premise string | hypothesis string | label int64 |
|---|---|---|
| | 1Node | 2Nodes | 4Nodes | 8Nodes | 16Nodes |
| --- | --- | --- | --- | --- | --- |
| Q1 | 47.71 | 45.32 | 47.41 | 46.83 | 49.1 |
| Q2 | 107.05 | 65.95 | 68.29 | 53.16 | 55.93 |
| Q3 | 620.57 | 498.45 | 312.17 | 195.13 | 135.73 |
| Q4 | 208.51 | 142.12 | 136.69 | 130.51 | 125.60 |
| Q5 | 539.37 | 437.27 | 264.13 | 179.18 | 131.98 |
| Q6 | 220.29 | 133.08 | 108.56 | 77.02 | 67.42 |
| Q7 | 35.96 | 33.15 | 33.64 | 36.12 | 34.44 |
| Q9 | 575.29 | 310.14 | 297.75 | 190.08 | 145.75 |
| Q10 | 36.68 | 32.03 | 34.04 | 36.00 | 33.91 |
| Q11 | 580.72 | 412.59 | 300.78 | 183.67 | 138.56 |
| Q12 | 99.04 | 61.24 | 48.05 | 47.07 | 42.52 |
| Q13 | 575.09 | 402.15 | 291.11 | 186.86 | 120.88 |
| Q14 | 47.66 | 45.92 | 48.03 | 46.61 | 47.36 |
| Q15 | 36.90 | 32.04 | 36.53 | 36.06 | 35.46 | | | Q16 | 610.85 | 387.59 | 315.06 | 202.07 | 149.09 |
| --- | --- | --- | --- | --- | --- |
| Q17 | NaN | NaN | NaN | NaN | NaN |
| Q18 | 35.88 | 32.05 | 36.69 | 35.00 | 34.23 |
| Q19 | 597.83 | 499.11 | 305.14 | 196.61 | 140.85 |
| Q20 | 607.89 | 336.38 | 316.46 | 194.37 | 140.92 | | 1 |
| | 1Node | 2Nodes | 4Nodes | 8Nodes | 16Nodes |
| --- | --- | --- | --- | --- | --- |
| Q1 | 47.71 | 45.32 | 47.41 | 46.83 | 49.1 |
| Q2 | 107.05 | 65.95 | 68.29 | 53.16 | 55.93 |
| Q3 | 620.57 | 498.45 | 312.17 | 195.13 | 135.73 |
| Q4 | 208.51 | 142.12 | 136.69 | 130.51 | 125.60 |
| Q5 | 539.37 | 437.27 | 264.13 | 179.18 | 131.98 |
| Q6 | 220.29 | 133.08 | 108.56 | 77.02 | 67.42 |
| Q7 | 35.96 | 33.15 | 33.64 | 36.12 | 34.44 |
| Q9 | 575.29 | 310.14 | 297.75 | 190.08 | 145.75 |
| Q10 | 36.68 | 32.03 | 34.04 | 36.00 | 33.91 |
| Q11 | 580.72 | 412.59 | 300.78 | 183.67 | 138.56 |
| Q12 | 99.04 | 61.24 | 48.05 | 47.07 | 42.52 |
| Q13 | 575.09 | 402.15 | 291.11 | 186.86 | 120.88 |
| Q14 | 47.66 | 45.92 | 48.03 | 46.61 | 47.36 |
| Q15 | 36.90 | 32.04 | 36.53 | 36.06 | 35.46 | | | | 1Node | 2Nodes | 4Nodes | 8Nodes | 16Nodes |
| --- | --- | --- | --- | --- | --- |
| Q1 | 395.82 | 254.49 | 307.9 | 215.35 | 146.35 |
| Q2 | 181.91 | 165.32 | 160.97 | 150.87 | 144.49 |
| Q3 | 354.55 | 192.83 | 231.96 | 156.26 | 106.05 |
| Q4 | 705.96 | 737.82 | 725.21 | 292.48 | 196.56 |
| Q5 | 178.55 | 161.36 | 168.21 | 167.29 | 147.78 |
| Q7 | 889.83 | 602.84 | 569.87 | 446.54 | 335.63 |
| Q8 | 271.94 | 202.84 | 247.64 | 184.74 | 146.29 |
| Q9 | 615.42 | 457.34 | 349.46 | 259.7 | 137.27 |
| Q10 | 526.03 | 319.47 | 339.01 | 258.55 | 203.17 |
| Q11 | 36.64 | 36.3 | 36.24 | 36.52 | 33.58 |
| Q12 | 102.55 | 72.25 | 66.01 | 85.13 | 68.13 | | 0 |
| | 1Node | 2Nodes | 4Nodes | 8Nodes | 16Nodes |
| --- | --- | --- | --- | --- | --- |
| Q1 | 47.71 | 45.32 | 47.41 | 46.83 | 49.1 |
| Q2 | 107.05 | 65.95 | 68.29 | 53.16 | 55.93 |
| Q3 | 620.57 | 498.45 | 312.17 | 195.13 | 135.73 |
| Q4 | 208.51 | 142.12 | 136.69 | 130.51 | 125.60 |
| Q5 | 539.37 | 437.27 | 264.13 | 179.18 | 131.98 |
| Q6 | 220.29 | 133.08 | 108.56 | 77.02 | 67.42 |
| Q7 | 35.96 | 33.15 | 33.64 | 36.12 | 34.44 |
| Q9 | 575.29 | 310.14 | 297.75 | 190.08 | 145.75 |
| Q10 | 36.68 | 32.03 | 34.04 | 36.00 | 33.91 |
| Q11 | 580.72 | 412.59 | 300.78 | 183.67 | 138.56 |
| Q12 | 99.04 | 61.24 | 48.05 | 47.07 | 42.52 |
| Q13 | 575.09 | 402.15 | 291.11 | 186.86 | 120.88 |
| Q14 | 47.66 | 45.92 | 48.03 | 46.61 | 47.36 |
| Q15 | 36.90 | 32.04 | 36.53 | 36.06 | 35.46 |
| Q16 | 610.85 | 387.59 | 315.06 | 202.07 | 149.09 | | | Q17 | NaN | NaN | NaN | NaN | NaN |
| --- | --- | --- | --- | --- | --- |
| Q18 | 35.88 | 32.05 | 36.69 | 35.00 | 34.23 |
| Q19 | 597.83 | 499.11 | 305.14 | 196.61 | 140.85 |
| Q20 | 607.89 | 336.38 | 316.46 | 194.37 | 140.92 | | 1 |
| | 1Node | 2Nodes | 4Nodes | 8Nodes | 16Nodes |
| --- | --- | --- | --- | --- | --- |
| Q1 | 47.71 | 45.32 | 47.41 | 46.83 | 49.1 |
| Q2 | 107.05 | 65.95 | 68.29 | 53.16 | 55.93 |
| Q3 | 620.57 | 498.45 | 312.17 | 195.13 | 135.73 |
| Q4 | 208.51 | 142.12 | 136.69 | 130.51 | 125.60 |
| Q5 | 539.37 | 437.27 | 264.13 | 179.18 | 131.98 |
| Q6 | 220.29 | 133.08 | 108.56 | 77.02 | 67.42 |
| Q7 | 35.96 | 33.15 | 33.64 | 36.12 | 34.44 |
| Q9 | 575.29 | 310.14 | 297.75 | 190.08 | 145.75 |
| Q10 | 36.68 | 32.03 | 34.04 | 36.00 | 33.91 |
| Q11 | 580.72 | 412.59 | 300.78 | 183.67 | 138.56 |
| Q12 | 99.04 | 61.24 | 48.05 | 47.07 | 42.52 |
| Q13 | 575.09 | 402.15 | 291.11 | 186.86 | 120.88 |
| Q14 | 47.66 | 45.92 | 48.03 | 46.61 | 47.36 |
| Q15 | 36.90 | 32.04 | 36.53 | 36.06 | 35.46 |
| Q16 | 610.85 | 387.59 | 315.06 | 202.07 | 149.09 | | | Q10 | 526.03 | 319.47 | 339.01 | 258.55 | 203.17 |
| --- | --- | --- | --- | --- | --- |
| Q11 | 36.64 | 36.3 | 36.24 | 36.52 | 33.58 |
| Q12 | 102.55 | 72.25 | 66.01 | 85.13 | 68.13 | | 0 |
| 8<br>4<br>2 | 895542<br>1791084<br>3582168 | 934040<br>1808784<br>3585869 |
| --- | --- | --- |
| 8<br>4<br>2 | 3203546<br>6407091<br>7<br>1.2814·10 | 3219769<br>6427398<br>7<br>1.2827·10 |
| 8<br>4<br>2 | 8.928·10<br>9<br>1.7856·10<br>9<br>3.5712·10 | 8.9394·10<br>9<br>1.7871·10<br>9<br>3.573·10 | | | 8<br>4<br>2 | 1.2497·10<br>9<br>2.4995·10<br>9<br>4.9989·10 | 1.251·10<br>9<br>2.5005·10<br>9<br>4.9995·10 |
| --- | --- | --- |
| 8 | 6.4582·10 | 6.4651·10 | | 1 |
| 8<br>4<br>2 | 895542<br>1791084<br>3582168 | 934040<br>1808784<br>3585869 |
| --- | --- | --- |
| 8<br>4<br>2 | 3203546<br>6407091<br>7<br>1.2814·10 | 3219769<br>6427398<br>7<br>1.2827·10 |
| 8<br>4<br>2 | 8.928·10<br>9<br>1.7856·10<br>9<br>3.5712·10 | 8.9394·10<br>9<br>1.7871·10<br>9<br>3.573·10 | | | 1234567 |
| --- |
| 8.627.887.768.349.138.078.89<br>0.510.520.540.520.540.530.55<br>-8.9-5.0-9.0-4.3-14-5.6-10 |
| 71691.11.31.31.18.7<br>0.890.880.920.840.890.900.92 |
| 10.94.818.274.4216.55.2111.0<br>4.566.674.222.601.853.621.01<br>-4.74-4.38-4.60-4.99-5.79-4.91-6.03 |
| 1.130.8921.321.471.721.261.17<br>0.830.850.900.820.860.890.89 | | 0 |
| 8<br>4<br>2 | 895542<br>1791084<br>3582168 | 934040<br>1808784<br>3585869 |
| --- | --- | --- |
| 8<br>4<br>2 | 3203546<br>6407091<br>7<br>1.2814·10 | 3219769<br>6427398<br>7<br>1.2827·10 | | | 8<br>4<br>2 | 8.928·10<br>9<br>1.7856·10<br>9<br>3.5712·10 | 8.9394·10<br>9<br>1.7871·10<br>9<br>3.573·10 |
| --- | --- | --- |
| 8<br>4<br>2 | 1.2497·10<br>9<br>2.4995·10<br>9<br>4.9989·10 | 1.251·10<br>9<br>2.5005·10<br>9<br>4.9995·10 |
