.117 | | 1 |
| | P-average(mm) | D-average(mm) | R(pixels) |
| --- | --- | --- | --- |
| Plane1 | 5.802 | 2.015 | 1.512 |
| Plane2 | 5.166 | 4.117 | 1.215 |
| Plane3 | 3.002 | 3.481 | 0.405 | | | Plane3 | 4.864 | 4.5740 | 1.656 |
| --- | --- | --- | --- |
| Plane4 | 1.640 | 0.1930 | 0.353 |
| Plane5 | 833.587 | 1482 | 17.741 | | 0 |
| NumberofApps | NumberofHLI |
| --- | --- |
| 176 | [1,49) |
| 13 | [49,97) |
| 2 | [97,145) | | | 0 | [145,193) |
| --- | --- |
| 3 | [193,241) | | 1 |
| NumberofApps | NumberofHLI |
| --- | --- |
| 176 | [1,49) |
| 13 | [49,97) |
| 2 | [97,145) | | | Numberofpairsexcluded | |
| --- | --- |
| EdgeThreshold(60 | 3398 |
| 65 | 3440 |
| 70 | 3428 |
| 75 | 3409 |
| 80 | 2696 |
| 85 | 2409 |
| 90 | 1837 |
| 95 | 1707 | | 0 |
| NumberofApps | NumberofHLI |
| --- | --- |
| 176 | [1,49) |
| 13 | [49,97) | | | 2 | [97,145) |
| --- | --- |
| 0 | [145,193) |
| 3 | [193,241) | | 1 |
| NumberofApps | NumberofHLI |
| --- | --- |
| 176 | [1,49) |
| 13 | [49,97) | | | 90 | 1837 |
| --- | --- |
| 95 | 1707 | | 0 |
| | | MKCF(Ours) | UT | TI | Mendesetal. | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Video | Type | MOTA | MOTP | MOTA | MOTP | MOTA | MOTP | MOTA | MOTP |
| Sherbroo | Cars<br>ePedestrians<br>AllObjects | 0.789<br>0.671<br>0.763 | 11.82<br>7.63<br>10.55 | 0.887<br>0.705<br>0.787 | 10.59<br>6.61<br>8.64 | 0.825<br>0.014<br>0.3841 | 7.42<br>11.98<br>7.54 | 0.707<br>0.601<br>0.695 | 13.21<br>7.97<br>9.95 | | | Rouen | Cars<br>Pedestrians<br>Cyclists<br>AllObjects | 0.813<br>0.804<br>0.890<br>0.813 | 14.86<br>14.81<br>14.67<br>14.86 | 0.896<br>0.830<br>0.927<br>0.844 | 9.73<br>13.77<br>14.13<br>13.19 | 0.185<br>0.647<br>0.869<br>0.589 | 66.69<br>20.04<br>13.11<br>24.20 | 0.918<br>0.672<br>0.881<br>0.718 | 11.41<br>14.88<br>13.67<br>14.29 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| St-<br>Marc | Cars<br>Pedestrians<br>Cyclists<br>AllObjects | 0.590<br>0.834<br>0.975<br>0.825 | 12.54<br>7.35<br>6.33<br>7.93 | 0.889<br>0.730<br>0.989<br>0.764 | 10.90<br>5.05<br>6.39<br>5.99 | -0.178<br>0.693<br>0.895<br>0.602 | 38.99<br>10.44<br>7.46<br>14.58 | 0.713<br>0.505<br>0.935<br>0.560 | 11.44<br>7.09<br>6.30<br>7.71 |
| Rene-<br>Levesqu | Cars<br>Cyclists<br>AllObjects | 0.855<br>0.291<br>0.572 | 2.72<br>2.77<br>2.74 | 0.796<br>0.232<br>0.723 | 3.04<br>2.20<br>2.98 | 0.547<br>0.232<br>0.503 | 5.23<br>3.14<br>5.10 | 0.163<br>0.216<br>0.402 | 7.09<br>2.26<br>2.95 | | 1 |
| | | MKCF(Ours) | UT | TI | Mendesetal. | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Video | Type | MOTA | MOTP | MOTA | MOTP | MOTA | MOTP | MOTA | MOTP |
| Sherbroo | Cars<br>ePedestrians<br>AllObjects | 0.789<br>0.671<br>0.763 | 11.82<br>7.63<br>10.55 | 0.887<br>0.705<br>0.787 | 10.59<br>6.61<br>8.64 | 0.825<br>0.014<br>0.3841 | 7.42<br>11.98<br>7.54 | 0.707<br>0.601<br>0.695 | 13.21<br>7.97<br>9.95 | | | | MKCF | UT | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Dataset | MOTA | MOTP | MOTA | MOTP | | | | |
| | ViBe | Ours | ViBe | Ours | ViBe | Ours | ViBe | Ours |
| Sherbrooke | 0.317 | 0.523 | 0.553 | 0.576 | 0.404 | 0.690 | 0.576 | 0.590 |
| Rene-Levesque | 0.334 | 0.424 | 0.5309 | 0.660 | 0.565 | 0.613 | 0.582 | 0.705 |
| Rouen | 0.501 | 0.629 | 0.582 | 0.600 | 0.696 | 0.670 | 0.617 | 0.620 |
| St-Marc | 0.463 | 0.534 | 0.652 | 0.651 | 0.638 | 0.653 | 0.691 | 0.682 | | 0 |
| | | MKCF(Ours) | UT | TI | Mendesetal. | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Video | Type | MOTA | MOTP | MOTA | MOTP | MOTA | MOTP | MOTA | MOTP | | | Sherbroo | Cars<br>ePedestrians<br>AllObjects | 0.789<br>0.671<br>0.763 | 11.82<br>7.63<br>10.55 | 0.887<br>0.705<br>0.787 | 10.59<br>6.61<br>8.64 | 0.825<br>0.014<br>0.3841 | 7.42<br>11.98<br>7.54 | 0.707<br>0.601<br>0.695 | 13.21<br>7.97<br>9.95 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Rouen | Cars<br>Pedestrians<br>Cyclists<br>AllObjects | 0.813<br>0.804<br>0.890<br>0.813 | 14.86<br>14.81<br>14.67<br>14.86 | 0.896<br>0.830<br>0.927<br>0.844 | 9.73<br>13.77<br>14.13<br>13.19 | 0.185<br>0.647<br>0.869<br>0.589 | 66.69<br>20.04<br>13.11<br>24.20 | 0.918<br>0.672<br>0.881<br>0.718 | 11.41<br>14.88<br>13.67<br>14.29 |
| St-<br>Marc | Cars<br>Pedestrians<br>Cyclists<br>AllObjects | 0.590<br>0.834<br>0.975<br>0.825 | 12.54<br>7.35<br>6.33<br>7.93 | 0.889<br>0.730<br>0.989<br>0.764 | 10.90<br>5.05<br>6.39<br>5.99 | -0.178<br>0.693<br>0.895<br>0.602 | 38.99<br>10.44<br>7.46<br>14.58 | 0.713<br>0.505<br>0.935<br>0.560 | 11.44<br>7.09<br>6.30<br>7.71 |
| Rene-<br>Levesqu | Cars<br>Cyclists<br>AllObjects | 0.855<br>0.291<br>0.572 | 2.72<br>2.77<br>2.74 | 0.796<br>0.232<br>0.723 | 3.04<br>2.20<br>2.98 | 0.547<br>0.232<br>0.503 | 5.23<br>3.14<br>5.10 | 0.163<br>0.216<br>0.402 | 7.09<br>2.26<br>2.95 | | 1 |
| | | MKCF(Ours) | UT | TI | Mendesetal. | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Video | Type | MOTA | MOTP | MOTA | MOTP | MOTA | MOTP | MOTA | MOTP | | | Sherbrooke | 0.317 | 0.523 | 0.553 | 0.576 | 0.404 | 0.690 | 0.576 | 0.590 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Rene-Levesque | 0.334 | 0.424 | 0.5309 | 0.660 | 0.565 | 0.613 | 0.582 | 0.705 |
| Rouen | 0.501 | 0.629 | 0.582 | 0.600 | 0.696 | 0.670 | 0.617 | 0.620 |
| St-Marc | 0.463 | 0.534 | 0.652 | 0.651 | 0.638 | 0.653 | 0.691 | 0.682 | | 0 |
| Algorithm | α=0.01 | | | |
| --- | --- | --- | --- | --- |
| recall | precision | F1 | nTest | |
| He-Geng | 0.67±0.08 | 1.00±0.00 | 0.7976±0.06 | 53,525±2705 |
| Baseline | 1.00±0.00 | 0.91±0.11 | 0.9492±0.07 | 3,174±675 | | | MIMB | 0.95±0.08 | 0.94±0.08 | 0.9421±0.06 | 1,738±184 |
| --- | --- | --- | --- | --- |
| | α=0.05 | | | |
| He-Geng | 0.68±0.09 | 0.95±0.11 | 0.7876±0.07 | 62,228±2608 |
| Baseline | 1.00±0.00 | 0.71±0.14 | 0.8199±0.09 | 3,821±777 |
| MIMB | 0.95±0.08 | 0.93±0.10 | 0.9358±0.08 | 1,968±298 | | 1 |
| Algorithm | α=0.01 | | | |
| --- | --- | --- | --- | --- |
| recall | precision | F1 | nTest | |
| He-Geng | 0.67±0.08 | 1.00±0.00 | 0.7976±0.06 | 53,525±2705 |
| Baseline | 1.00±0.00 | 0.91±0.11 | 0.9492±0.07 | 3,174±675 | | | Algorithm | α=0.01 | | | |
| --- | --- | --- | --- | --- |
| recall | precision | F1 | nTest | |
| He-Geng | 0.70±0.11 | 0.95±0.16 | 0.80±0.11 | 52,042±3010 |
| Baseline | 1.00±0.00 | 0.83±0.14 | 0.90±0.09 | 3,837±598 |
| MIMB | 0.84±0.10 | 0.96±0.12 | 0.89±0.08 | 2,166±307 |
