premise string | hypothesis string | label int64 |
|---|---|---|
| GPUconfig | Amountorcount |
| --- | --- |
| NumberofSM | 16 | | | NumberofSPperSM | 192 |
| --- | --- |
| Sharedmemoryperblock | 49,152bytes |
| Maximumthreadsperblock | 1024 |
| Totalconstantmemoryperdevice | 65,535bytes |
| Maximumno.ofthreadsperSM | 2048 | | 1 |
| GPUconfig | Amountorcount |
| --- | --- |
| NumberofSM | 16 | | | | TeslaK40t |
| --- | --- |
| GPUchip | GK110BGL |
| Computecapability | 3.5 |
| GPUmemory(GDDR5SGRAM) | 12288MiB |
| Memorybuswidth | 384bits |
| Peakmemoryclockrate | 3004MHz |
| Theoreticalmemorybandwidth | 268.58GiB/s |
| NumberofSMXprocessors | 15 |
| Max32-bitregistersperSIMDprocessor | 65536 |
| Maxsharedmemoryperthreadblock | 49152bytes |
| L2cachesize | 1.50MiB | | 0 |
| GPUconfig | Amountorcount |
| --- | --- |
| NumberofSM | 16 |
| NumberofSPperSM | 192 |
| Sharedmemoryperblock | 49,152bytes | | | Maximumthreadsperblock | 1024 |
| --- | --- |
| Totalconstantmemoryperdevice | 65,535bytes |
| Maximumno.ofthreadsperSM | 2048 | | 1 |
| GPUconfig | Amountorcount |
| --- | --- |
| NumberofSM | 16 |
| NumberofSPperSM | 192 |
| Sharedmemoryperblock | 49,152bytes | | | Computecapability | 3.5 |
| --- | --- |
| GPUmemory(GDDR5SGRAM) | 12288MiB |
| Memorybuswidth | 384bits |
| Peakmemoryclockrate | 3004MHz |
| Theoreticalmemorybandwidth | 268.58GiB/s |
| NumberofSMXprocessors | 15 |
| Max32-bitregistersperSIMDprocessor | 65536 |
| Maxsharedmemoryperthreadblock | 49152bytes |
| L2cachesize | 1.50MiB | | 0 |
| Metric | Dev | Test |
| --- | --- | --- |
| Tokens | 291,746 | 216,473 |
| Sentences | 15,084 | 11,623 |
| SpanPrecision | 93.42 | 93.04 |
| Recall | 94.21 | 94.34 |
| F1 | 93.81 | 93.69 |
| FramePrecision | 93.47 | 93.20 |
| Recall | 94.16 | 94.08 |
| F1 | 93.81 | 93.64 |
| TypePrecision | 85.56 | 85.67 |
| Recall | 86.20 | 86.49 |
| F1 | 85.88 | 86.08 |
| RolePrecision | 70.21 | 69.59 |
| Recall | 69.11 | 69.20 | | | F1 | 69.65 | 69.39 |
| --- | --- | --- |
| LabelPrecision | 96.51 | 95.02 |
| Recall | 94.97 | 90.70 |
| F1 | 95.73 | 92.81 |
| SlotPrecision | 80.00 | 79.81 |
| Recall | 79.90 | 80.10 |
| F1 | 79.95 | 79.96 |
| CombinedPrecision | 87.46 | 87.20 |
| Recall | 87.79 | 87.91 |
| F1 | 87.63 | 87.55 | | 1 |
| Metric | Dev | Test |
| --- | --- | --- |
| Tokens | 291,746 | 216,473 |
| Sentences | 15,084 | 11,623 |
| SpanPrecision | 93.42 | 93.04 |
| Recall | 94.21 | 94.34 |
| F1 | 93.81 | 93.69 |
| FramePrecision | 93.47 | 93.20 |
| Recall | 94.16 | 94.08 |