| 8 | 6.4582·10 | 6.4651·10 | | 1 |
| 8<br>4<br>2 | 895542<br>1791084<br>3582168 | 934040<br>1808784<br>3585869 |
| --- | --- | --- |
| 8<br>4<br>2 | 3203546<br>6407091<br>7<br>1.2814·10 | 3219769<br>6427398<br>7<br>1.2827·10 | | | 71691.11.31.31.18.7<br>0.890.880.920.840.890.900.92 |
| --- |
| 10.94.818.274.4216.55.2111.0<br>4.566.674.222.601.853.621.01<br>-4.74-4.38-4.60-4.99-5.79-4.91-6.03 |
| 1.130.8921.321.471.721.261.17<br>0.830.850.900.820.860.890.89 | | 0 |
| VisualParts(VP) | | | |
| --- | --- | --- | --- |
| Train→ | 1 | 19 | 19 |
| Test↓→ | 1 | 1 | 19 | | | LanguageParts<br>(LP) | 1 | 25.0 | 26.8 | 32.1 |
| --- | --- | --- | --- | --- |
| 50 | 23.6 | 30.5 | 33.9 | | | 1 |
| VisualParts(VP) | | | |
| --- | --- | --- | --- |
| Train→ | 1 | 19 | 19 |
| Test↓→ | 1 | 1 | 19 | | | Usage |
| --- |
| TMtrain |
| LMtrain |
| train |
| dev |
| test<br>test | | 0 |
| VisualParts(VP) | | | |
| --- | --- | --- | --- |
| Train→ | 1 | 19 | 19 |
| Test↓→ | 1 | 1 | 19 | | | LanguageParts<br>(LP) | 1 | 25.0 | 26.8 | 32.1 |
| --- | --- | --- | --- | --- |
| 50 | 23.6 | 30.5 | 33.9 | | | 1 |
| VisualParts(VP) | | | |
| --- | --- | --- | --- |
| Train→ | 1 | 19 | 19 |
| Test↓→ | 1 | 1 | 19 | | | dev |
| --- |
| test<br>test | | 0 |
| | DIIVINE | BRISQUE | MetricQ | Anisotropy | |
| --- | --- | --- | --- | --- | --- |
| LIVE | medianofallSSIMdifferences | 1.06×10 | 1.07×10 | 2.36×10 | 6.95×10 |
| averageofallSSIMdifferences | 1.22×10 | 1.25×10 | 6.73×10 | 8.23×10 | |
| averageofnon-outliers | 1.22×10 | 1.25×10 | 5.67×10 | 8.23×10 | |
| CSIQ | medianofallSSIMdifferences | 8.81×10 | 8.68×10 | 2.83×10 | 2.18×10 | | | averageofallSSIMdifferences | 9.11×10 | 8.95×10 | 7.65×10 | 4.30×10 |
| --- | --- | --- | --- | --- |
| averageofnon-outliers | 8.54×10 | 8.06×10 | 6.34×10 | 3.17×10 | | 1 |
| | DIIVINE | BRISQUE | MetricQ | Anisotropy | |
| --- | --- | --- | --- | --- | --- |
| LIVE | medianofallSSIMdifferences | 1.06×10 | 1.07×10 | 2.36×10 | 6.95×10 |
| averageofallSSIMdifferences | 1.22×10 | 1.25×10 | 6.73×10 | 8.23×10 | |
| averageofnon-outliers | 1.22×10 | 1.25×10 | 5.67×10 | 8.23×10 | |
| CSIQ | medianofallSSIMdifferences | 8.81×10 | 8.68×10 | 2.83×10 | 2.18×10 | | | | DIIVINE | BRISQUE | MetricQ | Anisotropy | |
| --- | --- | --- | --- | --- | --- |
| LIVE | medianofallSSIMdifferences | 1.67×10 | 1.33×10 | 2.42×10 | 8.88×10 |
| averageofallSSIMdifference | 1.85×10 | 1.33×10 | 5.07×10 | 1.09×10 | |
| averageofnon-outliers | 1.74×10 | 1.33×10 | 5.07×10 | 1.09×10 | |
| CSIQ | medianofallSSIMdifference | 1.24×10 | 1.05×10 | 2.44×10 | 3.66×10 |
| averageofallSSIMdifference | 1.43×10 | 1.23×10 | 4.25×10 | 4.30×10 | |
| averageofnon-outliers | 1.31×10 | 1.23×10 | 2.19×10 | 3.81×10 | | | 0 |
| | DIIVINE | BRISQUE | MetricQ | Anisotropy | |
| --- | --- | --- | --- | --- | --- |
| LIVE | medianofallSSIMdifferences | 1.06×10 | 1.07×10 | 2.36×10 | 6.95×10 | | | averageofallSSIMdifferences | 1.22×10 | 1.25×10 | 6.73×10 | 8.23×10 | |
| --- | --- | --- | --- | --- | --- |
| averageofnon-outliers | 1.22×10 | 1.25×10 | 5.67×10 | 8.23×10 | |
| CSIQ | medianofallSSIMdifferences | 8.81×10 | 8.68×10 | 2.83×10 | 2.18×10 |
| averageofallSSIMdifferences | 9.11×10 | 8.95×10 | 7.65×10 | 4.30×10 | |
| averageofnon-outliers | 8.54×10 | 8.06×10 | 6.34×10 | 3.17×10 | | | 1 |
| | DIIVINE | BRISQUE | MetricQ | Anisotropy | |
| --- | --- | --- | --- | --- | --- |
| LIVE | medianofallSSIMdifferences | 1.06×10 | 1.07×10 | 2.36×10 | 6.95×10 | | | averageofnon-outliers | 1.74×10 | 1.33×10 | 5.07×10 | 1.09×10 | |
| --- | --- | --- | --- | --- | --- |
| CSIQ | medianofallSSIMdifference | 1.24×10 | 1.05×10 | 2.44×10 | 3.66×10 |
| averageofallSSIMdifference | 1.43×10 | 1.23×10 | 4.25×10 | 4.30×10 | |
| averageofnon-outliers | 1.31×10 | 1.23×10 | 2.19×10 | 3.81×10 | | | 0 |
| | LOSO | LOUO |
| --- | --- | --- |
| SMT | 0.18\|0.31 | 0.05\|-0.22 |
| DCT | 0.46\|0.57 | 0.14\|0.24 |
| DFT | 0.40\|0.45 | 0.19\|0.12 |
| ApEn | 0.24\|0.23 | 0.22\|0.10 |
| SMT+DCT | 0.43\|0.39 | 0.08\|0.22 | | | SMT+DFT | 0.38\|0.51 | 0.22\|0.04 |
| --- | --- | --- |
| SMT+ApEn | 0.20\|0.22 | 0.21\|0.08 |
| SMT+DCT+DFT | 0.50\|0.57 | 0.41\|0.36 |
| DCT+DFT | 0.50\|0.60 | 0.40\|0.38 |
| DCT+DFT+ApEn | 0.51\|0.61 | 0.38\|0.41 |
| SMT+DCT+DFT+ApEn | 0.49\|0.58 | 0.24\|0.27 | | 1 |
| | LOSO | LOUO |
| --- | --- | --- |
| SMT | 0.18\|0.31 | 0.05\|-0.22 |
| DCT | 0.46\|0.57 | 0.14\|0.24 |
| DFT | 0.40\|0.45 | 0.19\|0.12 |
| ApEn | 0.24\|0.23 | 0.22\|0.10 |
| SMT+DCT | 0.43\|0.39 | 0.08\|0.22 | | | | P | R | F | P | R | F |
| --- | --- | --- | --- | --- | --- | --- |
| R3-5 | 0.495 | 0.665 | 0.568 | 0.894 | 0.872 | 0.883 |
| R3-6 | 0.683 | 0.683 | 0.683 | 0.957 | 0.95 | 0.953 |
| R3-6+BT | 0.755 | 0.705 | 0.729 | 0.961 | 0.961 | 0.961 |
| S+r | 0.722 | 0.63 | 0.673 | 0.979 | 0.955 | 0.967 |
| S+r+BT | 0.799 | 0.753 | 0.776 | 0.973 | 0.969 | 0.971 |
| S+BT | 0.779 | 0.714 | 0.745 | 0.969 | 0.966 | 0.968 | | 0 |
| | LOSO | LOUO |
| --- | --- | --- |
| SMT | 0.18\|0.31 | 0.05\|-0.22 |
| DCT | 0.46\|0.57 | 0.14\|0.24 |
| DFT | 0.40\|0.45 | 0.19\|0.12 |
| ApEn | 0.24\|0.23 | 0.22\|0.10 | | | SMT+DCT | 0.43\|0.39 | 0.08\|0.22 |
| --- | --- | --- |
| SMT+DFT | 0.38\|0.51 | 0.22\|0.04 |
| SMT+ApEn | 0.20\|0.22 | 0.21\|0.08 |
| SMT+DCT+DFT | 0.50\|0.57 | 0.41\|0.36 |
| DCT+DFT | 0.50\|0.60 | 0.40\|0.38 |
| DCT+DFT+ApEn | 0.51\|0.61 | 0.38\|0.41 |
| SMT+DCT+DFT+ApEn | 0.49\|0.58 | 0.24\|0.27 | | 1 |
| | LOSO | LOUO |
| --- | --- | --- |
| SMT | 0.18\|0.31 | 0.05\|-0.22 |
| DCT | 0.46\|0.57 | 0.14\|0.24 |
| DFT | 0.40\|0.45 | 0.19\|0.12 |
| ApEn | 0.24\|0.23 | 0.22\|0.10 | | | S+r+BT | 0.799 | 0.753 | 0.776 | 0.973 | 0.969 | 0.971 |
| --- | --- | --- | --- | --- | --- | --- |
| S+BT | 0.779 | 0.714 | 0.745 | 0.969 | 0.966 | 0.968 | | 0 |
| Corpus | Language | #Instances | #Words(F/E) |
| --- | --- | --- | --- |
| HindiTreebank | Hindi | 147 | 963/945 |
| ODIN | German | 105 | 747/774 | | | Irish | 46 | 252/278 | |
| --- | --- | --- | --- |
| Hausa | 77 | 424/520 | |
| Korean | 103 | 518/731 | |
| Malagasy | 87 | 489/646 | |
| Welsh | 53 | 312/329 | |
| Yaqui | 68 | 350/544 | |
| SMULTRON | German | 281 | 6829/7236 |
| Swedish | 281 | 8402/9377 | | | 1 |