| | α=0.05 | | | |
| He-Geng | 0.80±0.13 | 0.92±0.13 | 0.84±0.06 | 61,841±9378 |
| Baseline | 1.00±0.00 | 0.71±0.08 | 0.83±0.05 | 4,237±567 |
| MIMB | 0.90±0.11 | 0.94±0.10 | 0.92±0.09 | 2,827±442 | | 0 |
| Algorithm | α=0.01 | | | |
| --- | --- | --- | --- | --- |
| recall | precision | F1 | nTest | |
| He-Geng | 0.67±0.08 | 1.00±0.00 | 0.7976±0.06 | 53,525±2705 | | | Baseline | 1.00±0.00 | 0.91±0.11 | 0.9492±0.07 | 3,174±675 |
| --- | --- | --- | --- | --- |
| MIMB | 0.95±0.08 | 0.94±0.08 | 0.9421±0.06 | 1,738±184 |
| | α=0.05 | | | |
| He-Geng | 0.68±0.09 | 0.95±0.11 | 0.7876±0.07 | 62,228±2608 |
| Baseline | 1.00±0.00 | 0.71±0.14 | 0.8199±0.09 | 3,821±777 |
| MIMB | 0.95±0.08 | 0.93±0.10 | 0.9358±0.08 | 1,968±298 | | 1 |
| Algorithm | α=0.01 | | | |
| --- | --- | --- | --- | --- |
| recall | precision | F1 | nTest | |
| He-Geng | 0.67±0.08 | 1.00±0.00 | 0.7976±0.06 | 53,525±2705 | | | Baseline | 1.00±0.00 | 0.71±0.08 | 0.83±0.05 | 4,237±567 |
| --- | --- | --- | --- | --- |
| MIMB | 0.90±0.11 | 0.94±0.10 | 0.92±0.09 | 2,827±442 | | 0 |
| Benchmark | #Agents<br>124814 | | | | |
| --- | --- | --- | --- | --- | --- |
| 9-Costas | 715.369 | 368.298(1.94) | 184.141(3.88) | 92.165(7.76) | 53.453(13.38) |
| Stable | 653.705 | 368.943(1.77) | 185.474(3.52) | 92.811(7.04) | 53.860(12.13) |
| Knight | 275.737 | 141.213(1.95) | 70.528(3.9) | 35.539(7.75) | 22.403(12.3) | | | SendMore | 115.183 | 65.271(1.76) | 31.447(3.66) | 16.496(6.98) | 9.686(11.89) |
| --- | --- | --- | --- | --- | --- |
| 8-Costas | 66.392 | 34.281(1.93) | 17.192(3.86) | 8.680(7.64) | 5.202(12.76) |
| 8-Puzzle | 52.945 | 29.601(1.78) | 15.026(3.52) | 7.845(6.74) | 4.754(11.13) |
| Bart | 25.562 | 15.411(1.65) | 6.868(3.72) | 3.577(7.14) | 2.144(11.93) |
| Solitaire | 12.912 | 7.598(1.69) | 3.813(3.38) | 2.029(6.36) | 1.335(9.67) |
| 10-Queens | 7.575 | 3.922(1.93) | 2.087(3.62) | 1.378(5.49) | 1.141(6.63) |
| Hamilton | 6.895 | 3.879(1.77) | 1.940(3.55) | 1.151(5.99) | 0.761(9.06) |
| MapColoring | 2.036 | 1.298(1.56) | 0.696(2.92) | 0.479(4.25) | 0.430(4.73) |
| 8-Queens | 0.306 | 0.198(1.54) | 0.143(2.13) | 0.157(1.94) | 0.149(2.05) | | 1 |
| Benchmark | #Agents<br>124814 | | | | |
| --- | --- | --- | --- | --- | --- |
| 9-Costas | 715.369 | 368.298(1.94) | 184.141(3.88) | 92.165(7.76) | 53.453(13.38) |
| Stable | 653.705 | 368.943(1.77) | 185.474(3.52) | 92.811(7.04) | 53.860(12.13) |
| Knight | 275.737 | 141.213(1.95) | 70.528(3.9) | 35.539(7.75) | 22.403(12.3) | | | Benchmark | #Agents<br>124814 | | | | |
| --- | --- | --- | --- | --- | --- |
| 9-Costas | 715.963 | 366.385(1.95) | 182.654(3.91) | 93.602(7.64) | 52.901(13.53) |
| Stable | 614.582 | 374.259(1.64) | 184.404(3.33) | 93.884(6.54) | 54.022(11.37) |
| Knight | 276.849 | 141.118(1.96) | 70.568(3.92) | 35.741(7.74) | 20.958(13.2) |
| SendMore | 116.518 | 65.936(1.76) | 31.892(3.65) | 16.882(6.9) | 10.364(11.24) |
| 8-Costas | 66.221 | 34.053(1.94) | 17.126(3.86) | 8.656(7.65) | 5.202(12.72) |
| 8-Puzzle | 52.909 | 29.615(1.78) | 15.148(3.49) | 8.206(6.44) | 5.654(9.35) |
| Bart | 25.734 | 13.898(1.85) | 6.863(3.74) | 3.704(6.94) | 2.382(10.8) |
| Solitaire | 12.676 | 7.552(1.67) | 3.910(3.24) | 2.177(5.82) | 1.606(7.89) |
| 10-Queens | 7.557 | 3.935(1.92) | 2.116(3.57) | 1.483(5.09) | 1.535(4.92) |
| Hamilton | 6.908 | 3.910(1.76) | 1.963(3.51) | 1.284(5.38) | 0.991(6.97) |
| MapColoring | 2.009 | 1.332(1.5) | 0.721(2.78) | 0.476(4.22) | 0.675(2.97) |
| 8-Queens | 0.308 | 0.194(1.58) | 0.158(1.94) | 0.161(1.91) | 0.138(2.23) | | 0 |
| Benchmark | #Agents<br>124814 | | | | |
| --- | --- | --- | --- | --- | --- |
| 9-Costas | 715.369 | 368.298(1.94) | 184.141(3.88) | 92.165(7.76) | 53.453(13.38) |
| Stable | 653.705 | 368.943(1.77) | 185.474(3.52) | 92.811(7.04) | 53.860(12.13) |
| Knight | 275.737 | 141.213(1.95) | 70.528(3.9) | 35.539(7.75) | 22.403(12.3) |
| SendMore | 115.183 | 65.271(1.76) | 31.447(3.66) | 16.496(6.98) | 9.686(11.89) | | | 8-Costas | 66.392 | 34.281(1.93) | 17.192(3.86) | 8.680(7.64) | 5.202(12.76) |
| --- | --- | --- | --- | --- | --- |
| 8-Puzzle | 52.945 | 29.601(1.78) | 15.026(3.52) | 7.845(6.74) | 4.754(11.13) |
| Bart | 25.562 | 15.411(1.65) | 6.868(3.72) | 3.577(7.14) | 2.144(11.93) |
| Solitaire | 12.912 | 7.598(1.69) | 3.813(3.38) | 2.029(6.36) | 1.335(9.67) |
| 10-Queens | 7.575 | 3.922(1.93) | 2.087(3.62) | 1.378(5.49) | 1.141(6.63) |
| Hamilton | 6.895 | 3.879(1.77) | 1.940(3.55) | 1.151(5.99) | 0.761(9.06) |
| MapColoring | 2.036 | 1.298(1.56) | 0.696(2.92) | 0.479(4.25) | 0.430(4.73) |
| 8-Queens | 0.306 | 0.198(1.54) | 0.143(2.13) | 0.157(1.94) | 0.149(2.05) | | 1 |
| Benchmark | #Agents<br>124814 | | | | |
| --- | --- | --- | --- | --- | --- |
| 9-Costas | 715.369 | 368.298(1.94) | 184.141(3.88) | 92.165(7.76) | 53.453(13.38) |
| Stable | 653.705 | 368.943(1.77) | 185.474(3.52) | 92.811(7.04) | 53.860(12.13) |
| Knight | 275.737 | 141.213(1.95) | 70.528(3.9) | 35.539(7.75) | 22.403(12.3) |
| SendMore | 115.183 | 65.271(1.76) | 31.447(3.66) | 16.496(6.98) | 9.686(11.89) | | | 10-Queens | 7.557 | 3.935(1.92) | 2.116(3.57) | 1.483(5.09) | 1.535(4.92) |
| --- | --- | --- | --- | --- | --- |
| Hamilton | 6.908 | 3.910(1.76) | 1.963(3.51) | 1.284(5.38) | 0.991(6.97) |
| MapColoring | 2.009 | 1.332(1.5) | 0.721(2.78) | 0.476(4.22) | 0.675(2.97) |
| 8-Queens | 0.308 | 0.194(1.58) | 0.158(1.94) | 0.161(1.91) | 0.138(2.23) | | 0 |
| Model | F1measure | | |
| --- | --- | --- | --- |
| | forward | backward | bidirectional |
| lstm<br>gru | 95.12<br>95.43 | –<br>– | 95.23<br>95.53 | | | E-rnn<br>J-rnn<br>I-rnn | 94.73<br>94.94<br>95.21 | 93.61<br>94.80<br>94.64 | 94.71<br>94.89<br>94.75 |
| --- | --- | --- | --- |
| I-rnnWordsGRU | 93.58 | 93.81 | 93.83 |
| I-rnnWords<br>I-rnnWords+Classes<br>I-rnnWords+Classes+CC | 94.31<br>95.37<br>95.40 | 94.32<br>95.44<br>95.39 | 94.47<br>95.56<br>95.46 |
| I-rnnWordsdeep<br>I-rnnWords+Classesdeep<br>I-rnnWords+Classes+CCdeep | 94.47<br>95.67<br>95.56 | 94.29<br>95.54<br>95.39 | 94.52<br>95.60<br>95.53 | | 1 |
| Model | F1measure | | |
| --- | --- | --- | --- |
| | forward | backward | bidirectional |
| lstm<br>gru | 95.12<br>95.43 | –<br>– | 95.23<br>95.53 | | | Model | Manuallyadded | | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Tagset | full | reduced | full | | | | | | |