| F1 | 93.81 | 93.64 |
| TypePrecision | 85.56 | 85.67 |
| Recall | 86.20 | 86.49 |
| F1 | 85.88 | 86.08 |
| RolePrecision | 70.21 | 69.59 |
| Recall | 69.11 | 69.20 | | | | | Precision | Recall | F1 |
| --- | --- | --- | --- | --- |
| Partial | GS+noEP | 79.40 | 79.96 | 79.68 |
| GS+EP | 65.93 | 79.96 | 72.27 | |
| Auto+EP | 64.40 | 51.68 | 57.34 | |
| Exact | GS+noEP | 65.72 | 66.19 | 65.95 |
| GS+EP | 54.57 | 66.19 | 59.82 | |
| Auto+EP | 47.83 | 38.39 | 42.59 | | | 0 |
| Metric | Dev | Test |
| --- | --- | --- |
| Tokens | 291,746 | 216,473 |
| Sentences | 15,084 | 11,623 |
| SpanPrecision | 93.42 | 93.04 |
| Recall | 94.21 | 94.34 |
| F1 | 93.81 | 93.69 |
| FramePrecision | 93.47 | 93.20 |
| Recall | 94.16 | 94.08 |
| F1 | 93.81 | 93.64 |
| TypePrecision | 85.56 | 85.67 |
| Recall | 86.20 | 86.49 |
| F1 | 85.88 | 86.08 |
| RolePrecision | 70.21 | 69.59 |
| Recall | 69.11 | 69.20 |
| F1 | 69.65 | 69.39 |
| LabelPrecision | 96.51 | 95.02 |
| Recall | 94.97 | 90.70 |
| F1 | 95.73 | 92.81 |
| SlotPrecision | 80.00 | 79.81 |
| Recall | 79.90 | 80.10 |
| F1 | 79.95 | 79.96 |
| CombinedPrecision | 87.46 | 87.20 | | | Recall | 87.79 | 87.91 |
| --- | --- | --- |
| F1 | 87.63 | 87.55 | | 1 |
| Metric | Dev | Test |
| --- | --- | --- |
| Tokens | 291,746 | 216,473 |
| Sentences | 15,084 | 11,623 |
| SpanPrecision | 93.42 | 93.04 |
| Recall | 94.21 | 94.34 |
| F1 | 93.81 | 93.69 |
| FramePrecision | 93.47 | 93.20 |
| Recall | 94.16 | 94.08 |
| F1 | 93.81 | 93.64 |
| TypePrecision | 85.56 | 85.67 |
| Recall | 86.20 | 86.49 |
| F1 | 85.88 | 86.08 |
| RolePrecision | 70.21 | 69.59 |
| Recall | 69.11 | 69.20 |
| F1 | 69.65 | 69.39 |
| LabelPrecision | 96.51 | 95.02 |
| Recall | 94.97 | 90.70 |
| F1 | 95.73 | 92.81 |
| SlotPrecision | 80.00 | 79.81 |
| Recall | 79.90 | 80.10 |
| F1 | 79.95 | 79.96 |
| CombinedPrecision | 87.46 | 87.20 | | | Exact | GS+noEP | 65.72 | 66.19 | 65.95 |
| --- | --- | --- | --- | --- |
| GS+EP | 54.57 | 66.19 | 59.82 | |
| Auto+EP | 47.83 | 38.39 | 42.59 | | | 0 |
| Dataset | No.of<br>Pages | No.of<br>SFAs | Sizeas: |
| --- | --- | --- | --- |
| SFAs | Text | | | | | Cong.Acts(CA) | 38 | 1590 | 533MB | 90kB |
| --- | --- | --- | --- | --- |
| EnglishLit.(LT) | 32 | 1211 | 524MB | 78kB |
| DBPapers(DB) | 16 | 627 | 359MB | 54kB | | 1 |
| Dataset | No.of<br>Pages | No.of<br>SFAs | Sizeas: |
| --- | --- | --- | --- |
| SFAs | Text | | | | | Dataset | #triples | ntFileSize |
| --- | --- | --- |
| LUBM1K | 133M | 22GB |
| LUBM2K | 267M | 43GB |