| Corpus | Language | #Instances | #Words(F/E) |
| --- | --- | --- | --- |
| HindiTreebank | Hindi | 147 | 963/945 |
| ODIN | German | 105 | 747/774 | | | Languages | MovieCount | UserCount |
| --- | --- | --- |
| Hindi | 615 | 902 |
| Bengali | 582 | 28 |
| Assamese | 22 | 9 |
| Tamil | 313 | 30 |
| Nepali | 51 | 9 |
| Punjabi | 150 | 78 |
| Rajasthani | 18 | 14 |
| Malayalam | 346 | 16 |
| Bhojpuri | 26 | 21 |
| Kannada | 303 | 11 |
| Haryanvi | 3 | 18 |
| Manipuri | 8 | 4 |
| Urdu | 129 | 23 |
| Marathi | 204 | 14 |
| Telugu | 338 | 18 |
| Oriya | 98 | 6 |
| Gujarati | 49 | 7 |
| Konkani | 6 | 4 | | 0 |
| Corpus | Language | #Instances | #Words(F/E) |
| --- | --- | --- | --- |
| HindiTreebank | Hindi | 147 | 963/945 |
| ODIN | German | 105 | 747/774 |
| Irish | 46 | 252/278 | |
| Hausa | 77 | 424/520 | | | | Korean | 103 | 518/731 | |
| --- | --- | --- | --- |
| Malagasy | 87 | 489/646 | |
| Welsh | 53 | 312/329 | |
| Yaqui | 68 | 350/544 | |
| SMULTRON | German | 281 | 6829/7236 |
| Swedish | 281 | 8402/9377 | | | 1 |
| Corpus | Language | #Instances | #Words(F/E) |
| --- | --- | --- | --- |
| HindiTreebank | Hindi | 147 | 963/945 |
| ODIN | German | 105 | 747/774 |
| Irish | 46 | 252/278 | |
| Hausa | 77 | 424/520 | | | | Punjabi | 150 | 78 |
| --- | --- | --- |
| Rajasthani | 18 | 14 |
| Malayalam | 346 | 16 |
| Bhojpuri | 26 | 21 |
| Kannada | 303 | 11 |
| Haryanvi | 3 | 18 |
| Manipuri | 8 | 4 |
| Urdu | 129 | 23 |
| Marathi | 204 | 14 |
| Telugu | 338 | 18 |
| Oriya | 98 | 6 |
| Gujarati | 49 | 7 |
| Konkani | 6 | 4 | | 0 |
| Parameter | 32-bit | | |
| --- | --- | --- | --- |
| Silicon | Carbon | Silicon | |
| Totalpowerdissipation<br>(watts) | 323.358µ | 76.8077n | 957.513µ | | | Averagepower<br>consumption(watts) | 43.834E-05 | 11.923E-05 | 122.50E-05 |
| --- | --- | --- | --- |
| PropagationDelay(s) | 262.36p | 680.36f | 280.43p |
| Powerdelayproduct(J) | 115E-15 | 81.1E-15 | 343.52E-15 | | 1 |
| Parameter | 32-bit | | |
| --- | --- | --- | --- |
| Silicon | Carbon | Silicon | |
| Totalpowerdissipation<br>(watts) | 323.358µ | 76.8077n | 957.513µ | | | Parameter | 32-bit | | |
| --- | --- | --- | --- |
| Silicon | Carbon | Silicon | |
| Totalpowerdissipation<br>(watts) | 234.8754µ | 79.3373n | 301.5764µ |
| Averagepower<br>consumption(watts) | 4.4421E-04 | 1.2223E-04 | 5.8691E-04 |
| PropagationDelay(s) | 174.63p | 658.85f | 223.85p |
| Powerdelayproduct(J) | 77.572E-15 | 80.53E-18 | 131.37E-15 | | 0 |
| Parameter | 32-bit | |
| --- | --- | --- |
| Silicon | Carbon | Silicon | | | Totalpowerdissipation<br>(watts) | 323.358µ | 76.8077n | 957.513µ |
| --- | --- | --- | --- |
| Averagepower<br>consumption(watts) | 43.834E-05 | 11.923E-05 | 122.50E-05 |
| PropagationDelay(s) | 262.36p | 680.36f | 280.43p |
| Powerdelayproduct(J) | 115E-15 | 81.1E-15 | 343.52E-15 | | 1 |
| Parameter | 32-bit | |
| --- | --- | --- |
| Silicon | Carbon | Silicon | | | Totalpowerdissipation<br>(watts) | 234.8754µ | 79.3373n | 301.5764µ |
| --- | --- | --- | --- |
| Averagepower<br>consumption(watts) | 4.4421E-04 | 1.2223E-04 | 5.8691E-04 |
| PropagationDelay(s) | 174.63p | 658.85f | 223.85p |
| Powerdelayproduct(J) | 77.572E-15 | 80.53E-18 | 131.37E-15 | | 0 |
| Portalcategories | Numberofportals |
| --- | --- |
| Statistics | 1 |
| Representations | 2 | | | PeriphericalOffices | 6 |
| --- | --- |
| Certifications | 4 |
| PropertyRegisterOffices | 3 |
| SocialSecurity | 9 |
| ForeignRelations | 4 |
| RelationsAbroad | 6 |
| Defense | 1 |
| Justice | 10 |
| Criminality | 6 |
| InternalSecurity | 6 |
| PublicAssistance | 5 |
| HealthServices | 6 |
| Education | 3 |
| Environment | 8 |
| CulturalGoods | 10 |
| Employment | 9 |
| Farms | 3 |
| IndustrialCompanies | 9 |
| Transportations | 10 | | 1 |
| Portalcategories | Numberofportals |
| --- | --- |
| Statistics | 1 |
| Representations | 2 | | | Attribute | DomainSize |
| --- | --- |
| Age | 76 |
| Gender | 2 |
| Education | 14 |
| Marital | 6 |
| Race | 9 |
| Work-Class | 10 |
| Country | 83 |
| Occupation | 50 | | 0 |
| Portalcategories | Numberofportals |
| --- | --- |
| Statistics | 1 |
| Representations | 2 |
| PeriphericalOffices | 6 |
| Certifications | 4 |
| PropertyRegisterOffices | 3 |
| SocialSecurity | 9 | | | ForeignRelations | 4 |
| --- | --- |
| RelationsAbroad | 6 |
| Defense | 1 |
| Justice | 10 |
| Criminality | 6 |
| InternalSecurity | 6 |
| PublicAssistance | 5 |
| HealthServices | 6 |
| Education | 3 |
| Environment | 8 |
| CulturalGoods | 10 |
| Employment | 9 |
| Farms | 3 |
| IndustrialCompanies | 9 |
| Transportations | 10 | | 1 |
| Portalcategories | Numberofportals |
| --- | --- |
| Statistics | 1 |
| Representations | 2 |
| PeriphericalOffices | 6 |
| Certifications | 4 |
| PropertyRegisterOffices | 3 |
| SocialSecurity | 9 | | | Marital | 6 |
| --- | --- |
| Race | 9 |
| Work-Class | 10 |
| Country | 83 |
| Occupation | 50 | | 0 |
| Memristorposition | Comparison | P-value |
| --- | --- | --- |
| Input-hidden | HPvs.PEO-PANI | 0.710 |
| | HPvs.LINEAR | 0.543 |
| | PEOvs.LINEAR | 0.339 |
| Hidden-hidden | HPvs.PEO-PANI | 0.482 |
| | HPvs.LINEAR | 0.045 | | | | PEOvs.LINEAR | 0.012 |
| --- | --- | --- |
| Hidden-Output | HPvs.PEO-PANI | 0.04 |
| | HPvs.LINEAR | 0.079 |
| | PEOvs.LINEAR | 0.839 | | 1 |
| Memristorposition | Comparison | P-value |
| --- | --- | --- |
| Input-hidden | HPvs.PEO-PANI | 0.710 |
| | HPvs.LINEAR | 0.543 |
| | PEOvs.LINEAR | 0.339 |
| Hidden-hidden | HPvs.PEO-PANI | 0.482 |
| | HPvs.LINEAR | 0.045 | | | Inputsourceneuron | Comparison | P-value |
| --- | --- | --- |
| IRsensor | HPvs.PEO-PANI | 0.033 |
| | HPvs.LINEAR | 0.074 |
| | PEOvs.LINEAR | 0.933 |
| Lightsensor | HPvs.PEO-PANI | 1 |
| | HPvs.LINEAR | 0.379 |
| | PEOvs.LINEAR | 0.410 | | 0 |
| Memristorposition | Comparison | P-value |
| --- | --- | --- |
| Input-hidden | HPvs.PEO-PANI | 0.710 |
| | HPvs.LINEAR | 0.543 |
| | PEOvs.LINEAR | 0.339 |
| Hidden-hidden | HPvs.PEO-PANI | 0.482 |
| | HPvs.LINEAR | 0.045 |
| | PEOvs.LINEAR | 0.012 | | | Hidden-Output | HPvs.PEO-PANI | 0.04 |
| --- | --- | --- |
| | HPvs.LINEAR | 0.079 |
| | PEOvs.LINEAR | 0.839 | | 1 |
| Memristorposition | Comparison | P-value |
| --- | --- | --- |