| Previouslytrainedmodel | – | – | no | yes | no | | | | |
| Maximumsuffixlenght<br>parameter | – | – | 15 | 5 | 15 | 5 | 15 | 5 | 15 |
| Numberofsuffixes<br>Maximumsuffixlenght<br>Totalnumberoftags<br>Tagspersuffix | 208<br>–<br>376<br>1.8 | 208<br>–<br>362<br>1.7 | 16<br>1<br>97<br>6 | 94<br>4<br>445<br>4.7 | 16<br>1<br>97<br>6 | 100<br>4<br>340<br>3.4 | 16<br>1<br>87<br>5.4 | 78<br>4<br>418<br>5.4 | 16<br>2<br>51<br>3.2 | | 0 |
| Model | F1measure | | |
| --- | --- | --- | --- |
| | forward | backward | bidirectional | | | lstm<br>gru | 95.12<br>95.43 | –<br>– | 95.23<br>95.53 |
| --- | --- | --- | --- |
| E-rnn<br>J-rnn<br>I-rnn | 94.73<br>94.94<br>95.21 | 93.61<br>94.80<br>94.64 | 94.71<br>94.89<br>94.75 |
| I-rnnWordsGRU | 93.58 | 93.81 | 93.83 |
| I-rnnWords<br>I-rnnWords+Classes<br>I-rnnWords+Classes+CC | 94.31<br>95.37<br>95.40 | 94.32<br>95.44<br>95.39 | 94.47<br>95.56<br>95.46 |
| I-rnnWordsdeep<br>I-rnnWords+Classesdeep<br>I-rnnWords+Classes+CCdeep | 94.47<br>95.67<br>95.56 | 94.29<br>95.54<br>95.39 | 94.52<br>95.60<br>95.53 | | 1 |
| Model | F1measure | | |
| --- | --- | --- | --- |
| | forward | backward | bidirectional | | | Maximumsuffixlenght<br>parameter | – | – | 15 | 5 | 15 | 5 | 15 | 5 | 15 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Numberofsuffixes<br>Maximumsuffixlenght<br>Totalnumberoftags<br>Tagspersuffix | 208<br>–<br>376<br>1.8 | 208<br>–<br>362<br>1.7 | 16<br>1<br>97<br>6 | 94<br>4<br>445<br>4.7 | 16<br>1<br>97<br>6 | 100<br>4<br>340<br>3.4 | 16<br>1<br>87<br>5.4 | 78<br>4<br>418<br>5.4 | 16<br>2<br>51<br>3.2 | | 0 |
| Name | SpectralSDPGT | IndexM-treeLSH |
| --- | --- | --- |
| Facebook | 0.00970.10740.1044 | 0.10820.08270.0340 |
| Gplus | 0.01190.15930.1544 | 0.16020.12070.0500 |
| Twitter | 0.00350.04800.0465 | 0.04830.03630.0150 |
| Epinions1 | 0.00870.12470.1208 | 0.12540.09410.0390 |
| LiveJournal1 | 0.00390.07030.0680 | 0.07060.05230.0218 |
| Pokec | 0.00090.01740.0168 | 0.01750.01290.0054 |
| Slashdot0811 | 0.00050.00970.0094 | 0.00980.00720.0030 | | | Slashdot0922 | 0.00070.01380.0133 | 0.01380.01020.0043 |
| --- | --- | --- |
| Friendster | 0.00120.02730.0263 | 0.02730.02000.0084 |
| Orkut | 0.00160.04110.0397 | 0.04120.03000.0126 |
| Youtube | 0.00310.08690.0838 | 0.08710.06330.0267 |
| DBLP | 0.00070.02100.0203 | 0.02110.01520.0064 |
| Arxiv-AstroPh | 0.00240.09290.0895 | 0.09310.06690.0283 |
| web-Stanford | 0.00070.03200.0308 | 0.03200.02290.0097 |
| Amazon0601 | 0.00180.08990.0865 | 0.09000.06430.0273 |
| P2P-Gnutella31 | 0.00090.05220.0503 | 0.05230.03730.0158 |
| RoadNet-CA | 0.00240.15020.1445 | 0.15040.10700.0455 |
| Wiki-Vote | 0.00260.18530.1783 | 0.18550.13180.0561 | | 1 |
| Name | SpectralSDPGT | IndexM-treeLSH |
| --- | --- | --- |
| Facebook | 0.00970.10740.1044 | 0.10820.08270.0340 |
| Gplus | 0.01190.15930.1544 | 0.16020.12070.0500 |
| Twitter | 0.00350.04800.0465 | 0.04830.03630.0150 |
| Epinions1 | 0.00870.12470.1208 | 0.12540.09410.0390 |
| LiveJournal1 | 0.00390.07030.0680 | 0.07060.05230.0218 |
| Pokec | 0.00090.01740.0168 | 0.01750.01290.0054 |
| Slashdot0811 | 0.00050.00970.0094 | 0.00980.00720.0030 | | | 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 |
| Name | SpectralSDPGT | IndexM-treeLSH |
| --- | --- | --- |
| Facebook | 0.00970.10740.1044 | 0.10820.08270.0340 |
| Gplus | 0.01190.15930.1544 | 0.16020.12070.0500 |
| Twitter | 0.00350.04800.0465 | 0.04830.03630.0150 |
| Epinions1 | 0.00870.12470.1208 | 0.12540.09410.0390 |
| LiveJournal1 | 0.00390.07030.0680 | 0.07060.05230.0218 |
| Pokec | 0.00090.01740.0168 | 0.01750.01290.0054 | | | Slashdot0811 | 0.00050.00970.0094 | 0.00980.00720.0030 |
| --- | --- | --- |
| Slashdot0922 | 0.00070.01380.0133 | 0.01380.01020.0043 |
| Friendster | 0.00120.02730.0263 | 0.02730.02000.0084 |
| Orkut | 0.00160.04110.0397 | 0.04120.03000.0126 |
| Youtube | 0.00310.08690.0838 | 0.08710.06330.0267 |
| DBLP | 0.00070.02100.0203 | 0.02110.01520.0064 |
| Arxiv-AstroPh | 0.00240.09290.0895 | 0.09310.06690.0283 |
| web-Stanford | 0.00070.03200.0308 | 0.03200.02290.0097 |
| Amazon0601 | 0.00180.08990.0865 | 0.09000.06430.0273 |
| P2P-Gnutella31 | 0.00090.05220.0503 | 0.05230.03730.0158 |
| RoadNet-CA | 0.00240.15020.1445 | 0.15040.10700.0455 |
| Wiki-Vote | 0.00260.18530.1783 | 0.18550.13180.0561 | | 1 |
| Name | SpectralSDPGT | IndexM-treeLSH |
| --- | --- | --- |
| Facebook | 0.00970.10740.1044 | 0.10820.08270.0340 |
| Gplus | 0.01190.15930.1544 | 0.16020.12070.0500 |
| Twitter | 0.00350.04800.0465 | 0.04830.03630.0150 |
| Epinions1 | 0.00870.12470.1208 | 0.12540.09410.0390 |
| LiveJournal1 | 0.00390.07030.0680 | 0.07060.05230.0218 |
| Pokec | 0.00090.01740.0168 | 0.01750.01290.0054 | | | LiveJournal | undirected | 4.8M | 69M |
| --- | --- | --- | --- |
| Orkut | undirected | 3.1M | 117M |
| Twitter-2010 | directed | 42M | 1.5B |
| UK-2007-05 | directed | 106M | 3.7B | | 0 |
| | Cluster1(similar) | Cluster2(Non-similar) | Cluster3others |
| --- | --- | --- | --- |
| EuclideanMetric | 23 | 3 | 16 | | | Minkowski,p=3 | 81 | 7 | 17 |
| --- | --- | --- | --- |
| ManhattanMetric | 23 | 3 | 16 |
| HammingMetric | 23 | 3 | 16 |
| PQ-GramMetric | 15 | 15 | 12 |
| EditDistanceMetric | 16 | 15 | 11 | | 1 |
| | Cluster1(similar) | Cluster2(Non-similar) | Cluster3others |
| --- | --- | --- | --- |
| EuclideanMetric | 23 | 3 | 16 | | | Euclideandistance | dvalueofdatalake | dvalueofDW |
| --- | --- | --- |
| Cluster1 | 0.64 | 0.76 |
| Cluster2 | 0.71 | 0.87 |
| Cluster3 | 0.65 | 0.87 |
| Cluster4 | 0.88 | 0.99 | | 0 |
| | Cluster1(similar) | Cluster2(Non-similar) | Cluster3others |
| --- | --- | --- | --- |
| EuclideanMetric | 23 | 3 | 16 |
| Minkowski,p=3 | 81 | 7 | 17 | | | ManhattanMetric | 23 | 3 | 16 |
| --- | --- | --- | --- |
| HammingMetric | 23 | 3 | 16 |
| PQ-GramMetric | 15 | 15 | 12 |
| EditDistanceMetric | 16 | 15 | 11 | | 1 |
| | Cluster1(similar) | Cluster2(Non-similar) | Cluster3others |
| --- | --- | --- | --- |
| EuclideanMetric | 23 | 3 | 16 |
| Minkowski,p=3 | 81 | 7 | 17 | | | Cluster2 | 0.71 | 0.87 |
| --- | --- | --- |
| Cluster3 | 0.65 | 0.87 |
| Cluster4 | 0.88 | 0.99 | | 0 |
| | Featuresandlabels | | | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| f0 | f1 | f2 | f3 | f4 | f5 | f6 | f7 | label | pred | |