| LUBM10K | 1,334M | 213GB |
| Wikidata | 233M | 37GB | | 0 |
| Dataset | No.of<br>Pages | No.of<br>SFAs | Sizeas: |
| --- | --- | --- | --- |
| SFAs | Text | | | | | Cong.Acts(CA) | 38 | 1590 | 533MB | 90kB |
| --- | --- | --- | --- | --- |
| EnglishLit.(LT) | 32 | 1211 | 524MB | 78kB |
| DBPapers(DB) | 16 | 627 | 359MB | 54kB | | 1 |
| Dataset | No.of<br>Pages | No.of<br>SFAs | Sizeas: |
| --- | --- | --- | --- |
| SFAs | Text | | | | | LUBM2K | 267M | 43GB |
| --- | --- | --- |
| LUBM10K | 1,334M | 213GB |
| Wikidata | 233M | 37GB | | 0 |
| Sigma | Index | Methods | | | |
| --- | --- | --- | --- | --- | --- |
| Noisy | LSCD | CBM3D | WLRTR | | |
| 10 | PSNR | 28.13 | 33.85 | 35.90 | 35.91 |
| SSIM | 0.7020 | 0.9188 | 0.9501 | 0.9511 | |
| 20 | PSNR | 22.17 | 30.26 | 31.85 | 31.94 |
| SSIM | 0.4580 | 0.8469 | 0.8923 | 0.8953 | |
| 30 | PSNR | 18.58 | 28.22 | 29.69 | 29.87 | | | SSIM | 0.3223 | 0.7854 | 0.8402 | 0.8444 | |
| --- | --- | --- | --- | --- | --- |
| 40 | PSNR | 16.08 | 27.00 | 28.10 | 28.47 |
| SSIM | 0.2388 | 0.7417 | 0.7872 | 0.7973 | | | 1 |
| Sigma | Index | Methods | | | |
| --- | --- | --- | --- | --- | --- |
| Noisy | LSCD | CBM3D | WLRTR | | |
| 10 | PSNR | 28.13 | 33.85 | 35.90 | 35.91 |
| SSIM | 0.7020 | 0.9188 | 0.9501 | 0.9511 | |
| 20 | PSNR | 22.17 | 30.26 | 31.85 | 31.94 |
| SSIM | 0.4580 | 0.8469 | 0.8923 | 0.8953 | |
| 30 | PSNR | 18.58 | 28.22 | 29.69 | 29.87 | | | Method | FRGC4× | FRGC8× | | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| PSNR | SSIM | IFC | WPSNR | NQM | PSNR | SSIM | IFC | WPSNR | NQM | |
| NN | 25.39 | 0.694 | 1.25 | 35.17 | 6.94 | 21.95 | 0.466 | 0.39 | 28.79 | 3.49 |
| Bicubic | 27.39 | 0.797 | 1.84 | 36.04 | 9.09 | 23.71 | 0.617 | 0.84 | 30.27 | 5.29 |
| KK | 28.06 | 0.825 | 2.10 | 37.34 | 9.72 | 24.11 | 0.631 | 0.89 | 30.85 | 5.74 |
| SRCNN | 28.19 | 0.829 | 2.10 | 37.47 | 9.91 | 24.18 | 0.641 | 0.91 | 30.89 | 5.84 |
| LSF | 25.64 | 0.723 | 1.28 | 33.56 | 7.42 | 23.21 | 0.614 | 0.76 | 30.35 | 4.90 |
| MZQ | 29.22 | 0.857 | 2.22 | 38.67 | 11.21 | 25.81 | 0.752 | 1.34 | 33.17 | 7.67 |
| YLY | 26.80 | 0.791 | 1.79 | 35.67 | 8.55 | 22.57 | 0.602 | 0.83 | 29.45 | 4.21 |
| BCCNN | 28.67 | 0.842 | 2.13 | 37.98 | 10.63 | 25.70 | 0.749 | 1.34 | 32.90 | 7.60 |
| GLN | 30.34 | 0.884 | 2.66 | 40.94 | 12.37 | 26.75 | 0.787 | 1.56 | 34.37 | 8.60 | | 0 |
| Sigma | Index | Methods | | | |
| --- | --- | --- | --- | --- | --- |
| Noisy | LSCD | CBM3D | WLRTR | | |
| 10 | PSNR | 28.13 | 33.85 | 35.90 | 35.91 |