| Input-hidden | HPvs.PEO-PANI | 0.710 |
| | HPvs.LINEAR | 0.543 |
| | PEOvs.LINEAR | 0.339 |
| Hidden-hidden | HPvs.PEO-PANI | 0.482 |
| | HPvs.LINEAR | 0.045 |
| | PEOvs.LINEAR | 0.012 | | | Lightsensor | HPvs.PEO-PANI | 1 |
| --- | --- | --- |
| | HPvs.LINEAR | 0.379 |
| | PEOvs.LINEAR | 0.410 | | 0 |
| CH | SWB | | |
| --- | --- | --- | --- |
| ASR | Human | ASR | Human |
| 15:a | 10:i | 19:i | 12:i |
| 15:is | 9:and | 9:and | 11:and |
| 11:i | 8:a | 7:of | 9:you |
| 11:the | 8:that | 6:do | 8:is |
| 11:you | 8:the | 6:is | 6:they |
| 9:it | 7:have | 5:but | 5:do |
| 7:oh | 5:you | 5:yeah | 5:have | | | 6:and | 4:are | 4:air | 5:it |
| --- | --- | --- | --- |
| 6:in | 4:is | 4:in | 5:yeah |
| 6:know | 4:they | 4:you | 4:a | | 1 |
| CH | SWB | | |
| --- | --- | --- | --- |
| ASR | Human | ASR | Human |
| 15:a | 10:i | 19:i | 12:i |
| 15:is | 9:and | 9:and | 11:and |
| 11:i | 8:a | 7:of | 9:you |
| 11:the | 8:that | 6:do | 8:is |
| 11:you | 8:the | 6:is | 6:they |
| 9:it | 7:have | 5:but | 5:do |
| 7:oh | 5:you | 5:yeah | 5:have | | | CH | SWB | | |
| --- | --- | --- | --- |
| ASR | Human | ASR | Human |
| 15:a | 10:i | 19:i | 12:i |
| 15:is | 9:and | 9:and | 11:and |
| 11:i | 8:a | 7:of | 9:you |
| 11:the | 8:that | 6:do | 8:is |
| 11:you | 8:the | 6:is | 6:they |
| 9:it | 7:have | 5:but | 5:do |
| 7:oh | 5:you | 5:yeah | 5:have |
| 6:and | 4:are | 4:air | 5:it |
| 6:in | 4:is | 4:in | 5:yeah |
| 6:know | 4:they | 4:you | 4:a | | 0 |
| CH | SWB | | |
| --- | --- | --- | --- |
| ASR | Human | ASR | Human |
| 15:a | 10:i | 19:i | 12:i | | | 15:is | 9:and | 9:and | 11:and |
| --- | --- | --- | --- |
| 11:i | 8:a | 7:of | 9:you |
| 11:the | 8:that | 6:do | 8:is |
| 11:you | 8:the | 6:is | 6:they |
| 9:it | 7:have | 5:but | 5:do |
| 7:oh | 5:you | 5:yeah | 5:have |
| 6:and | 4:are | 4:air | 5:it |
| 6:in | 4:is | 4:in | 5:yeah |
| 6:know | 4:they | 4:you | 4:a | | 1 |
| CH | SWB | | |
| --- | --- | --- | --- |
| ASR | Human | ASR | Human |
| 15:a | 10:i | 19:i | 12:i | | | 6:and | 4:are | 4:air | 5:it |
| --- | --- | --- | --- |
| 6:in | 4:is | 4:in | 5:yeah |
| 6:know | 4:they | 4:you | 4:a | | 0 |
| hammingradius | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| #ofbuckets(16bits) | 1 | 16 | 120 | 560 | 1,820 | 4,368 | 8,008 | 11,440 | 12,870 |
| #ofqueries(16bits)(1.752s) | 0 | 3637 | 4932 | 1230 | 169 | 30 | 1 | 1 | 0 | | | #ofbuckets(32bits) | 1 | 32 | 496 | 4960 | 35,960 | 201,376 | 906,192 | 3,365,856 | 10,518,300 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| #ofqueries(32bits)(237.8s) | 0 | 0 | 0 | 4 | 1710 | 4282 | 2691 | 1021 | 241 | | 1 |
| hammingradius | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| #ofbuckets(16bits) | 1 | 16 | 120 | 560 | 1,820 | 4,368 | 8,008 | 11,440 | 12,870 |
| #ofqueries(16bits)(1.752s) | 0 | 3637 | 4932 | 1230 | 169 | 30 | 1 | 1 | 0 | | | hammingradius | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| #ofbuckets(24bits) | 1 | 24 | 276 | 2,024 | 10,626 | 42,504 | 134,596 | 346,104 | 735,471 |
| #ofqueries(24bits)(0.234s) | 70 | 467 | 277 | 115 | 44 | 18 | 7 | 2 | 0 |
| #ofbuckets(40bits) | 1 | 40 | 780 | 9,880 | 91,390 | 658,008 | 3,838,380 | 18,643,560 | 76,904,685 |
| #ofqueries(40bits)(240.0s) | 0 | 0 | 27 | 252 | 302 | 205 | 107 | 57 | 27 | | 0 |
| hammingradius | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| #ofbuckets(16bits) | 1 | 16 | 120 | 560 | 1,820 | 4,368 | 8,008 | 11,440 | 12,870 |
| #ofqueries(16bits)(1.752s) | 0 | 3637 | 4932 | 1230 | 169 | 30 | 1 | 1 | 0 | | | #ofbuckets(32bits) | 1 | 32 | 496 | 4960 | 35,960 | 201,376 | 906,192 | 3,365,856 | 10,518,300 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| #ofqueries(32bits)(237.8s) | 0 | 0 | 0 | 4 | 1710 | 4282 | 2691 | 1021 | 241 | | 1 |
| hammingradius | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| #ofbuckets(16bits) | 1 | 16 | 120 | 560 | 1,820 | 4,368 | 8,008 | 11,440 | 12,870 |
| #ofqueries(16bits)(1.752s) | 0 | 3637 | 4932 | 1230 | 169 | 30 | 1 | 1 | 0 | | | #ofbuckets(40bits) | 1 | 40 | 780 | 9,880 | 91,390 | 658,008 | 3,838,380 | 18,643,560 | 76,904,685 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| #ofqueries(40bits)(240.0s) | 0 | 0 | 27 | 252 | 302 | 205 | 107 | 57 | 27 | | 0 |
| AlgorithmVersion | Single-signal | Indexed | Multi-signal | GPU-based |
| --- | --- | --- | --- | --- |
| NetworkConfigurationatConvergence | | | | |
| Iterations | 1,100,000 | 1,100,000 | 1,128 | 1,128 |
| Signals | 1,100,000 | 1,100,000 | 1,100,110 | 1,100,110 |
| DiscardedSignals | 0 | 0 | 562,277 | 562,277 |
| Units | 656 | 649 | 658 | 658 |
| Connections | 1,974 | 1,953 | 1,980 | 1,980 |
| TimetoConvergence | | | | |
| TotalTime | 12.3540 | 5.5690 | 11.6070 | 3.8690 |
| Sample<br>FindWinners<br>Update | 0.0150<br>8.8600<br>3.4790 | 0.0480<br>2.8220<br>2.6990 | 0.0620<br>8.5060<br>3.0390 | 0.1410<br>0.7650<br>2.9630 | | | TimeperSignal | | | | |
| --- | --- | --- | --- | --- |
| TimeperSignal | 1.1231×10 | 5.0627×10 | 1.0551×10 | 3.5169×10 |
| FindWinners | 8.0545×10 | 2.5655×10 | 7.7320×10 | 6.9539×10 | | 1 |
| AlgorithmVersion | Single-signal | Indexed | Multi-signal | GPU-based |
| --- | --- | --- | --- | --- |
| NetworkConfigurationatConvergence | | | | |
| Iterations | 1,100,000 | 1,100,000 | 1,128 | 1,128 |
| Signals | 1,100,000 | 1,100,000 | 1,100,110 | 1,100,110 |
| DiscardedSignals | 0 | 0 | 562,277 | 562,277 |
| Units | 656 | 649 | 658 | 658 |
| Connections | 1,974 | 1,953 | 1,980 | 1,980 |
| TimetoConvergence | | | | |
| TotalTime | 12.3540 | 5.5690 | 11.6070 | 3.8690 |
| Sample<br>FindWinners<br>Update | 0.0150<br>8.8600<br>3.4790 | 0.0480<br>2.8220<br>2.6990 | 0.0620<br>8.5060<br>3.0390 | 0.1410<br>0.7650<br>2.9630 | | | Algorithm | MR=0.25 | MR=0.10 | MR=0.04 | MR=0.01 |
| --- | --- | --- | --- | --- |
| TVAL3 | 2.943 | 3.223 | 3.467 | 7.790 |
| NLR-CS | 314.852 | 305.703 | 300.666 | 314.176 |
| D-AMP | 27.764 | 31.849 | 34.207 | 54.643 |
| ReconNet(CPU) | 0.5249 | 0.5258 | 0.5284 | 0.5193 |
| ReconNet(GPU) | 0.0213 | 0.0195 | 0.0192 | 0.0244 |
| SDA(GPU) | 0.0042 | 0.0029 | 0.0025 | 0.0045 | | 0 |
| AlgorithmVersion | Single-signal | Indexed | Multi-signal | GPU-based |
| --- | --- | --- | --- | --- |
| NetworkConfigurationatConvergence | | | | |