| True1 | 4 | 0 | 7 | 7 | 0 | 0 | 0 | 0 | 3 | 3 | | | True2 | 5 | 0 | 0 | 5 | 9 | 5 | 3 | 6 | 0 | 0 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Wrong1 | 5 | 6 | 7 | 9 | 6 | 4 | 7 | 9 | 5 | 9 | | 1 |
| | Featuresandlabels | | | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| f0 | f1 | f2 | f3 | f4 | f5 | f6 | f7 | label | pred | |
| True1 | 4 | 0 | 7 | 7 | 0 | 0 | 0 | 0 | 3 | 3 | | | Labels | Road | Road | Road,Wood | Road,Wood | Wood | Wood |
| --- | --- | --- | --- | --- | --- | --- |
| cAw | 100 | 30 | 40 | 50 | 10 | 20 |
| cAm | 20 | 3 | 4 | 5 | 1 | 2 |
| cBw | 10 | 7 | 45 | 55 | 30 | 50 |
| cCw | 15 | 12 | 35 | 40 | 15 | 25 |
| cCw | 10 | 3 | 4 | 5 | 1 | 2 | | 0 |
| | Featuresandlabels | | | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| f0 | f1 | f2 | f3 | f4 | f5 | f6 | f7 | label | pred | |
| True1 | 4 | 0 | 7 | 7 | 0 | 0 | 0 | 0 | 3 | 3 | | | True2 | 5 | 0 | 0 | 5 | 9 | 5 | 3 | 6 | 0 | 0 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Wrong1 | 5 | 6 | 7 | 9 | 6 | 4 | 7 | 9 | 5 | 9 | | 1 |
| | Featuresandlabels | | | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| f0 | f1 | f2 | f3 | f4 | f5 | f6 | f7 | label | pred | |
| True1 | 4 | 0 | 7 | 7 | 0 | 0 | 0 | 0 | 3 | 3 | | | cBw | 10 | 7 | 45 | 55 | 30 | 50 |
| --- | --- | --- | --- | --- | --- | --- |
| cCw | 15 | 12 | 35 | 40 | 15 | 25 |
| cCw | 10 | 3 | 4 | 5 | 1 | 2 | | 0 |
| Expected | January | February | March |
| --- | --- | --- | --- |
| 180000 | 80000 | 25000 | 15000 |
| 450000 | 100000 | 20000 | 30000 |
| 45000 | 25000 | 30000 | 80000 |
| 150000 | 15000 | 10000 | 5000 |
| 35000 | 150000 | 5000 | 10000 |
| 50000 | 5000 | 40000 | 60000 | | | 200000 | 20000 | 50000 | 70000 |
| --- | --- | --- | --- |
| 70000 | 35000 | 200000 | 100000 | | 1 |
| Expected | January | February | March |
| --- | --- | --- | --- |
| 180000 | 80000 | 25000 | 15000 |
| 450000 | 100000 | 20000 | 30000 |
| 45000 | 25000 | 30000 | 80000 |
| 150000 | 15000 | 10000 | 5000 |
| 35000 | 150000 | 5000 | 10000 |
| 50000 | 5000 | 40000 | 60000 | | | Expected | January | February | March |
| --- | --- | --- | --- |
| 180000 | 5000 | 25000 | 15000 |
| 450000 | 15000 | 20000 | 30000 |
| 45000 | 20000 | 30000 | 80000 |
| 150000 | 25000 | 10000 | 5000 |
| 35000 | 35000 | 5000 | 10000 |
| 50000 | 80000 | 40000 | 60000 |
| 200000 | 100000 | 50000 | 70000 |
| 70000 | 150000 | 200000 | 100000 | | 0 |
| Expected | January | February | March |
| --- | --- | --- | --- |
| 180000 | 80000 | 25000 | 15000 |
| 450000 | 100000 | 20000 | 30000 |
| 45000 | 25000 | 30000 | 80000 |
| 150000 | 15000 | 10000 | 5000 |
| 35000 | 150000 | 5000 | 10000 | | | 50000 | 5000 | 40000 | 60000 |
| --- | --- | --- | --- |
| 200000 | 20000 | 50000 | 70000 |
| 70000 | 35000 | 200000 | 100000 | | 1 |
| Expected | January | February | March |
| --- | --- | --- | --- |
| 180000 | 80000 | 25000 | 15000 |
| 450000 | 100000 | 20000 | 30000 |
| 45000 | 25000 | 30000 | 80000 |
| 150000 | 15000 | 10000 | 5000 |
| 35000 | 150000 | 5000 | 10000 | | | 450000 | 15000 | 20000 | 30000 |
| --- | --- | --- | --- |
| 45000 | 20000 | 30000 | 80000 |
| 150000 | 25000 | 10000 | 5000 |
| 35000 | 35000 | 5000 | 10000 |
| 50000 | 80000 | 40000 | 60000 |
| 200000 | 100000 | 50000 | 70000 |
| 70000 | 150000 | 200000 | 100000 | | 0 |
| block-size/sparsity | top-10 | top-20 | top-30 | top-40 |
| --- | --- | --- | --- | --- |
| 4x1/60 | 89.31 | 76.95 | 68.21 | 61.73 |
| 4x1/63,1x1/97 | 100 | 88.28 | 74.41 | 65.51 |
| 4x1/65,1x1/95 | 100 | 95.48 | 78.46 | 67.95 | | | 4x1/70,1x1/90 | 100 | 100 | 88.16 | 73.78 |
| --- | --- | --- | --- | --- |
| 4x1/80,1x1/80 | 100 | 100 | 100 | 84.29 | | 1 |
| block-size/sparsity | top-10 | top-20 | top-30 | top-40 |
| --- | --- | --- | --- | --- |
| 4x1/60 | 89.31 | 76.95 | 68.21 | 61.73 |
| 4x1/63,1x1/97 | 100 | 88.28 | 74.41 | 65.51 |
| 4x1/65,1x1/95 | 100 | 95.48 | 78.46 | 67.95 | | | Level-1<br>(Block-size/<br>sparsity) | Level-2<br>(Block-size/<br>sparsity) | Top-1Accuracy | Top-5Accuracy |
| --- | --- | --- | --- |
| 4x1/60 | – | 74.81(-1.32) | 92.26(-0.60) |
| 4x1/63 | 1x1/97 | 75.29(-0.84) | 92.57(-0.29) |
| 4x1/65 | 1x1/95 | 75.38(-0.75) | 92.57(-0.29) |
| 4x1/70 | 1x1/90 | 75.48(-0.65) | 92.66(-0.20) |
| 4x1/80 | 1x1/80 | 75.53(-0.60) | 92.77(-0.09) |
| – | 1x1/60 | 75.76(-0.37) | 92.85(-0.01) | | 0 |
| block-size/sparsity | top-10 | top-20 | top-30 | top-40 |
| --- | --- | --- | --- | --- |
| 4x1/60 | 89.31 | 76.95 | 68.21 | 61.73 | | | 4x1/63,1x1/97 | 100 | 88.28 | 74.41 | 65.51 |
| --- | --- | --- | --- | --- |
| 4x1/65,1x1/95 | 100 | 95.48 | 78.46 | 67.95 |
| 4x1/70,1x1/90 | 100 | 100 | 88.16 | 73.78 |
| 4x1/80,1x1/80 | 100 | 100 | 100 | 84.29 | | 1 |
| block-size/sparsity | top-10 | top-20 | top-30 | top-40 |
| --- | --- | --- | --- | --- |
| 4x1/60 | 89.31 | 76.95 | 68.21 | 61.73 | | | 4x1/63 | 1x1/97 | 75.29(-0.84) | 92.57(-0.29) |
| --- | --- | --- | --- |
| 4x1/65 | 1x1/95 | 75.38(-0.75) | 92.57(-0.29) |
| 4x1/70 | 1x1/90 | 75.48(-0.65) | 92.66(-0.20) |
| 4x1/80 | 1x1/80 | 75.53(-0.60) | 92.77(-0.09) |
| – | 1x1/60 | 75.76(-0.37) | 92.85(-0.01) | | 0 |
| Architecture | CIFAR-10(LR) | CIFAR-100(LR) |
| --- | --- | --- |
| ResNet | 92.8(0.1) | 71.2(0.1) |
| ResNet | 93.3(0.2) | 71.6(0.2) |
| ResNet | 91.8(0.3) | 71.9(0.3) |
| ResNet+CLR | 93.6(0.1−0.3) | 72.5(0.1−0.3) |
| SD | 94.6(0.1) | 75.2(0.1) | | | SD | 94.5(0.2) | 75.2(0.2) |
| --- | --- | --- |
| SD | 94.2(0.3) | 74.6(0.3) |
| SD+CLR | 94.5(0.1−0.3) | 75.4(0.1−0.3) |
| DenseNet | 94.5(0.1) | 75.2(0.1) |
| DenseNet | 94.5(0.2) | 75.3(0.2) |
| DenseNet | 94.2(0.3) | 74.5(0.3) |
| DenseNet+CLR | 94.9(0.1−0.2) | 75.9(0.1−0.2) | | 1 |
| Architecture | CIFAR-10(LR) | CIFAR-100(LR) |
| --- | --- | --- |
| ResNet | 92.8(0.1) | 71.2(0.1) |
| ResNet | 93.3(0.2) | 71.6(0.2) |
| ResNet | 91.8(0.3) | 71.9(0.3) |
| ResNet+CLR | 93.6(0.1−0.3) | 72.5(0.1−0.3) |
| SD | 94.6(0.1) | 75.2(0.1) | | | CIFAR-10 | Float | Binary | Ternary | | |
| --- | --- | --- | --- | --- | --- |
| BWN | Ours | TWN | Ours | | |
| VGG-11 | 91.93 | 88.70 | 89.28 | 90.48 | 91.01 |
| VGG-16 | 93.59 | 91.60 | 91.98 | 92.75 | 93.20 |
| ResNet-20 | 92.68 | 87.44 | 87.82 | 88.65 | 90.07 |
| ResNet-32 | 93.40 | 89.49 | 90.65 | 90.94 | 92.04 |
| ResNet-18 | 95.49 | 92.72 | 94.19 | 93.55 | 94.98 |
| ResNet-34 | 95.70 | 93.25 | 94.66 | 94.05 | 95.07 | | 0 |
| Architecture | CIFAR-10(LR) | CIFAR-100(LR) |
| --- | --- | --- |