| SSIM | 0.7020 | 0.9188 | 0.9501 | 0.9511 | |
| 20 | PSNR | 22.17 | 30.26 | 31.85 | 31.94 |
| SSIM | 0.4580 | 0.8469 | 0.8923 | 0.8953 | |
| 30 | PSNR | 18.58 | 28.22 | 29.69 | 29.87 |
| SSIM | 0.3223 | 0.7854 | 0.8402 | 0.8444 | | | | 40 | PSNR | 16.08 | 27.00 | 28.10 | 28.47 |
| --- | --- | --- | --- | --- | --- |
| SSIM | 0.2388 | 0.7417 | 0.7872 | 0.7973 | | | 1 |
| Sigma | Index | Methods | | | |
| --- | --- | --- | --- | --- | --- |
| Noisy | LSCD | CBM3D | WLRTR | | |
| 10 | PSNR | 28.13 | 33.85 | 35.90 | 35.91 |
| SSIM | 0.7020 | 0.9188 | 0.9501 | 0.9511 | |
| 20 | PSNR | 22.17 | 30.26 | 31.85 | 31.94 |
| SSIM | 0.4580 | 0.8469 | 0.8923 | 0.8953 | |
| 30 | PSNR | 18.58 | 28.22 | 29.69 | 29.87 |
| SSIM | 0.3223 | 0.7854 | 0.8402 | 0.8444 | | | | NN | 25.39 | 0.694 | 1.25 | 35.17 | 6.94 | 21.95 | 0.466 | 0.39 | 28.79 | 3.49 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Bicubic | 27.39 | 0.797 | 1.84 | 36.04 | 9.09 | 23.71 | 0.617 | 0.84 | 30.27 | 5.29 |
| KK | 28.06 | 0.825 | 2.10 | 37.34 | 9.72 | 24.11 | 0.631 | 0.89 | 30.85 | 5.74 |
| SRCNN | 28.19 | 0.829 | 2.10 | 37.47 | 9.91 | 24.18 | 0.641 | 0.91 | 30.89 | 5.84 |
| LSF | 25.64 | 0.723 | 1.28 | 33.56 | 7.42 | 23.21 | 0.614 | 0.76 | 30.35 | 4.90 |
| MZQ | 29.22 | 0.857 | 2.22 | 38.67 | 11.21 | 25.81 | 0.752 | 1.34 | 33.17 | 7.67 |
| YLY | 26.80 | 0.791 | 1.79 | 35.67 | 8.55 | 22.57 | 0.602 | 0.83 | 29.45 | 4.21 |
| BCCNN | 28.67 | 0.842 | 2.13 | 37.98 | 10.63 | 25.70 | 0.749 | 1.34 | 32.90 | 7.60 |
| GLN | 30.34 | 0.884 | 2.66 | 40.94 | 12.37 | 26.75 | 0.787 | 1.56 | 34.37 | 8.60 | | 0 |
| nv045docs | #ret | Av.P | Av.R | Av.F | #novel |
| --- | --- | --- | --- | --- | --- |
| s0.4 | 986 | 0.688 | 0.977 | 0.790 | 627 | | | o0.7 | 974 | 0.694 | 0.964 | 0.786 | 634 |
| --- | --- | --- | --- | --- | --- |
| nv0425docs | #ret | Av.P | Av.R | Av.F | #novel |
| s0.4 | 7008 | 0.463 | 0.957 | 0.610 | 3282 |
| o0.7 | 6965 | 0.462 | 0.950 | 0.608 | 3255 |
| nv03 | #ret | Av.P | Av.R | Av.F | #novel |
| s0.4 | 13495 | 0.719 | 0.978 | 0.817 | 9962 |
| o0.7 | 13303 | 0.719 | 0.972 | 0.815 | 9836 |
| nvyiz | #ret | Av.P | Av.R | Av.F | #novel |
| s0.4 | 9082 | 0.919 | 0.977 | 0.946 | 8313 |
| o0.8 | 9349 | 0.909 | 0.988 | 0.945 | 8452 | | 1 |
| nv045docs | #ret | Av.P | Av.R | Av.F | #novel |
| --- | --- | --- | --- | --- | --- |
| s0.4 | 986 | 0.688 | 0.977 | 0.790 | 627 | | | nv04 | #ret | Av.P | Av.R | Av.F | Difference |
| --- | --- | --- | --- | --- | --- |
| p0.7 | 5713 | 0.495 | 0.864 | 0.615 | 192novelin<br>492extra |