| Iterations | 1,100,000 | 1,100,000 | 1,128 | 1,128 |
| Signals | 1,100,000 | 1,100,000 | 1,100,110 | 1,100,110 |
| DiscardedSignals | 0 | 0 | 562,277 | 562,277 |
| Units | 656 | 649 | 658 | 658 |
| Connections | 1,974 | 1,953 | 1,980 | 1,980 |
| TimetoConvergence | | | | |
| TotalTime | 12.3540 | 5.5690 | 11.6070 | 3.8690 |
| Sample<br>FindWinners<br>Update | 0.0150<br>8.8600<br>3.4790 | 0.0480<br>2.8220<br>2.6990 | 0.0620<br>8.5060<br>3.0390 | 0.1410<br>0.7650<br>2.9630 | | | TimeperSignal | | | | |
| --- | --- | --- | --- | --- |
| TimeperSignal | 1.1231×10 | 5.0627×10 | 1.0551×10 | 3.5169×10 |
| FindWinners | 8.0545×10 | 2.5655×10 | 7.7320×10 | 6.9539×10 | | 1 |
| AlgorithmVersion | Single-signal | Indexed | Multi-signal | GPU-based |
| --- | --- | --- | --- | --- |
| NetworkConfigurationatConvergence | | | | |
| Iterations | 1,100,000 | 1,100,000 | 1,128 | 1,128 |
| Signals | 1,100,000 | 1,100,000 | 1,100,110 | 1,100,110 |
| DiscardedSignals | 0 | 0 | 562,277 | 562,277 |
| Units | 656 | 649 | 658 | 658 |
| Connections | 1,974 | 1,953 | 1,980 | 1,980 |
| TimetoConvergence | | | | |
| TotalTime | 12.3540 | 5.5690 | 11.6070 | 3.8690 |
| Sample<br>FindWinners<br>Update | 0.0150<br>8.8600<br>3.4790 | 0.0480<br>2.8220<br>2.6990 | 0.0620<br>8.5060<br>3.0390 | 0.1410<br>0.7650<br>2.9630 | | | ReconNet(GPU) | 0.0213 | 0.0195 | 0.0192 | 0.0244 |
| --- | --- | --- | --- | --- |
| SDA(GPU) | 0.0042 | 0.0029 | 0.0025 | 0.0045 | | 0 |
| x | y | z | Numberofsatisfiedclauses |
| --- | --- | --- | --- |
| 0 | 1 | 1 | 2 |
| 0 | 1 | 0 | 3 |
| 0 | 0 | 1 | 3 |
| 0 | 0 | 0 | 3 | | | 1 | 1 | 1 | 3 |
| --- | --- | --- | --- |
| 1 | 1 | 0 | 3 |
| 1 | 0 | 1 | 3 |
| 1 | 0 | 0 | 2 | | 1 |
| x | y | z | Numberofsatisfiedclauses |
| --- | --- | --- | --- |
| 0 | 1 | 1 | 2 |
| 0 | 1 | 0 | 3 |
| 0 | 0 | 1 | 3 |
| 0 | 0 | 0 | 3 | | | x1 | x2 | x3 | x4 | f(x):Case1 | Case2 | Case3 |
| --- | --- | --- | --- | --- | --- | --- |
| 0 | 0 | 0 | 0 | 0 | 1 | 1 |
| 0 | 0 | 0 | 1 | 1 | 1 | 1 |
| 0 | 0 | 1 | 0 | 1 | 1 | * |
| 0 | 0 | 1 | 1 | 1 | 1 | * |
| 0 | 1 | 0 | 0 | 1 | 1 | 1 |
| 0 | 1 | 0 | 1 | 1 | 1 | 1 |
| 0 | 1 | 1 | 0 | 1 | 1 | 1 |
| 0 | 1 | 1 | 1 | 1 | 0 | 1 |
| 1 | 0 | 0 | 0 | 1 | 1 | 1 |
| 1 | 0 | 0 | 1 | 1 | 1 | 1 |
| 1 | 0 | 1 | 0 | 1 | 1 | 1 |
| 1 | 0 | 1 | 1 | 1 | 0 | 1 |
| 1 | 1 | 0 | 0 | 1 | 1 | * |
| 1 | 1 | 0 | 1 | 1 | 0 | * |
| 1 | 1 | 1 | 0 | 1 | 0 | * |
| 1 | 1 | 1 | 1 | * | * | * | | 0 |
| x | y | z | Numberofsatisfiedclauses |
| --- | --- | --- | --- |
| 0 | 1 | 1 | 2 | | | 0 | 1 | 0 | 3 |
| --- | --- | --- | --- |
| 0 | 0 | 1 | 3 |
| 0 | 0 | 0 | 3 |
| 1 | 1 | 1 | 3 |
| 1 | 1 | 0 | 3 |
| 1 | 0 | 1 | 3 |
| 1 | 0 | 0 | 2 | | 1 |
| x | y | z | Numberofsatisfiedclauses |
| --- | --- | --- | --- |
| 0 | 1 | 1 | 2 | | | 1 | 0 | 1 | 0 | 1 | 1 | 1 |
| --- | --- | --- | --- | --- | --- | --- |
| 1 | 0 | 1 | 1 | 1 | 0 | 1 |
| 1 | 1 | 0 | 0 | 1 | 1 | * |
| 1 | 1 | 0 | 1 | 1 | 0 | * |
| 1 | 1 | 1 | 0 | 1 | 0 | * |
| 1 | 1 | 1 | 1 | * | * | * | | 0 |
| Method | Tweet2011 | GoogleNews |
| --- | --- | --- |
| LDA | 0.2809±0.0037 | 0.8669±0.0145 | | | MRF-LDA | 0.0504±0.0119 | 0.6642±0.0354 |
| --- | --- | --- |
| Unigrams | 0.3250±0.0139 | 0.8948±0.0184 |
| DMM | 0.3151±0.0126 | 0.8963±0.0501 |
| BTM | 0.0624±0.0123 | 0.8885±0.0319 |
| ETM | 0.3999±0.0095 | 0.9193±0.0193 | | 1 |
| Method | Tweet2011 | GoogleNews |
| --- | --- | --- |
| LDA | 0.2809±0.0037 | 0.8669±0.0145 | | | #Methods | | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| DATASET | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
| englishdailabor | 49.90 | 65.68 | 68.26 | 66.38 | 67.09 | 68.68 | 66.70 | 69.68 |
| aisoposntua | 41.90 | 59.21 | 57.78 | 61.56 | 59.99 | 58.13 | 59.78 | 65.21 |
| tweetsemevaltest | 39.54 | 56.31 | 61.51 | 61.65 | 62.06 | 62.94 | 62.26 | 62.64 |
| sentistrengthtwitter | 36.26 | 49.24 | 56.20 | 57.88 | 57.91 | 57.96 | 57.50 | 58.68 |
| sentistrengthyoutube | 38.14 | 50.01 | 54.98 | 56.56 | 57.13 | 55.83 | 55.45 | 56.93 |
| sentistrengthmyspace | 26.88 | 44.94 | 47.37 | 53.04 | 52.91 | 51.53 | 46.99 | 55.00 |
| sanders | 46.40 | 54.22 | 54.34 | 54.59 | 55.84 | 57.14 | 54.30 | 53.03 |
| sentistrengthdigg | 28.16 | 43.62 | 48.67 | 50.44 | 50.59 | 52.47 | 51.55 | 54.18 |
| sentistrengthrw | 30.47 | 42.60 | 50.37 | 48.30 | 49.55 | 48.61 | 47.39 | 47.30 |
| sentistrengthbbc | 21.92 | 35.79 | 45.35 | 47.15 | 48.41 | 49.45 | 47.34 | 45.72 |
| debate | 25.10 | 34.03 | 41.40 | 45.76 | 45.17 | 45.11 | 42.74 | 45.06 |
| nikolaosted | 24.42 | 34.82 | 41.32 | 42.44 | 46.19 | 44.11 | 44.80 | 42.56 |
| vadernyt | 9.38 | 19.64 | 30.27 | 34.97 | 37.42 | 36.83 | 36.98 | 37.97 | | 0 |
| Method | Tweet2011 | GoogleNews |
| --- | --- | --- |
| LDA | 0.2809±0.0037 | 0.8669±0.0145 |
| MRF-LDA | 0.0504±0.0119 | 0.6642±0.0354 |
| Unigrams | 0.3250±0.0139 | 0.8948±0.0184 |
| DMM | 0.3151±0.0126 | 0.8963±0.0501 | | | BTM | 0.0624±0.0123 | 0.8885±0.0319 |
| --- | --- | --- |
| ETM | 0.3999±0.0095 | 0.9193±0.0193 | | 1 |
| Method | Tweet2011 | GoogleNews |
| --- | --- | --- |
| LDA | 0.2809±0.0037 | 0.8669±0.0145 |
| MRF-LDA | 0.0504±0.0119 | 0.6642±0.0354 |
| Unigrams | 0.3250±0.0139 | 0.8948±0.0184 |
| DMM | 0.3151±0.0126 | 0.8963±0.0501 | | | nikolaosted | 24.42 | 34.82 | 41.32 | 42.44 | 46.19 | 44.11 | 44.80 | 42.56 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| vadernyt | 9.38 | 19.64 | 30.27 | 34.97 | 37.42 | 36.83 | 36.98 | 37.97 | | 0 |
| | k-means | boostk-means | | |
| --- | --- | --- | --- | --- |
| Initialassigment | k-way | bisecting | k-way | bisecting |
| Random | k-means | BsKM | BKM(rnd) | BsBKM(rnd) | | | Probabilitybased | k-means++ | BsBKM++ | BKM(kpp) | BsBKM(kpp) |
| --- | --- | --- | --- | --- |
| None | - | - | BKM(non) | BsBKM(non) | | 1 |
| | k-means | boostk-means | | |
| --- | --- | --- | --- | --- |
| Initialassigment | k-way | bisecting | k-way | bisecting |
| Random | k-means | BsKM | BKM(rnd) | BsBKM(rnd) | | | Methods | DiceCoefficient | HausdorffDistance |
| --- | --- | --- |
| k-meansclustering | 0.5249 | 169.745 |
| Meanshiftclustering | 0.3927 | 221.744 |
| DRLSE | 0.7104 | 95.0747 |
| GrabCut | 0.8311 | 42.629 |
| MIST | 0.8545 | 34.375 | | 0 |
| | k-means | boostk-means | | |
| --- | --- | --- | --- | --- |