| ResNet | 92.8(0.1) | 71.2(0.1) |
| ResNet | 93.3(0.2) | 71.6(0.2) | | | ResNet | 91.8(0.3) | 71.9(0.3) |
| --- | --- | --- |
| ResNet+CLR | 93.6(0.1−0.3) | 72.5(0.1−0.3) |
| SD | 94.6(0.1) | 75.2(0.1) |
| SD | 94.5(0.2) | 75.2(0.2) |
| SD | 94.2(0.3) | 74.6(0.3) |
| SD+CLR | 94.5(0.1−0.3) | 75.4(0.1−0.3) |
| DenseNet | 94.5(0.1) | 75.2(0.1) |
| DenseNet | 94.5(0.2) | 75.3(0.2) |
| DenseNet | 94.2(0.3) | 74.5(0.3) |
| DenseNet+CLR | 94.9(0.1−0.2) | 75.9(0.1−0.2) | | 1 |
| Architecture | CIFAR-10(LR) | CIFAR-100(LR) |
| --- | --- | --- |
| ResNet | 92.8(0.1) | 71.2(0.1) |
| ResNet | 93.3(0.2) | 71.6(0.2) | | | ResNet-32 | 93.40 | 89.49 | 90.65 | 90.94 | 92.04 |
| --- | --- | --- | --- | --- | --- |
| ResNet-18 | 95.49 | 92.72 | 94.19 | 93.55 | 94.98 |
| ResNet-34 | 95.70 | 93.25 | 94.66 | 94.05 | 95.07 | | 0 |
| Phase | NumberofUsers |
| --- | --- |
| Crawling3monthsofTweets | 50million | | | FilteringU.S.users | 6million |
| --- | --- |
| U.S.userswithprofileimage | 2million |
| U.S.userswithoneface(Baseline) | 1.6million |
| U.S.userswithcrawledtweets | 304thousand | | 1 |
| Phase | NumberofUsers |
| --- | --- |
| Crawling3monthsofTweets | 50million | | | Tweets | 196,985,580 |
| --- | --- |
| Users | 9,801,062 |
| Hashtags | 1,341,733 |
| TweetswithHashtags | 19,043,104 |
| Retweets | 15,126,588 |
| TweetswithURLs | 54,443,857 |
| Direct(@)Tweets | 41,951,786 | | 0 |
| Phase | NumberofUsers |
| --- | --- |
| Crawling3monthsofTweets | 50million |
| FilteringU.S.users | 6million | | | U.S.userswithprofileimage | 2million |
| --- | --- |
| U.S.userswithoneface(Baseline) | 1.6million |
| U.S.userswithcrawledtweets | 304thousand | | 1 |
| Phase | NumberofUsers |
| --- | --- |
| Crawling3monthsofTweets | 50million |
| FilteringU.S.users | 6million | | | Hashtags | 1,341,733 |
| --- | --- |
| TweetswithHashtags | 19,043,104 |
| Retweets | 15,126,588 |
| TweetswithURLs | 54,443,857 |
| Direct(@)Tweets | 41,951,786 | | 0 |
| n | Definitional | Pruning | PredictedRatio | ActualRatio |
| --- | --- | --- | --- | --- |
| 3 | 36 | 29 | 0.5 | 0.72 |
| 4 | 1,000 | 288 | 0.25 | 0.288 |
| 5 | 50,625 | 2,424 | 0.125 | 0.0478 | | | 6 | 4,084,101 | 18,479 | 0.0625 | 0.00452 |
| --- | --- | --- | --- | --- |
| 7 | 481,890,304 | 145,134 | 0.03125 | 0.000301 |
| 8 | 78,364,164,096 | 1,150,386 | 0.015625 | 0.0000147 | | 1 |
| n | Definitional | Pruning | PredictedRatio | ActualRatio |
| --- | --- | --- | --- | --- |
| 3 | 36 | 29 | 0.5 | 0.72 |
| 4 | 1,000 | 288 | 0.25 | 0.288 |
| 5 | 50,625 | 2,424 | 0.125 | 0.0478 | | | n | Definitional | Pruning | PredictedRatio | ActualRatio |
| --- | --- | --- | --- | --- |
| 4 | 120 | 44 | 0.25 | 0.36 |
| 5 | 1850 | 210 | 0.125 | 0.113 |
| 6 | 63,981 | 2,040 | 0.0625 | 0.0318 |
| 7 | 989,751 | 6,272 | 0.03125 | 0.00634 |
| 8 | 58,155,904 | 39,808 | 0.015625 | 0.000684 |
| 9 | | 198,300 | 0.0078125 | |
| 10 | | 1,933,147 | 0.00390625 | | | 0 |
| n | Definitional | Pruning | PredictedRatio | ActualRatio |
| --- | --- | --- | --- | --- |
| 3 | 36 | 29 | 0.5 | 0.72 | | | 4 | 1,000 | 288 | 0.25 | 0.288 |
| --- | --- | --- | --- | --- |
| 5 | 50,625 | 2,424 | 0.125 | 0.0478 |
| 6 | 4,084,101 | 18,479 | 0.0625 | 0.00452 |
| 7 | 481,890,304 | 145,134 | 0.03125 | 0.000301 |
| 8 | 78,364,164,096 | 1,150,386 | 0.015625 | 0.0000147 | | 1 |
| n | Definitional | Pruning | PredictedRatio | ActualRatio |
| --- | --- | --- | --- | --- |
| 3 | 36 | 29 | 0.5 | 0.72 | | | 9 | | 198,300 | 0.0078125 | |
| --- | --- | --- | --- | --- |
| 10 | | 1,933,147 | 0.00390625 | | | 0 |
| Combination | Pfd | Psd | Pas | Snns | Snn | Sns | Snsp |
| --- | --- | --- | --- | --- | --- | --- | --- |
| C1 | 50 | 50 | 100 | 22.4 | 36.6 | 16.2 | 24.8 |
| C2 | 50 | 70 | 100 | 31.5 | 27.7 | 22.7 | 18.1 | | | C3 | 20 | 70 | 100 | 14.5 | 11.9 | 41 | 32.6 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| C4 | 20 | 50 | 100 | 10 | 15.9 | 29.2 | 44.9 |
| C5 | 20 | 50 | 40 | 4 | 22 | 12 | 62 |
| C6 | 20 | 70 | 40 | 5 | 20 | 16 | 59 |
| C7 | 50 | 70 | 40 | 12 | 46 | 9 | 33 |
| C8 | 50 | 50 | 40 | 9 | 45 | 6 | 40 | | 1 |
| Combination | Pfd | Psd | Pas | Snns | Snn | Sns | Snsp |
| --- | --- | --- | --- | --- | --- | --- | --- |
| C1 | 50 | 50 | 100 | 22.4 | 36.6 | 16.2 | 24.8 |
| C2 | 50 | 70 | 100 | 31.5 | 27.7 | 22.7 | 18.1 | | | | GradualandSharp | | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| Video | TP | FP | FN | P | R | F |
| 01811a | 60 | 7 | 4 | 0.896 | 0.938 | 0.916 |
| 6011 | 40 | 96 | 81 | 0.294 | 0.331 | 0.311 |
| 8024 | 85 | 22 | 21 | 0.794 | 0.802 | 0.798 |
| 8386 | 113 | 10 | 5 | 0.919 | 0.958 | 0.938 |
| 8401 | 26 | 5 | 5 | 0.839 | 0.839 | 0.839 |
| 10558a | 122 | 1 | 8 | 0.992 | 0.938 | 0.964 |
| 23585a | 149 | 10 | 16 | 0.937 | 0.903 | 0.92 |
| 23585b | 103 | 3 | 1 | 0.972 | 0.99 | 0.981 |
| 34921a | 70 | 4 | 5 | 0.946 | 0.933 | 0.94 |
| 34921b | 91 | 10 | 8 | 0.901 | 0.919 | 0.91 |
| 36553 | 200 | 21 | 14 | 0.905 | 0.935 | 0.92 |
| 50009 | 44 | 28 | 14 | 0.611 | 0.759 | 0.677 |
| 50028 | 81 | 17 | 12 | 0.827 | 0.871 | 0.848 |
| UGS01 | 164 | 8 | 12 | 0.953 | 0.932 | 0.943 |
| UGS04 | 218 | 25 | 5 | 0.897 | 0.978 | 0.936 |
| UGS05 | 21 | 6 | 9 | 0.778 | 0.7 | 0.737 |
| UGS09 | 169 | 12 | 24 | 0.934 | 0.876 | 0.904 |
| Total | 1756 | 285 | 244 | 0.86 | 0.878 | 0.869 | | 0 |
| Combination | Pfd | Psd | Pas | Snns | Snn | Sns | Snsp |
| --- | --- | --- | --- | --- | --- | --- | --- |
| C1 | 50 | 50 | 100 | 22.4 | 36.6 | 16.2 | 24.8 |
| C2 | 50 | 70 | 100 | 31.5 | 27.7 | 22.7 | 18.1 |
| C3 | 20 | 70 | 100 | 14.5 | 11.9 | 41 | 32.6 |
| C4 | 20 | 50 | 100 | 10 | 15.9 | 29.2 | 44.9 | | | C5 | 20 | 50 | 40 | 4 | 22 | 12 | 62 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| C6 | 20 | 70 | 40 | 5 | 20 | 16 | 59 |
| C7 | 50 | 70 | 40 | 12 | 46 | 9 | 33 |
| C8 | 50 | 50 | 40 | 9 | 45 | 6 | 40 | | 1 |
| Combination | Pfd | Psd | Pas | Snns | Snn | Sns | Snsp |
| --- | --- | --- | --- | --- | --- | --- | --- |
| C1 | 50 | 50 | 100 | 22.4 | 36.6 | 16.2 | 24.8 |
| C2 | 50 | 70 | 100 | 31.5 | 27.7 | 22.7 | 18.1 |
| C3 | 20 | 70 | 100 | 14.5 | 11.9 | 41 | 32.6 |
| C4 | 20 | 50 | 100 | 10 | 15.9 | 29.2 | 44.9 | | | UGS05 | 21 | 6 | 9 | 0.778 | 0.7 | 0.737 |
| --- | --- | --- | --- | --- | --- | --- |
| UGS09 | 169 | 12 | 24 | 0.934 | 0.876 | 0.904 |
| Total | 1756 | 285 | 244 | 0.86 | 0.878 | 0.869 | | 0 |