| sp0.7s2.0 | 6205 | 0.487 | 0.911 | 0.620 | |
| sp0.7s2.0 | 6205 | 0.487 | 0.911 | 0.620 | 80novelin<br>347extra |
| sp0.7s3.0 | 6552 | 0.475 | 0.929 | 0.615 | |
| sp0.7s3.0 | 6552 | 0.475 | 0.929 | 0.615 | 56novelin<br>266extra |
| sp0.7s4.0 | 6818 | 0.466 | 0.942 | 0.609 | |
| sp0.7s4.0 | 6818 | 0.466 | 0.942 | 0.609 | 15novelin<br>75extra |
| sp0.7s5.0 | 6893 | 0.464 | 0.945 | 0.608 | |
| sp0.7s5.0 | 6893 | 0.464 | 0.945 | 0.608 | 22novelin<br>72extra |
| o0.7 | 6965 | 0.462 | 0.950 | 0.608 | |
| nv03 | #ret | Av.P | Av.R | Av.F | Difference |
| p0.7 | 9127 | 0.755 | 0.762 | 0.744 | 2763novel<br>4123extra |
| sp0.7s5.0 | 13250 | 0.720 | 0.969 | 0.815 | |
| sp0.7s5.0 | 13250 | 0.720 | 0.969 | 0.815 | 25novel<br>53extra |
| o0.7 | 13303 | 0.719 | 0.972 | 0.815 | |
| nvyiz | #ret | Av.P | Av.R | Av.F | Difference |
| sp0.8s5.0 | 9199 | 0.914 | 0.978 | 0.943 | 70novel<br>97extra |
| sp0.8s6.0 | 9296 | 0.911 | 0.985 | 0.946 | |
| sp0.8s6.0 | 9296 | 0.911 | 0.985 | 0.946 | 19novel<br>53extra |
| o0.8 | 9349 | 0.909 | 0.988 | 0.945 | | | 0 |
| nv045docs | #ret | Av.P | Av.R | Av.F | #novel |
| --- | --- | --- | --- | --- | --- |
| s0.4 | 986 | 0.688 | 0.977 | 0.790 | 627 |
| o0.7 | 974 | 0.694 | 0.964 | 0.786 | 634 | | | nv0425docs | #ret | Av.P | Av.R | Av.F | #novel |
| --- | --- | --- | --- | --- | --- |
| s0.4 | 7008 | 0.463 | 0.957 | 0.610 | 3282 |
| o0.7 | 6965 | 0.462 | 0.950 | 0.608 | 3255 |
| nv03 | #ret | Av.P | Av.R | Av.F | #novel |
| s0.4 | 13495 | 0.719 | 0.978 | 0.817 | 9962 |
| o0.7 | 13303 | 0.719 | 0.972 | 0.815 | 9836 |
| nvyiz | #ret | Av.P | Av.R | Av.F | #novel |
| s0.4 | 9082 | 0.919 | 0.977 | 0.946 | 8313 |
| o0.8 | 9349 | 0.909 | 0.988 | 0.945 | 8452 | | 1 |
| nv045docs | #ret | Av.P | Av.R | Av.F | #novel |
| --- | --- | --- | --- | --- | --- |
| s0.4 | 986 | 0.688 | 0.977 | 0.790 | 627 |
| o0.7 | 974 | 0.694 | 0.964 | 0.786 | 634 | | | o0.7 | 13303 | 0.719 | 0.972 | 0.815 | |
| --- | --- | --- | --- | --- | --- |
| nvyiz | #ret | Av.P | Av.R | Av.F | Difference |
| sp0.8s5.0 | 9199 | 0.914 | 0.978 | 0.943 | 70novel<br>97extra |
| sp0.8s6.0 | 9296 | 0.911 | 0.985 | 0.946 | |
| sp0.8s6.0 | 9296 | 0.911 | 0.985 | 0.946 | 19novel<br>53extra |
| o0.8 | 9349 | 0.909 | 0.988 | 0.945 | | | 0 |
| | | Precision | Recall | F1 |
| --- | --- | --- | --- | --- |
| Partial | GS+noEP | 79.40 | 79.96 | 79.68 |
| GS+EP | 65.93 | 79.96 | 72.27 | |
| Auto+EP | 64.40 | 51.68 | 57.34 | |
| Exact | GS+noEP | 65.72 | 66.19 | 65.95 | | | GS+EP | 54.57 | 66.19 | 59.82 |