| Initialassigment | k-way | bisecting | k-way | bisecting |
| Random | k-means | BsKM | BKM(rnd) | BsBKM(rnd) | | | Probabilitybased | k-means++ | BsBKM++ | BKM(kpp) | BsBKM(kpp) |
| --- | --- | --- | --- | --- |
| None | - | - | BKM(non) | BsBKM(non) | | 1 |
| | k-means | boostk-means | | |
| --- | --- | --- | --- | --- |
| Initialassigment | k-way | bisecting | k-way | bisecting |
| Random | k-means | BsKM | BKM(rnd) | BsBKM(rnd) | | | Meanshiftclustering | 0.3927 | 221.744 |
| --- | --- | --- |
| DRLSE | 0.7104 | 95.0747 |
| GrabCut | 0.8311 | 42.629 |
| MIST | 0.8545 | 34.375 | | 0 |
| Alg. | Samplingratio0.1 | Samplingratio0.2 | Samplingratio0.3 | Samplingratio0.4 |
| --- | --- | --- | --- | --- |
| DWT | 24.16\0.6798\32.46 | 28.13\0.7882\24.43 | 30.38\0.8389\15.75 | 31.99\0.8753\11.71 | | | TV | 25.24\0.6887\16.02 | 28.07\0.7844\13.34 | 30.12\0.8424\10.25 | 32.03\0.8837\8.42 |
| --- | --- | --- | --- | --- |
| MH | 26.38\0.7282\64.22 | 29.47\0.8237\60.33 | 31.37\0.8694\52.35 | 33.03\0.9009\44.18 |
| CoS | 18698.8227.20\0.7433\ | 17762.8430.07\0.8278\ | 17314.0432.03\0.8732\ | 15371.9734.00\0.9084\ |
| GSR | 27.50\0.7705\883.72 | 31.22\0.8642\883.08 | 33.74\0.9071\815.99 | 35.78\0.9336\799.38 |
| CSNet | 28.91\0.8119\0.12 | 31.86\0.8908\0.12 | 34.00\0.9276\0.12 | 35.95\0.9495\0.15 | | 1 |
| Alg. | Samplingratio0.1 | Samplingratio0.2 | Samplingratio0.3 | Samplingratio0.4 |
| --- | --- | --- | --- | --- |
| DWT | 24.16\0.6798\32.46 | 28.13\0.7882\24.43 | 30.38\0.8389\15.75 | 31.99\0.8753\11.71 | | | | | Our-Sampling | Our-Smooth |
| --- | --- | --- | --- |
| 51.7 | 27.5 | 40.6 | 45.9 |
| 17.5 | 33.3 | 39.8 | 40.6 |
| 34.4 | 27.8 | 33.3 | 36.4 |
| 34.7 | 34.1 | 34.1 | 33.9 |
| 22.3 | 42.0 | 35.3 | 35.3 |
| 17.9 | 28.4 | 18.9 | 22.1 |
| 13.5 | 35.7 | 27.0 | 27.2 |
| 26.7 | 35.6 | 21.9 | 25.2 |
| 41.2 | 22.0 | 17.6 | 20.0 |
| 25.0 | 25.0 | 32.6 | 35.8 |
| 28.5 | 31.1 | 30.1 | 32.2 | | 0 |
| Alg. | Samplingratio0.1 | Samplingratio0.2 | Samplingratio0.3 | Samplingratio0.4 |
| --- | --- | --- | --- | --- |
| DWT | 24.16\0.6798\32.46 | 28.13\0.7882\24.43 | 30.38\0.8389\15.75 | 31.99\0.8753\11.71 |
| TV | 25.24\0.6887\16.02 | 28.07\0.7844\13.34 | 30.12\0.8424\10.25 | 32.03\0.8837\8.42 | | | MH | 26.38\0.7282\64.22 | 29.47\0.8237\60.33 | 31.37\0.8694\52.35 | 33.03\0.9009\44.18 |
| --- | --- | --- | --- | --- |
| CoS | 18698.8227.20\0.7433\ | 17762.8430.07\0.8278\ | 17314.0432.03\0.8732\ | 15371.9734.00\0.9084\ |
| GSR | 27.50\0.7705\883.72 | 31.22\0.8642\883.08 | 33.74\0.9071\815.99 | 35.78\0.9336\799.38 |
| CSNet | 28.91\0.8119\0.12 | 31.86\0.8908\0.12 | 34.00\0.9276\0.12 | 35.95\0.9495\0.15 | | 1 |
| Alg. | Samplingratio0.1 | Samplingratio0.2 | Samplingratio0.3 | Samplingratio0.4 |
| --- | --- | --- | --- | --- |
| DWT | 24.16\0.6798\32.46 | 28.13\0.7882\24.43 | 30.38\0.8389\15.75 | 31.99\0.8753\11.71 |
| TV | 25.24\0.6887\16.02 | 28.07\0.7844\13.34 | 30.12\0.8424\10.25 | 32.03\0.8837\8.42 | | | 17.5 | 33.3 | 39.8 | 40.6 |
| --- | --- | --- | --- |
| 34.4 | 27.8 | 33.3 | 36.4 |
| 34.7 | 34.1 | 34.1 | 33.9 |
| 22.3 | 42.0 | 35.3 | 35.3 |
| 17.9 | 28.4 | 18.9 | 22.1 |
| 13.5 | 35.7 | 27.0 | 27.2 |
| 26.7 | 35.6 | 21.9 | 25.2 |
| 41.2 | 22.0 | 17.6 | 20.0 |
| 25.0 | 25.0 | 32.6 | 35.8 |
| 28.5 | 31.1 | 30.1 | 32.2 | | 0 |
| Algorithm | Strong<br>PRF | Weak<br>PRF |
| --- | --- | --- |
| Megvii-Image++ | 0.92530.79210.8535 | 0.90590.79000.8440 |
| Deep2TextII+ | 0.92270.73920.8208 | 0.89160.73780.8075 |
| Stradvision-2 | 0.83930.73020.7810 | 0.77610.70860.7408 |
| Deep2TextII-1 | 0.80970.73370.7698 | 0.80970.73370.7698 |
| StradVision-1 | 0.84720.70170.7676 | 0.78900.67870.7297 |
| Deep2TextI | 0.83460.61400.7075 | 0.83460.61400.7075 |
| PAL(v1.5) | 0.65220.61540.6333 | --- | | | NJUText(Version3) | 0.60120.41310.4897 | --- |
| --- | --- | --- |
| BaselineOpenCV3.0+Tesseract | 0.46480.37130.4128 | 0.47200.32820.3872 | | 1 |
| Algorithm | Strong<br>PRF | Weak<br>PRF |
| --- | --- | --- |
| Megvii-Image++ | 0.92530.79210.8535 | 0.90590.79000.8440 |
| Deep2TextII+ | 0.92270.73920.8208 | 0.89160.73780.8075 |
| Stradvision-2 | 0.83930.73020.7810 | 0.77610.70860.7408 |
| Deep2TextII-1 | 0.80970.73370.7698 | 0.80970.73370.7698 |
| StradVision-1 | 0.84720.70170.7676 | 0.78900.67870.7297 |
| Deep2TextI | 0.83460.61400.7075 | 0.83460.61400.7075 |
| PAL(v1.5) | 0.65220.61540.6333 | --- | | | Algorithm | Strong<br>PRF | Weak<br>PRF |
| --- | --- | --- |
| Megvii-Image++ | 0.57480.39380.4674 | 0.49190.3370.4 |
| Stradvision-2 | 0.67920.32210.4370 | --- |
| Baseline-TextSpotter | 0.62210.24410.3506 | 0.24960.16560.1991 |
| StradVisionv1 | 0.28510.39770.3321 | --- |
| NJUText(Version3) | 0.4880.24510.3263 | --- |
| BeamsearchCUNI | 0.37830.15650.2214 | 0.33720.14010.1980 |
| Deep2Text-MO | 0.21340.13820.1677 | 0.21340.13820.1677 |
| Baseline(OpenCV+Tesseract) | 0.4090.08330.1384 | 0.32480.07370.1201 |
| BeamsearchCUNI+S | 0.81080.07220.1326 | 0.05920.64740.1085 | | 0 |
| Algorithm | Strong<br>PRF | Weak<br>PRF |
| --- | --- | --- |
| Megvii-Image++ | 0.92530.79210.8535 | 0.90590.79000.8440 |
| Deep2TextII+ | 0.92270.73920.8208 | 0.89160.73780.8075 |
| Stradvision-2 | 0.83930.73020.7810 | 0.77610.70860.7408 |
| Deep2TextII-1 | 0.80970.73370.7698 | 0.80970.73370.7698 |
| StradVision-1 | 0.84720.70170.7676 | 0.78900.67870.7297 |
| Deep2TextI | 0.83460.61400.7075 | 0.83460.61400.7075 | | | PAL(v1.5) | 0.65220.61540.6333 | --- |
| --- | --- | --- |
| NJUText(Version3) | 0.60120.41310.4897 | --- |
| BaselineOpenCV3.0+Tesseract | 0.46480.37130.4128 | 0.47200.32820.3872 | | 1 |
| Algorithm | Strong<br>PRF | Weak<br>PRF |
| --- | --- | --- |
| Megvii-Image++ | 0.92530.79210.8535 | 0.90590.79000.8440 |
| Deep2TextII+ | 0.92270.73920.8208 | 0.89160.73780.8075 |
| Stradvision-2 | 0.83930.73020.7810 | 0.77610.70860.7408 |
| Deep2TextII-1 | 0.80970.73370.7698 | 0.80970.73370.7698 |
| StradVision-1 | 0.84720.70170.7676 | 0.78900.67870.7297 |
| Deep2TextI | 0.83460.61400.7075 | 0.83460.61400.7075 | | | Baseline(OpenCV+Tesseract) | 0.4090.08330.1384 | 0.32480.07370.1201 |
| --- | --- | --- |
| BeamsearchCUNI+S | 0.81080.07220.1326 | 0.05920.64740.1085 | | 0 |
| F(i)n | F(i)l,m | \|F(i)−F(i)\|nl,m |
| --- | --- | --- |