| Group | 4 | 5 | 6 | 7 | 8 | 9 | 11 | 12 | 13 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | 23 | 52 | 76 | 104 | 129 | 153 | 185 | 235 | 261 |
| 2 | 9 | 52 | 76 | 104 | 129 | 153 | 185 | 235 | 261 |
| 3 | 15 | 58 | 76 | 120 | 129 | 153 | 198 | 235 | 247 |
| 4 | 23 | 58 | 76 | 120 | 129 | 178 | 185 | 235 | 261 |
| 5 | 23 | 52 | 76 | 120 | 129 | 178 | 208 | 235 | 261 |
| 6 | 23 | 58 | 76 | 111 | 129 | 178 | 196 | 224 | 261 |
| 7 | 23 | 58 | 76 | 120 | 129 | 178 | 208 | 235 | 261 |
| 8 | 23 | 52 | 76 | 120 | 129 | 178 | 208 | 235 | 261 |
| 9 | 23 | 58 | 76 | 104 | 129 | 153 | 195 | 235 | 247 |
| 10 | 23 | 58 | 76 | 120 | 129 | 178 | 208 | 224 | 261 |
| 11 | 23 | 58 | 76 | 104 | 129 | 178 | 208 | 235 | 261 | | | 12 | 23 | 37 | 76 | 120 | 129 | 154 | 208 | 235 | 261 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 13 | 23 | 58 | 76 | 104 | 129 | 153 | 195 | 235 | 261 | | 1 |
| Group | 4 | 5 | 6 | 7 | 8 | 9 | 11 | 12 | 13 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | 23 | 52 | 76 | 104 | 129 | 153 | 185 | 235 | 261 |
| 2 | 9 | 52 | 76 | 104 | 129 | 153 | 185 | 235 | 261 |
| 3 | 15 | 58 | 76 | 120 | 129 | 153 | 198 | 235 | 247 |
| 4 | 23 | 58 | 76 | 120 | 129 | 178 | 185 | 235 | 261 |
| 5 | 23 | 52 | 76 | 120 | 129 | 178 | 208 | 235 | 261 |
| 6 | 23 | 58 | 76 | 111 | 129 | 178 | 196 | 224 | 261 |
| 7 | 23 | 58 | 76 | 120 | 129 | 178 | 208 | 235 | 261 |
| 8 | 23 | 52 | 76 | 120 | 129 | 178 | 208 | 235 | 261 |
| 9 | 23 | 58 | 76 | 104 | 129 | 153 | 195 | 235 | 247 |
| 10 | 23 | 58 | 76 | 120 | 129 | 178 | 208 | 224 | 261 |
| 11 | 23 | 58 | 76 | 104 | 129 | 178 | 208 | 235 | 261 | | | 16 | 11 | 10 | 16 | 24 | 40 | 51 | 61 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| 12 | 12 | 14 | 19 | 26 | 58 | 60 | 55 |
| 14 | 13 | 16 | 24 | 40 | 57 | 69 | 56 |
| 14 | 17 | 22 | 29 | 51 | 87 | 80 | 62 |
| 18 | 22 | 37 | 56 | 68 | 109 | 103 | 77 |
| 24 | 35 | 55 | 64 | 81 | 104 | 113 | 92 |
| 49 | 64 | 78 | 87 | 103 | 121 | 120 | 101 |
| 72 | 92 | 95 | 98 | 112 | 100 | 103 | 99 | | 0 |
| Group | 4 | 5 | 6 | 7 | 8 | 9 | 11 | 12 | 13 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | 23 | 52 | 76 | 104 | 129 | 153 | 185 | 235 | 261 |
| 2 | 9 | 52 | 76 | 104 | 129 | 153 | 185 | 235 | 261 | | | 3 | 15 | 58 | 76 | 120 | 129 | 153 | 198 | 235 | 247 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 4 | 23 | 58 | 76 | 120 | 129 | 178 | 185 | 235 | 261 |
| 5 | 23 | 52 | 76 | 120 | 129 | 178 | 208 | 235 | 261 |
| 6 | 23 | 58 | 76 | 111 | 129 | 178 | 196 | 224 | 261 |
| 7 | 23 | 58 | 76 | 120 | 129 | 178 | 208 | 235 | 261 |
| 8 | 23 | 52 | 76 | 120 | 129 | 178 | 208 | 235 | 261 |
| 9 | 23 | 58 | 76 | 104 | 129 | 153 | 195 | 235 | 247 |
| 10 | 23 | 58 | 76 | 120 | 129 | 178 | 208 | 224 | 261 |
| 11 | 23 | 58 | 76 | 104 | 129 | 178 | 208 | 235 | 261 |
| 12 | 23 | 37 | 76 | 120 | 129 | 154 | 208 | 235 | 261 |
| 13 | 23 | 58 | 76 | 104 | 129 | 153 | 195 | 235 | 261 | | 1 |
| Group | 4 | 5 | 6 | 7 | 8 | 9 | 11 | 12 | 13 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 1 | 23 | 52 | 76 | 104 | 129 | 153 | 185 | 235 | 261 |
| 2 | 9 | 52 | 76 | 104 | 129 | 153 | 185 | 235 | 261 | | | 14 | 13 | 16 | 24 | 40 | 57 | 69 | 56 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| 14 | 17 | 22 | 29 | 51 | 87 | 80 | 62 |
| 18 | 22 | 37 | 56 | 68 | 109 | 103 | 77 |
| 24 | 35 | 55 | 64 | 81 | 104 | 113 | 92 |
| 49 | 64 | 78 | 87 | 103 | 121 | 120 | 101 |
| 72 | 92 | 95 | 98 | 112 | 100 | 103 | 99 | | 0 |
| category | ours | | | |
| --- | --- | --- | --- | --- |
| bathtub | 0.8348 | 0.7017 | 0.7190 | 0.1644 | | | bed | 0.9202 | 0.7775 | 0.3963 | 0.3239 |
| --- | --- | --- | --- | --- |
| chair | 0.9920 | 0.9700 | 0.9892 | 0.8482 |
| desk | 0.8203 | 0.7936 | 0.8145 | 0.1068 |
| dresser | 0.7678 | 0.6314 | 0.7010 | 0.2166 |
| monitor | 0.9473 | 0.2493 | 0.8559 | 0.2767 |
| nightstand | 0.7195 | 0.6853 | 0.6592 | 0.4969 |
| sofa | 0.9480 | 0.9276 | 0.3017 | 0.4888 |
| table | 0.8910 | 0.8377 | 0.8751 | 0.7902 |
| toilet | 0.9701 | 0.8569 | 0.6943 | 0.8832 |
| Avg. | 0.8811 | 0.7431 | 0.7006 | 0.4596 | | 1 |
| category | ours | | | |
| --- | --- | --- | --- | --- |
| bathtub | 0.8348 | 0.7017 | 0.7190 | 0.1644 | | | category | ours | | |
| --- | --- | --- | --- |
| bathtub | 0.0152 | 0.0266 | 0.0621 |
| bed | 0.0068 | 0.0240 | 0.0617 |
| chair | 0.0118 | 0.0238 | 0.0444 |
| desk | 0.0122 | 0.0298 | 0.0731 |
| dresser | 0.0038 | 0.0384 | 0.1558 |
| monitor | 0.0103 | 0.0220 | 0.0783 |
| nightstand | 0.0080 | 0.0248 | 0.2925 |
| sofa | 0.0068 | 0.0186 | 0.0563 |
| table | 0.0051 | 0.0326 | 0.0340 |
| toilet | 0.0119 | 0.0180 | 0.0977 |
| Avg. | 0.0092 | 0.0259 | 0.0956 | | 0 |
| category | ours | | | |
| --- | --- | --- | --- | --- |
| bathtub | 0.8348 | 0.7017 | 0.7190 | 0.1644 |
| bed | 0.9202 | 0.7775 | 0.3963 | 0.3239 |
| chair | 0.9920 | 0.9700 | 0.9892 | 0.8482 |
| desk | 0.8203 | 0.7936 | 0.8145 | 0.1068 |
| dresser | 0.7678 | 0.6314 | 0.7010 | 0.2166 | | | monitor | 0.9473 | 0.2493 | 0.8559 | 0.2767 |
| --- | --- | --- | --- | --- |
| nightstand | 0.7195 | 0.6853 | 0.6592 | 0.4969 |
| sofa | 0.9480 | 0.9276 | 0.3017 | 0.4888 |
| table | 0.8910 | 0.8377 | 0.8751 | 0.7902 |
| toilet | 0.9701 | 0.8569 | 0.6943 | 0.8832 |
| Avg. | 0.8811 | 0.7431 | 0.7006 | 0.4596 | | 1 |
| category | ours | | | |
| --- | --- | --- | --- | --- |
| bathtub | 0.8348 | 0.7017 | 0.7190 | 0.1644 |
| bed | 0.9202 | 0.7775 | 0.3963 | 0.3239 |
| chair | 0.9920 | 0.9700 | 0.9892 | 0.8482 |
| desk | 0.8203 | 0.7936 | 0.8145 | 0.1068 |
| dresser | 0.7678 | 0.6314 | 0.7010 | 0.2166 | | | bed | 0.0068 | 0.0240 | 0.0617 |
| --- | --- | --- | --- |
| chair | 0.0118 | 0.0238 | 0.0444 |
| desk | 0.0122 | 0.0298 | 0.0731 |
| dresser | 0.0038 | 0.0384 | 0.1558 |
| monitor | 0.0103 | 0.0220 | 0.0783 |
| nightstand | 0.0080 | 0.0248 | 0.2925 |
| sofa | 0.0068 | 0.0186 | 0.0563 |
| table | 0.0051 | 0.0326 | 0.0340 |
| toilet | 0.0119 | 0.0180 | 0.0977 |
| Avg. | 0.0092 | 0.0259 | 0.0956 | | 0 |
| NetworkgroupID | N | minc | maxc | µ | On |
| --- | --- | --- | --- | --- | --- |
| N1 | 1000 | 10 | 50 | 0-0.5 | 100 |
| N2 | 1000 | 20 | 100 | 0-0.5 | 100 |
| N3 | 5000 | 10 | 50 | 0-0.5 | 500 |
| N4 | 5000 | 20 | 100 | 0-0.5 | 500 |
| N5 | 1000 | 10 | 50 | 0.1 | 0-500 |
| N6 | 1000 | 20 | 100 | 0.1 | 0-500 | | | N7 | 5000 | 10 | 50 | 0.1 | 0-2000 |