| --- | --- | --- | --- |
| Auto+EP | 47.83 | 38.39 | 42.59 | | 1 |
| | | Precision | Recall | F1 |
| --- | --- | --- | --- | --- |
| Partial | GS+noEP | 79.40 | 79.96 | 79.68 |
| GS+EP | 65.93 | 79.96 | 72.27 | |
| Auto+EP | 64.40 | 51.68 | 57.34 | |
| Exact | GS+noEP | 65.72 | 66.19 | 65.95 | | | | avg/total | Positive | Neutral | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Featurecombination | Prec | Recall | F1 | Prec | Recall | F1 | Prec | Recall | F1 | Prec |
| +f1,f2 | 0.57 | 0.45 | 0.47 | 0.32 | 0.43 | 0.37 | 0.25 | 0.57 | 0.35 | 0.72 |
| +f1,f2,f4 | 0.57 | 0.45 | 0.47 | 0.33 | 0.44 | 0.38 | 0.25 | 0.56 | 0.34 | 0.72 |
| +f1,f2,f4,f6,f7 | 0.59 | 0.46 | 0.49 | 0.30 | 0.43 | 0.35 | 0.26 | 0.54 | 0.35 | 0.76 |
| +f1,f2,f4,f5,f6,f7 | 0.60 | 0.51 | 0.53 | 0.33 | 0.45 | 0.38 | 0.28 | 0.50 | 0.36 | 0.75 |
| +f1,f2,f3,f4,f5,f6,f7,f9 | 0.63 | 0.57 | 0.59 | 0.31 | 0.56 | 0.40 | 0.36 | 0.30 | 0.32 | 0.79 |
| +f1,f2,f3,f4,f5,f6,f7,f8,f9 | 0.69 | 0.71 | 0.69 | 0.51 | 0.33 | 0.40 | 0.66 | 0.35 | 0.45 | 0.75 | | 0 |
| | | Precision | Recall | F1 |
| --- | --- | --- | --- | --- |
| Partial | GS+noEP | 79.40 | 79.96 | 79.68 |
| GS+EP | 65.93 | 79.96 | 72.27 | |
| Auto+EP | 64.40 | 51.68 | 57.34 | |
| Exact | GS+noEP | 65.72 | 66.19 | 65.95 | | | GS+EP | 54.57 | 66.19 | 59.82 |
| --- | --- | --- | --- |
| Auto+EP | 47.83 | 38.39 | 42.59 | | 1 |
| | | Precision | Recall | F1 |
| --- | --- | --- | --- | --- |
| Partial | GS+noEP | 79.40 | 79.96 | 79.68 |
| GS+EP | 65.93 | 79.96 | 72.27 | |
| Auto+EP | 64.40 | 51.68 | 57.34 | |
| Exact | GS+noEP | 65.72 | 66.19 | 65.95 | | | +f1,f2 | 0.57 | 0.45 | 0.47 | 0.32 | 0.43 | 0.37 | 0.25 | 0.57 | 0.35 | 0.72 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| +f1,f2,f4 | 0.57 | 0.45 | 0.47 | 0.33 | 0.44 | 0.38 | 0.25 | 0.56 | 0.34 | 0.72 |
| +f1,f2,f4,f6,f7 | 0.59 | 0.46 | 0.49 | 0.30 | 0.43 | 0.35 | 0.26 | 0.54 | 0.35 | 0.76 |
| +f1,f2,f4,f5,f6,f7 | 0.60 | 0.51 | 0.53 | 0.33 | 0.45 | 0.38 | 0.28 | 0.50 | 0.36 | 0.75 |
| +f1,f2,f3,f4,f5,f6,f7,f9 | 0.63 | 0.57 | 0.59 | 0.31 | 0.56 | 0.40 | 0.36 | 0.30 | 0.32 | 0.79 |
| +f1,f2,f3,f4,f5,f6,f7,f8,f9 | 0.69 | 0.71 | 0.69 | 0.51 | 0.33 | 0.40 | 0.66 | 0.35 | 0.45 | 0.75 | | 0 |
| testview |
| --- |
| 1crop<br>1full |
| 1crop<br>1full | | | 1crop<br>1full |
| --- |
| 1crop<br>1full | | 1 |
| testview |
| --- |
| 1crop<br>1full |
| 1crop<br>1full | | | Window-Size |
| --- |
| 2000<br>10000 |
| 2000<br>10000 |
| 2000<br>10000 |
| 2000<br>10000 |