| 23 | 22 | 1 |
| 68 | 67 | 1 |
| 124 | 123 | 1 |
| 150 | 148 | 2 |
| 198 | 196 | 2 |
| 249 | 248 | 2 |
| 304 | 300 | 4 |
| 412 | 408 | 4 |
| 476 | 472 | 4 | | | 567 | 560 | 7 |
| --- | --- | --- |
| 848 | 840 | 8 |
| 999 | 992 | 7 |
| 1103 | 1088 | 15 |
| 1872 | 1856 | 16 |
| 2063 | 2048 | 15 |
| 2360 | 2336 | 24 |
| 3328 | 3296 | 32 |
| 3871 | 3840 | 31 | | 1 |
| F(i)n | F(i)l,m | \|F(i)−F(i)\|nl,m |
| --- | --- | --- |
| 23 | 22 | 1 |
| 68 | 67 | 1 |
| 124 | 123 | 1 |
| 150 | 148 | 2 |
| 198 | 196 | 2 |
| 249 | 248 | 2 |
| 304 | 300 | 4 |
| 412 | 408 | 4 |
| 476 | 472 | 4 | | | N= | K=10 | K=15 | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| PTP | RTP | VBP | PTP | RTP | VBP | |
| 10 | 32959 | 28147 | 31048 | 42093 | 38372 | 38727 |
| 20 | 21440 | 18449 | 21562 | 26905 | 24586 | 28958 |
| 30 | 17557 | 15756 | 16635 | 20421 | 18963 | 22486 |
| 40 | 15634 | 14004 | 14412 | 17458 | 16464 | 18394 |
| 50 | 14269 | 12931 | 13028 | 15377 | 14690 | 16037 |
| 60 | 13189 | 12179 | 11968 | 14148 | 13542 | 14380 |
| 70 | 12294 | 11361 | 11240 | 13230 | 12652 | 13194 |
| 80 | 11381 | 10680 | 10559 | 12433 | 11982 | 12254 |
| 90 | 10617 | 9873 | 10109 | 11677 | 11313 | 11472 | | 0 |
| F(i)n | F(i)l,m | \|F(i)−F(i)\|nl,m |
| --- | --- | --- |
| 23 | 22 | 1 |
| 68 | 67 | 1 | | | 124 | 123 | 1 |
| --- | --- | --- |
| 150 | 148 | 2 |
| 198 | 196 | 2 |
| 249 | 248 | 2 |
| 304 | 300 | 4 |
| 412 | 408 | 4 |
| 476 | 472 | 4 |
| 567 | 560 | 7 |
| 848 | 840 | 8 |
| 999 | 992 | 7 |
| 1103 | 1088 | 15 |
| 1872 | 1856 | 16 |
| 2063 | 2048 | 15 |
| 2360 | 2336 | 24 |
| 3328 | 3296 | 32 |
| 3871 | 3840 | 31 | | 1 |
| F(i)n | F(i)l,m | \|F(i)−F(i)\|nl,m |
| --- | --- | --- |
| 23 | 22 | 1 |
| 68 | 67 | 1 | | | 30 | 17557 | 15756 | 16635 | 20421 | 18963 | 22486 |
| --- | --- | --- | --- | --- | --- | --- |
| 40 | 15634 | 14004 | 14412 | 17458 | 16464 | 18394 |
| 50 | 14269 | 12931 | 13028 | 15377 | 14690 | 16037 |
| 60 | 13189 | 12179 | 11968 | 14148 | 13542 | 14380 |
| 70 | 12294 | 11361 | 11240 | 13230 | 12652 | 13194 |
| 80 | 11381 | 10680 | 10559 | 12433 | 11982 | 12254 |
| 90 | 10617 | 9873 | 10109 | 11677 | 11313 | 11472 | | 0 |
| Category |
| --- |
| Punctuation |
| POS |
| Sentiment |
| Emotion | | | SocialMedia |
| --- |
| Length |
| URLs |
| Novelty |
| PseudoFeedback | | 1 |
| Category |
| --- |
| Punctuation |
| POS |
| Sentiment |
| Emotion | | | Numberofwords | | | |
| --- | --- | --- | --- |
| 1Quartile | 2Quartile(Median) | 3Quartile | |
| Stanford | 5 | 15 | 18,5 |
| Yelp | 15,5 | 36 | 67,6 |
| Debate | 12 | 15,5 | 18 |
| ReviewsI | 19 | 13 | 32,5 |
| TwitterI | 14 | 20 | 23,5 |
| Myspace | 12 | 18 | 17 |
| Youtube | 6 | 11 | 26 |
| Digg | 5,5 | 15 | 19 |
| RW | 20 | 27 | 104 |
| BBC | 14 | 68 | 17 |
| Amazon | 14 | 10 | 4 |
| NYT | 18 | 8 | 6 |
| TweetsII | 8 | 10 | 15 |
| ReviewsII | 20 | 11 | 10 |
| Tricky | 10 | 12 | 11 | | 0 |
| Category |
| --- |
| Punctuation |
| POS |
| Sentiment |
| Emotion |
| SocialMedia | | | Length |
| --- |
| URLs |
| Novelty |
| PseudoFeedback | | 1 |
| Category |
| --- |
| Punctuation |
| POS |
| Sentiment |
| Emotion |
| SocialMedia | | | Amazon | 14 | 10 | 4 |
| --- | --- | --- | --- |
| NYT | 18 | 8 | 6 |
| TweetsII | 8 | 10 | 15 |
| ReviewsII | 20 | 11 | 10 |
| Tricky | 10 | 12 | 11 | | 0 |
| Testset | Duration | Nb.speakers | Nb.words |
| --- | --- | --- | --- |
| Hub5’00SWB | 2.1h | 40 | 21.4K |
| Hub5’00CH | 1.6h | 40 | 21.6K |
| RT’02 | 6.4h | 120 | 64.0K |
| RT’03 | 7.2h | 144 | 76.0K | | | RT’04 | 3.4h | 72 | 36.7K |
| --- | --- | --- | --- |
| DEV’04f | 3.2h | 72 | 37.8K | | 1 |
| Testset | Duration | Nb.speakers | Nb.words |
| --- | --- | --- | --- |
| Hub5’00SWB | 2.1h | 40 | 21.4K |
| Hub5’00CH | 1.6h | 40 | 21.6K |
| RT’02 | 6.4h | 120 | 64.0K |
| RT’03 | 7.2h | 144 | 76.0K | | | Channel | Type | Year(s) | h | #Words |
| --- | --- | --- | --- | --- |
| Trainingset | | | | |
| DLF<br>SWR2<br>SWR2Info<br>WDR2<br>NDR4 | Radio<br>Radio<br>Radio<br>Radio<br>Radio | 2000–01<br>2000<br>2000<br>2000<br>2000 | 67.81<br>38.42<br>1.88<br>26.75<br>11.41 | 535K<br>333K<br>18K<br>224K<br>98K |
| total | | | 146.28 | 1209K |
| Developmentset | | | | |
| ARD | TV | 2000–01 | 8.93 | 84K |
| Testset | | | | |
| DW | Radio | 2000–01 | 6.33 | 50K | | 0 |
| Testset | Duration | Nb.speakers | Nb.words |
| --- | --- | --- | --- |
| Hub5’00SWB | 2.1h | 40 | 21.4K |
| Hub5’00CH | 1.6h | 40 | 21.6K |
| RT’02 | 6.4h | 120 | 64.0K | | | RT’03 | 7.2h | 144 | 76.0K |
| --- | --- | --- | --- |
| RT’04 | 3.4h | 72 | 36.7K |
| DEV’04f | 3.2h | 72 | 37.8K | | 1 |
| Testset | Duration | Nb.speakers | Nb.words |
| --- | --- | --- | --- |
| Hub5’00SWB | 2.1h | 40 | 21.4K |
| Hub5’00CH | 1.6h | 40 | 21.6K |
| RT’02 | 6.4h | 120 | 64.0K | | | total | | | 146.28 | 1209K |
| --- | --- | --- | --- | --- |
| Developmentset | | | | |
| ARD | TV | 2000–01 | 8.93 | 84K |
| Testset | | | | |
| DW | Radio | 2000–01 | 6.33 | 50K | | 0 |
| Model | PredictionAccuracy |
| --- | --- |
| NIN | 0.8677 |
| VGG | 0.8914 |
| ResNet32 | 0.9181 |
| ResNet44 | 0.9243 | | | ResNet56 | 0.9272 |
| --- | --- |
| ResNet110 | 0.9399 | | 1 |
| Model | PredictionAccuracy |
| --- | --- |
| NIN | 0.8677 |
| VGG | 0.8914 |
| ResNet32 | 0.9181 |
| ResNet44 | 0.9243 | | | Model | Pre | Rec | F1 |
| --- | --- | --- | --- |
| MLN | 0.802 | 0.764 | 0.782 |
| PSL | 0.810 | 0.772 | 0.791 |
| SVM | 0.720 | 0.737 | 0.728 |
| CF | 0.701 | 0.694 | 0.697 | | 0 |
| Model | PredictionAccuracy |
| --- | --- |
| NIN | 0.8677 |
| VGG | 0.8914 |
| ResNet32 | 0.9181 |
| ResNet44 | 0.9243 | | | ResNet56 | 0.9272 |
| --- | --- |
| ResNet110 | 0.9399 | | 1 |
| Model | PredictionAccuracy |
| --- | --- |
| NIN | 0.8677 |
| VGG | 0.8914 |
| ResNet32 | 0.9181 |
| ResNet44 | 0.9243 | | | PSL | 0.810 | 0.772 | 0.791 |
| --- | --- | --- | --- |
| SVM | 0.720 | 0.737 | 0.728 |
| CF | 0.701 | 0.694 | 0.697 | | 0 |
| Edge | Iteration | | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| | 1 | 2 | 3 | 4 | 5 | ≥14 |
| 1-2 | 0.82 | 0.91 | 0.94 | 0.95 | 0.97 | 1.00 |
| 1-3 | 0.66 | 0.82 | 0.89 | 0.93 | 0.95 | 1.00 |
| 1-10 | 0.33 | 0.24 | 0.17 | 0.13 | 0.09 | 0.00 |
| 2-3 | 0.82 | 0.91 | 0.95 | 0.97 | 0.99 | 1.00 |
| 3-4 | 0.33 | 0.18 | 0.10 | 0.05 | 0.02 | 0.00 |