| --- | --- | --- | --- | --- | --- |
| N8 | 5000 | 20 | 100 | 0.1 | 0-2000 | | 1 |
| NetworkgroupID | N | minc | maxc | µ | On |
| --- | --- | --- | --- | --- | --- |
| N1 | 1000 | 10 | 50 | 0-0.5 | 100 |
| N2 | 1000 | 20 | 100 | 0-0.5 | 100 |
| N3 | 5000 | 10 | 50 | 0-0.5 | 500 |
| N4 | 5000 | 20 | 100 | 0-0.5 | 500 |
| N5 | 1000 | 10 | 50 | 0.1 | 0-500 |
| N6 | 1000 | 20 | 100 | 0.1 | 0-500 | | | 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 | 1 | 24 | 0.9540 | 0.9673 | 28KB | 43.15FPS | APN24 | 3 | 24 | 0.9851 |
| APN24 | 1 | 16 | 0.9872 | 0.9910 | 360KB | 22.91FPS | APN12 | 2 | 16 | 0.9598 |
| 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 |
| APN24 | 2 | 20 | 0.9888 | 0.9921 | 360KB | 29.68FPS | APN24(S) | 2 | 20 | 0.9604 |
| APN24 | 2 | 24 | 0.9859 | 0.9901 | 360KB | 38.02FPS | APN24(S) | 2 | 24 | 0.9564 | | 0 |
| NetworkgroupID | N | minc | maxc | µ | On |
| --- | --- | --- | --- | --- | --- |
| N1 | 1000 | 10 | 50 | 0-0.5 | 100 |
| N2 | 1000 | 20 | 100 | 0-0.5 | 100 |
| N3 | 5000 | 10 | 50 | 0-0.5 | 500 |
| N4 | 5000 | 20 | 100 | 0-0.5 | 500 |
| N5 | 1000 | 10 | 50 | 0.1 | 0-500 | | | N6 | 1000 | 20 | 100 | 0.1 | 0-500 |
| --- | --- | --- | --- | --- | --- |
| N7 | 5000 | 10 | 50 | 0.1 | 0-2000 |
| N8 | 5000 | 20 | 100 | 0.1 | 0-2000 | | 1 |
| NetworkgroupID | N | minc | maxc | µ | On |
| --- | --- | --- | --- | --- | --- |
| N1 | 1000 | 10 | 50 | 0-0.5 | 100 |
| N2 | 1000 | 20 | 100 | 0-0.5 | 100 |
| N3 | 5000 | 10 | 50 | 0-0.5 | 500 |
| N4 | 5000 | 20 | 100 | 0-0.5 | 500 |
| N5 | 1000 | 10 | 50 | 0.1 | 0-500 | | | APN24 | 2 | 20 | 0.9888 | 0.9921 | 360KB | 29.68FPS | APN24(S) | 2 | 20 | 0.9604 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| APN24 | 2 | 24 | 0.9859 | 0.9901 | 360KB | 38.02FPS | APN24(S) | 2 | 24 | 0.9564 | | 0 |
| Topology | Size | Detection | Cost |
| --- | --- | --- | --- |
| Ring | 9 | nodetection | 0.050 |
| outlier | 0.276 | | | | | fault | 0.921 | | |
| --- | --- | --- | --- |
| 25 | nodetection | 0.101 | |
| outlier | 1.131 | | |
| fault | 3.286 | | |
| Torus | 9 | nodetection | 0.027 |
| outlier | 0.121 | | |
| fault | 1.327 | | |
| 25 | nodetection | 0.043 | |
| outlier | 0.567 | | |
| fault | 6.055 | | |
| Petersen | 10 | nodetection | 0.005 |
| outlier | 0.135 | | |
| fault | 0.597 | | |
| Random | 10 | nodetection | 0.013 |
| outlier | 0.290 | | |
| fault | 1.268 | | | | 1 |
| Topology | Size | Detection | Cost |
| --- | --- | --- | --- |
| Ring | 9 | nodetection | 0.050 |
| outlier | 0.276 | | | | | Feature | Non-toptier | Toptier | | |
| --- | --- | --- | --- | --- |
| Mean | Std.Dev. | Mean | Std.Dev. | |
| CRDI | 0.25 | 0.259 | 0.173 | 0.178 |
| CKDI | 0.536 | 0.504 | 0.396 | 0.419 |
| CADI | 0.121 | 0.146 | 0.076 | 0.068 |
| PNA | 0.1 | 0.077 | 0.097 | 0.068 |
| CAAI | 0.206 | 0.232 | 0.175 | 0.16 |
| DDI | 0.386 | 0.323 | 0.335 | 0.28 |
| EDI | 0.323 | 0.292 | 0.23 | 0.265 |
| ACC | 0.02 | 0.034 | 0.018 | 0.019 |
| ABC | 0.034 | 0.087 | 0.015 | 0.034 | | 0 |
| Topology | Size | Detection | Cost |
| --- | --- | --- | --- |
| Ring | 9 | nodetection | 0.050 |
| outlier | 0.276 | | |
| fault | 0.921 | | |
| 25 | nodetection | 0.101 | | | | outlier | 1.131 | | |
| --- | --- | --- | --- |
| fault | 3.286 | | |
| Torus | 9 | nodetection | 0.027 |
| outlier | 0.121 | | |
| fault | 1.327 | | |
| 25 | nodetection | 0.043 | |
| outlier | 0.567 | | |
| fault | 6.055 | | |
| Petersen | 10 | nodetection | 0.005 |
| outlier | 0.135 | | |
| fault | 0.597 | | |
| Random | 10 | nodetection | 0.013 |
| outlier | 0.290 | | |
| fault | 1.268 | | | | 1 |
| Topology | Size | Detection | Cost |
| --- | --- | --- | --- |
| Ring | 9 | nodetection | 0.050 |
| outlier | 0.276 | | |
| fault | 0.921 | | |
| 25 | nodetection | 0.101 | | | | PNA | 0.1 | 0.077 | 0.097 | 0.068 |
| --- | --- | --- | --- | --- |
| CAAI | 0.206 | 0.232 | 0.175 | 0.16 |
| DDI | 0.386 | 0.323 | 0.335 | 0.28 |
| EDI | 0.323 | 0.292 | 0.23 | 0.265 |
| ACC | 0.02 | 0.034 | 0.018 | 0.019 |
| ABC | 0.034 | 0.087 | 0.015 | 0.034 | | 0 |
| h | Compression | Distortion |
| --- | --- | --- |
| 1 | 49 | 0.135196 | | | 2 | 24.5 | 0.124725 |
| --- | --- | --- |
| 3 | 16.33333333 | 0.0947032 |
| 5 | 9.8 | 0.0354035 |
| 7 | 7 | 0.031808 |
| 20 | 2.45 | 0.0149272 | | 1 |
| h | Compression | Distortion |
| --- | --- | --- |
| 1 | 49 | 0.135196 | | | compression<br>ratio |
| --- |
| 0.76 |
| 0.43 |
| 0.26 |
| 0.18 |
| 0.14 |
| 0.12 | | 0 |
| h | Compression | Distortion |
| --- | --- | --- |
| 1 | 49 | 0.135196 |
| 2 | 24.5 | 0.124725 |
| 3 | 16.33333333 | 0.0947032 |
| 5 | 9.8 | 0.0354035 | | | 7 | 7 | 0.031808 |
| --- | --- | --- |
| 20 | 2.45 | 0.0149272 | | 1 |
| h | Compression | Distortion |
| --- | --- | --- |
| 1 | 49 | 0.135196 |
| 2 | 24.5 | 0.124725 |
| 3 | 16.33333333 | 0.0947032 |
| 5 | 9.8 | 0.0354035 | | | 0.18 |
| --- |
| 0.14 |
| 0.12 | | 0 |
| n | degree | closeness | betweenness | random-walk |
| --- | --- | --- | --- | --- |
| 1 | {11} | {11} | {11} | {11} |
| 2 | {4,11} | {2,13},{4,11} | {4,11} | {4,11} | | | 3 | {0,11,13},{4,11,13},...(9) | {0,11,13},{4,11,13},...(4) | {4,11,13} | {0,11,13} |
| --- | --- | --- | --- | --- |
| 4 | {2,4,11,13},...(23) | {2,4,11,13},...(5) | {2,4,11,13} | {2,4,11,13} | | 1 |
| n | degree | closeness | betweenness | random-walk |
| --- | --- | --- | --- | --- |
| 1 | {11} | {11} | {11} | {11} |
| 2 | {4,11} | {2,13},{4,11} | {4,11} | {4,11} | | | n | degree | closeness | betweenness | random-walk |
| --- | --- | --- | --- | --- |
| 1 | {29},...(1) | {15} | {1} | {29} |
| 2 | {2,29} | {0,15},...(1) | {1,2} | {29,39} |
| 3 | {2,8,29},...(3) | {0,15,32},...(7) | {1,2,8} | {2,8,39} |
| 4 | {2,8,29,39},...(2) | {2,26,29,39},...(1) | {2,8,10,29} | {2,26,29,39} | | 0 |
| n | degree | closeness | betweenness | random-walk |
| --- | --- | --- | --- | --- |
| 1 | {11} | {11} | {11} | {11} |
| 2 | {4,11} | {2,13},{4,11} | {4,11} | {4,11} | | | 3 | {0,11,13},{4,11,13},...(9) | {0,11,13},{4,11,13},...(4) | {4,11,13} | {0,11,13} |
| --- | --- | --- | --- | --- |
| 4 | {2,4,11,13},...(23) | {2,4,11,13},...(5) | {2,4,11,13} | {2,4,11,13} | | 1 |
| n | degree | closeness | betweenness | random-walk |
| --- | --- | --- | --- | --- |
| 1 | {11} | {11} | {11} | {11} |
| 2 | {4,11} | {2,13},{4,11} | {4,11} | {4,11} | | | 3 | {2,8,29},...(3) | {0,15,32},...(7) | {1,2,8} | {2,8,39} |