| 4-5 | 0.82 | 0.91 | 0.95 | 0.97 | 0.99 | 1.00 |
| 4-6 | 0.66 | 0.82 | 0.89 | 0.93 | 0.95 | 1.00 | | | 5-6 | 0.82 | 0.91 | 0.94 | 0.95 | 0.97 | 1.00 |
| --- | --- | --- | --- | --- | --- | --- |
| 6-7 | 0.33 | 0.24 | 0.17 | 0.13 | 0.09 | 0.00 |
| 7-10 | 0.33 | 0.31 | 0.32 | 0.35 | 0.38 | 0.50 |
| 7-8 | 0.41 | 0.41 | 0.43 | 0.45 | 0.46 | 0.50 |
| 8-9 | 0.50 | 0.55 | 0.57 | 0.57 | 0.56 | 0.50 |
| 9-10 | 0.41 | 0.41 | 0.43 | 0.45 | 0.46 | 0.50 | | 1 |
| Edge | Iteration | | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| | 1 | 2 | 3 | 4 | 5 | ≥14 |
| 1-2 | 0.82 | 0.91 | 0.94 | 0.95 | 0.97 | 1.00 |
| 1-3 | 0.66 | 0.82 | 0.89 | 0.93 | 0.95 | 1.00 |
| 1-10 | 0.33 | 0.24 | 0.17 | 0.13 | 0.09 | 0.00 |
| 2-3 | 0.82 | 0.91 | 0.95 | 0.97 | 0.99 | 1.00 |
| 3-4 | 0.33 | 0.18 | 0.10 | 0.05 | 0.02 | 0.00 |
| 4-5 | 0.82 | 0.91 | 0.95 | 0.97 | 0.99 | 1.00 |
| 4-6 | 0.66 | 0.82 | 0.89 | 0.93 | 0.95 | 1.00 | | | 200 | 400 | 600 | 800 |
| --- | --- | --- | --- |
| 0.965 | 0.967 | 0.967 | 0.967 |
| 0.968 | 0.970 | 0.970 | 0.968 |
| 0.968 | 0.968 | 0.967 | 0.968 |
| 0.969 | 0.972 | 0.970 | 0.969 |
| 0.831 | 0.842 | 0.845 | 0.846 |
| 0.846 | 0.851 | 0.852 | 0.853 |
| 0.842 | 0.849 | 0.854 | 0.849 |
| 0.876 | 0.874 | 0.866 | 0.868 |
| 0.658 | 0.650 | 0.654 | 0.655 |
| 0.712 | 0.705 | 0.701 | 0.702 |
| 0.680 | 0.690 | 0.694 | 0.695 |
| 0.715 | 0.709 | 0.714 | 0.715 | | 0 |
| Edge | Iteration | | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| | 1 | 2 | 3 | 4 | 5 | ≥14 |
| 1-2 | 0.82 | 0.91 | 0.94 | 0.95 | 0.97 | 1.00 |
| 1-3 | 0.66 | 0.82 | 0.89 | 0.93 | 0.95 | 1.00 |
| 1-10 | 0.33 | 0.24 | 0.17 | 0.13 | 0.09 | 0.00 |
| 2-3 | 0.82 | 0.91 | 0.95 | 0.97 | 0.99 | 1.00 |
| 3-4 | 0.33 | 0.18 | 0.10 | 0.05 | 0.02 | 0.00 | | | 4-5 | 0.82 | 0.91 | 0.95 | 0.97 | 0.99 | 1.00 |
| --- | --- | --- | --- | --- | --- | --- |
| 4-6 | 0.66 | 0.82 | 0.89 | 0.93 | 0.95 | 1.00 |
| 5-6 | 0.82 | 0.91 | 0.94 | 0.95 | 0.97 | 1.00 |
| 6-7 | 0.33 | 0.24 | 0.17 | 0.13 | 0.09 | 0.00 |
| 7-10 | 0.33 | 0.31 | 0.32 | 0.35 | 0.38 | 0.50 |
| 7-8 | 0.41 | 0.41 | 0.43 | 0.45 | 0.46 | 0.50 |
| 8-9 | 0.50 | 0.55 | 0.57 | 0.57 | 0.56 | 0.50 |
| 9-10 | 0.41 | 0.41 | 0.43 | 0.45 | 0.46 | 0.50 | | 1 |
| Edge | Iteration | | | | | |
| --- | --- | --- | --- | --- | --- | --- |
| | 1 | 2 | 3 | 4 | 5 | ≥14 |
| 1-2 | 0.82 | 0.91 | 0.94 | 0.95 | 0.97 | 1.00 |
| 1-3 | 0.66 | 0.82 | 0.89 | 0.93 | 0.95 | 1.00 |
| 1-10 | 0.33 | 0.24 | 0.17 | 0.13 | 0.09 | 0.00 |
| 2-3 | 0.82 | 0.91 | 0.95 | 0.97 | 0.99 | 1.00 |
| 3-4 | 0.33 | 0.18 | 0.10 | 0.05 | 0.02 | 0.00 | | | 0.876 | 0.874 | 0.866 | 0.868 |
| --- | --- | --- | --- |
| 0.658 | 0.650 | 0.654 | 0.655 |
| 0.712 | 0.705 | 0.701 | 0.702 |
| 0.680 | 0.690 | 0.694 | 0.695 |
| 0.715 | 0.709 | 0.714 | 0.715 | | 0 |
| DataSet | Size | Released | Visible | Difficulty |
| --- | --- | --- | --- | --- |
| DS0 | 50×5 | Yes | Yes | Easy |
| DS1 | 1000×5 | Yes | No | Medium | | | DS2 | 1000×5 | Yes | No | Difficult |
| --- | --- | --- | --- | --- |
| DS3 | 1000×5 | No | No | Hard | | 1 |
| DataSet | Size | Released | Visible | Difficulty |
| --- | --- | --- | --- | --- |
| DS0 | 50×5 | Yes | Yes | Easy |
| DS1 | 1000×5 | Yes | No | Medium | | | Dataset | Numberoffeatures | Numberofinstances | Numberofclasses |
| --- | --- | --- | --- |
| connect-4 | 42 | 67,557 | 3 |
| splice | 60 | 3,175 | 3 |
| waveform | 40 | 5,000 | 3 |
| landsat | 36 | 6,435 | 6 |
| lung | 325 | 73 | 7 |
| lymph | 4,026 | 96 | 9 |
| NCI9 | 9,712 | 60 | 9 | | 0 |
| DataSet | Size | Released | Visible | Difficulty |
| --- | --- | --- | --- | --- |
| DS0 | 50×5 | Yes | Yes | Easy |
| DS1 | 1000×5 | Yes | No | Medium | | | DS2 | 1000×5 | Yes | No | Difficult |
| --- | --- | --- | --- | --- |
| DS3 | 1000×5 | No | No | Hard | | 1 |
| DataSet | Size | Released | Visible | Difficulty |
| --- | --- | --- | --- | --- |
| DS0 | 50×5 | Yes | Yes | Easy |
| DS1 | 1000×5 | Yes | No | Medium | | | splice | 60 | 3,175 | 3 |
| --- | --- | --- | --- |
| waveform | 40 | 5,000 | 3 |
| landsat | 36 | 6,435 | 6 |
| lung | 325 | 73 | 7 |
| lymph | 4,026 | 96 | 9 |
| NCI9 | 9,712 | 60 | 9 | | 0 |
| Model | Pre | Rec | F1 |
| --- | --- | --- | --- |
| MLN | 0.802 | 0.764 | 0.782 | | | PSL | 0.810 | 0.772 | 0.791 |
| --- | --- | --- | --- |
| SVM | 0.720 | 0.737 | 0.728 |
| CF | 0.701 | 0.694 | 0.697 | | 1 |
| Model | Pre | Rec | F1 |
| --- | --- | --- | --- |
| MLN | 0.802 | 0.764 | 0.782 | | | Framework | Model | CIR | COL | IBD | OBE | T2D | WT2 | AVG |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| MetAML | RF | 0.877 | 0.805 | 0.809 | 0.644 | 0.664 | 0.703 | 0.750 |
| | SVM | 0.834 | 0.743 | 0.809 | 0.636 | 0.613 | 0.596 | 0.705 |
| Met2Img | RF | 0.877 | 0.812 | 0.808 | 0.645 | 0.672 | 0.703 | 0.753 |
| | SVM-Sigmoid | 0.509 | 0.603 | 0.775 | 0.648 | 0.515 | 0.553 | 0.600 |
| | SVM-Radial | 0.529 | 0.603 | 0.775 | 0.648 | 0.593 | 0.553 | 0.617 |
| | SVM-Linear | 0.766 | 0.666 | 0.792 | 0.612 | 0.634 | 0.676 | 0.691 |
| | FC | 0.776 | 0.685 | 0.775 | 0.656 | 0.665 | 0.607 | 0.694 |
| | CNN1D | 0.775 | 0.722 | 0.842 | 0.663 | 0.668 | 0.618 | 0.715 | | 0 |
| Model | Pre | Rec | F1 |
| --- | --- | --- | --- |
| MLN | 0.802 | 0.764 | 0.782 |
| PSL | 0.810 | 0.772 | 0.791 | | | SVM | 0.720 | 0.737 | 0.728 |
| --- | --- | --- | --- |
| CF | 0.701 | 0.694 | 0.697 | | 1 |
| Model | Pre | Rec | F1 |
| --- | --- | --- | --- |
| MLN | 0.802 | 0.764 | 0.782 |
| PSL | 0.810 | 0.772 | 0.791 | | | | SVM-Radial | 0.529 | 0.603 | 0.775 | 0.648 | 0.593 | 0.553 | 0.617 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | SVM-Linear | 0.766 | 0.666 | 0.792 | 0.612 | 0.634 | 0.676 | 0.691 |
| | FC | 0.776 | 0.685 | 0.775 | 0.656 | 0.665 | 0.607 | 0.694 |
| | CNN1D | 0.775 | 0.722 | 0.842 | 0.663 | 0.668 | 0.618 | 0.715 | | 0 |
| 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 | | 1 |
| 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 | | | 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 | | 0 |
| 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 | | 1 |
| 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 | | | | | +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 | | 0 |
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