| --- | --- | --- | --- | --- |
| 4 | {2,8,29,39},...(2) | {2,26,29,39},...(1) | {2,8,10,29} | {2,26,29,39} | | 0 |
| Topics | Question | | | |
| --- | --- | --- | --- | --- |
| Q7 | Q8 | | | |
| NumberofYES | Ranking | NumberofYES | Ranking | |
| T1 | 6 | 2 | 3 | 5 |
| T2 | 5 | 3 | 2 | 8 |
| T3 | 7 | 1 | 5 | 2 |
| T4 | 4 | 4 | 3 | 5 |
| T5 | 3 | 6 | 3 | 5 | | | T6 | 4 | 4 | 1 | 9 |
| --- | --- | --- | --- | --- |
| T7 | 0 | (7) | 4 | 4 |
| T8 | 0 | (7) | 7 | 1 |
| T9 | 0 | (7) | 5 | 2 | | 1 |
| Topics | Question | | | |
| --- | --- | --- | --- | --- |
| Q7 | Q8 | | | |
| NumberofYES | Ranking | NumberofYES | Ranking | |
| T1 | 6 | 2 | 3 | 5 |
| T2 | 5 | 3 | 2 | 8 |
| T3 | 7 | 1 | 5 | 2 |
| T4 | 4 | 4 | 3 | 5 |
| T5 | 3 | 6 | 3 | 5 | | | Rank | Numberofparticipants | Topic |
| --- | --- | --- |
| 1 | 4,35M | humor |
| 2 | 4,10M | humor |
| 3 | 3,76M | movies |
| 4 | 3,69M | humor |
| 5 | 3,59M | humor |
| 6 | 3,58M | facts |
| 7 | 3,36M | cookery |
| 8 | 3,31M | humor |
| 9 | 3,14M | humor |
| 10 | 3,14M | movies |
| 100 | 1,65M | successstories | | 0 |
| Topics | Question | | | |
| --- | --- | --- | --- | --- |
| Q7 | Q8 | | | |
| NumberofYES | Ranking | NumberofYES | Ranking | |
| T1 | 6 | 2 | 3 | 5 |
| T2 | 5 | 3 | 2 | 8 |
| T3 | 7 | 1 | 5 | 2 |
| T4 | 4 | 4 | 3 | 5 | | | T5 | 3 | 6 | 3 | 5 |
| --- | --- | --- | --- | --- |
| T6 | 4 | 4 | 1 | 9 |
| T7 | 0 | (7) | 4 | 4 |
| T8 | 0 | (7) | 7 | 1 |
| T9 | 0 | (7) | 5 | 2 | | 1 |
| Topics | Question | | | |
| --- | --- | --- | --- | --- |
| Q7 | Q8 | | | |
| NumberofYES | Ranking | NumberofYES | Ranking | |
| T1 | 6 | 2 | 3 | 5 |
| T2 | 5 | 3 | 2 | 8 |
| T3 | 7 | 1 | 5 | 2 |
| T4 | 4 | 4 | 3 | 5 | | | 7 | 3,36M | cookery |
| --- | --- | --- |
| 8 | 3,31M | humor |
| 9 | 3,14M | humor |
| 10 | 3,14M | movies |
| 100 | 1,65M | successstories | | 0 |
| Method | Protein | DNA | Music | Sports |
| --- | --- | --- | --- | --- |
| ESP+SFM(D=128)<br>ESP+FM(D=128) | 7.054(±5.320)<br>7.055(±5.321) | 7.051(±5.318)<br>7.054(±2.664) | 7.058(±5.318)<br>7.059(±5.318) | 7.058(±5.319)<br>7.059(±5.320) |
| ESP+SFM(D=512)<br>ESP+FM(D=512) | 3.523(±2.662)<br>3.526(±2.665) | 3.526(±2.663)<br>3.526(±2.666) | 3.526(±2.662)<br>3.526(±2.663) | 3.525(±2.662)<br>3.526(±2.663) |
| ESP+SFM(D=2048)<br>ESP+FM(D=2048) | 1.762(±1.332)<br>1.763(±1.332) | 1.762(±1.332)<br>1.762(±1.332) | 1.762(±1.332)<br>1.762(±1.331) | 1.762(±1.332)<br>1.763(±1.331) | | | ESP+SFM(D=8192)<br>ESP+FM(D=8192) | 0.881(±0.666)<br>0.880(±0.666) | 0.881(±0.665)<br>0.881(±0.666) | 0.879(±0.665)<br>0.881(±0.666) | 0.881(±0.665)<br>0.881(±0.666) |
| --- | --- | --- | --- | --- |
| ESP+SFM(D=16384)<br>ESP+FM(D=16384) | 0.623(±0.471)<br>0.628(±0.470) | 0.623(±0.470)<br>0.623(±0.471) | 0.621(±0.470)<br>0.623(±0.471) | 0.623(±0.470)<br>0.623(±0.471) | | 1 |
| Method | Protein | DNA | Music | Sports |
| --- | --- | --- | --- | --- |
| ESP+SFM(D=128)<br>ESP+FM(D=128) | 7.054(±5.320)<br>7.055(±5.321) | 7.051(±5.318)<br>7.054(±2.664) | 7.058(±5.318)<br>7.059(±5.318) | 7.058(±5.319)<br>7.059(±5.320) |
| ESP+SFM(D=512)<br>ESP+FM(D=512) | 3.523(±2.662)<br>3.526(±2.665) | 3.526(±2.663)<br>3.526(±2.666) | 3.526(±2.662)<br>3.526(±2.663) | 3.525(±2.662)<br>3.526(±2.663) |
| ESP+SFM(D=2048)<br>ESP+FM(D=2048) | 1.762(±1.332)<br>1.763(±1.332) | 1.762(±1.332)<br>1.762(±1.332) | 1.762(±1.332)<br>1.762(±1.331) | 1.762(±1.332)<br>1.763(±1.331) | | | Method | Protein | DNA | Music | Sports |
| --- | --- | --- | --- | --- |
| CGK+SFM(D=128)<br>CGK+FM(D=128) | 7.056(±5.319)<br>7.054(±5.316) | 7.051(±5.318)<br>7.055(±5.322) | 7.059(±5.320)<br>7.059(±5.319) | 7.057(±5.319)<br>7.057(±5.319) |
| CGK+SFM(D=512)<br>CGK+FM(D=512) | 3.524(±2.662)<br>3.523(±2.664) | 3.526(±2.663)<br>3.526(±2.664) | 3.526(±2.662)<br>3.527(±2.661) | 3.525(±2.662)<br>3.525(±2.662) |
| CGK+SFM(D=2048)<br>CGK+FM(D=2048) | 1.761(±1.331)<br>1.762(±1.332) | 1.762(±1.332)<br>1.761(±1.331) | 1.763(±1.332)<br>1.332(±1.763) | 1.763(±1.332)<br>1.762(±1.331) |
| CGK+SFM(D=8192)<br>CGK+FM(D=8192) | 0.881(±0.662)<br>0.881(±0.666) | 0.881(±0.665)<br>0.881(±0.666) | 0.881(±0.665)<br>0.881(±0.666) | 0.881(±0.665)<br>0.881(±0.665) |
| CGK+SFM(D=16384)<br>CGK+FM(D=16384) | 0.623(±0.471)<br>0.623(±0.471) | 0.623(±0.470)<br>0.623(±0.470) | 0.632(±0.470)<br>0.632(±0.471) | 0.623(±0.470)<br>0.623(±0.470) | | 0 |
| Method | Protein | DNA | Music | Sports |
| --- | --- | --- | --- | --- |
| ESP+SFM(D=128)<br>ESP+FM(D=128) | 7.054(±5.320)<br>7.055(±5.321) | 7.051(±5.318)<br>7.054(±2.664) | 7.058(±5.318)<br>7.059(±5.318) | 7.058(±5.319)<br>7.059(±5.320) |
| ESP+SFM(D=512)<br>ESP+FM(D=512) | 3.523(±2.662)<br>3.526(±2.665) | 3.526(±2.663)<br>3.526(±2.666) | 3.526(±2.662)<br>3.526(±2.663) | 3.525(±2.662)<br>3.526(±2.663) | | | ESP+SFM(D=2048)<br>ESP+FM(D=2048) | 1.762(±1.332)<br>1.763(±1.332) | 1.762(±1.332)<br>1.762(±1.332) | 1.762(±1.332)<br>1.762(±1.331) | 1.762(±1.332)<br>1.763(±1.331) |
| --- | --- | --- | --- | --- |
| ESP+SFM(D=8192)<br>ESP+FM(D=8192) | 0.881(±0.666)<br>0.880(±0.666) | 0.881(±0.665)<br>0.881(±0.666) | 0.879(±0.665)<br>0.881(±0.666) | 0.881(±0.665)<br>0.881(±0.666) |
| ESP+SFM(D=16384)<br>ESP+FM(D=16384) | 0.623(±0.471)<br>0.628(±0.470) | 0.623(±0.470)<br>0.623(±0.471) | 0.621(±0.470)<br>0.623(±0.471) | 0.623(±0.470)<br>0.623(±0.471) | | 1 |
| Method | Protein | DNA | Music | Sports |
| --- | --- | --- | --- | --- |
| ESP+SFM(D=128)<br>ESP+FM(D=128) | 7.054(±5.320)<br>7.055(±5.321) | 7.051(±5.318)<br>7.054(±2.664) | 7.058(±5.318)<br>7.059(±5.318) | 7.058(±5.319)<br>7.059(±5.320) |
| ESP+SFM(D=512)<br>ESP+FM(D=512) | 3.523(±2.662)<br>3.526(±2.665) | 3.526(±2.663)<br>3.526(±2.666) | 3.526(±2.662)<br>3.526(±2.663) | 3.525(±2.662)<br>3.526(±2.663) | | | CGK+SFM(D=2048)<br>CGK+FM(D=2048) | 1.761(±1.331)<br>1.762(±1.332) | 1.762(±1.332)<br>1.761(±1.331) | 1.763(±1.332)<br>1.332(±1.763) | 1.763(±1.332)<br>1.762(±1.331) |
| --- | --- | --- | --- | --- |
| CGK+SFM(D=8192)<br>CGK+FM(D=8192) | 0.881(±0.662)<br>0.881(±0.666) | 0.881(±0.665)<br>0.881(±0.666) | 0.881(±0.665)<br>0.881(±0.666) | 0.881(±0.665)<br>0.881(±0.665) |
| CGK+SFM(D=16384)<br>CGK+FM(D=16384) | 0.623(±0.471)<br>0.623(±0.471) | 0.623(±0.470)<br>0.623(±0.470) | 0.632(±0.470)<br>0.632(±0.471) | 0.623(±0.470)<br>0.623(±0.470) | | 0 |
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