| 2000<br>10000<br>2000<br>10000<br>2000<br>10000<br>2000<br>10000<br>2000<br>10000<br>2000<br>10000<br>2000<br>10000<br>2000<br>10000<br>2000<br>10000<br>2000<br>10000<br>2000<br>10000<br>2000<br>10000 | | 0 |
| testview |
| --- |
| 1crop<br>1full |
| 1crop<br>1full | | | 1crop<br>1full |
| --- |
| 1crop<br>1full | | 1 |
| testview |
| --- |
| 1crop<br>1full |
| 1crop<br>1full | | | 2000<br>10000 |
| --- |
| 2000<br>10000<br>2000<br>10000<br>2000<br>10000<br>2000<br>10000<br>2000<br>10000<br>2000<br>10000<br>2000<br>10000<br>2000<br>10000<br>2000<br>10000<br>2000<br>10000<br>2000<br>10000<br>2000<br>10000 | | 0 |
| #ofRules | Accuracy | Avg.#oftagsperword |
| --- | --- | --- |
| 0 | 96.5 | 1.00 |
| 50 | 96.9 | 1.02 | | | 100 | 97.4 | 1.04 |
| --- | --- | --- |
| 150 | 97.9 | 1.10 |
| 200 | 98.4 | 1.19 |
| 250 | 99.1 | 1.50 | | 1 |
| #ofRules | Accuracy | Avg.#oftagsperword |
| --- | --- | --- |
| 0 | 96.5 | 1.00 |
| 50 | 96.9 | 1.02 | | | | avg.precision | ratiotoJ-J |
| --- | --- | --- |
| J-J | 0.204 | — |
| CWT | 0.193 | 0.946 |
| translit | 0.193 | 0.946 |
| control | 0.115 | 0.564 | | 0 |
| #ofRules | Accuracy | Avg.#oftagsperword |
| --- | --- | --- |
| 0 | 96.5 | 1.00 |
| 50 | 96.9 | 1.02 | | | 100 | 97.4 | 1.04 |
| --- | --- | --- |
| 150 | 97.9 | 1.10 |
| 200 | 98.4 | 1.19 |
| 250 | 99.1 | 1.50 | | 1 |
| #ofRules | Accuracy | Avg.#oftagsperword |
| --- | --- | --- |
| 0 | 96.5 | 1.00 |
| 50 | 96.9 | 1.02 | | | CWT | 0.193 | 0.946 |
| --- | --- | --- |
| translit | 0.193 | 0.946 |
| control | 0.115 | 0.564 | | 0 |
| | CNN | DailyMail | | |
| --- | --- | --- | --- | --- |
| | Train | Test | Train | Test |
| DeepLSTM | 55 | 57 | 63.3 | 62.2 | | | AttentiveReader | 61.6 | 63 | 70.5 | 69 |
| --- | --- | --- | --- | --- |
| ImpatientReader | 61.8 | 63.8 | 69 | 68 |
| L2RReader | 64.3 | 65.8 | 69.1 | 67.3 | | 1 |
| | CNN | DailyMail | | |
| --- | --- | --- | --- | --- |
| | Train | Test | Train | Test |
| DeepLSTM | 55 | 57 | 63.3 | 62.2 | | | | CNN | DailyMail | | |
| --- | --- | --- | --- | --- |
| | Train | Test | Train | Test |
| Frequency | 33.2 | 35.0 | 33.4 | 32.4 |
| WA | 47.3 | 50.6 | 54.3 | 53.4 |
| nBOW | 40.3 | 43.5 | 48.7 | 47.8 |
| WMD | 41.2 | 44.0 | 49.3 | 48.5 |
| FS | 18.9 | 22.0 | 25.2 | 24.3 | | 0 |
| | CNN | DailyMail | | |
| --- | --- | --- | --- | --- |
| | Train | Test | Train | Test |
| DeepLSTM | 55 | 57 | 63.3 | 62.2 | | | AttentiveReader | 61.6 | 63 | 70.5 | 69 |
| --- | --- | --- | --- | --- |
| ImpatientReader | 61.8 | 63.8 | 69 | 68 |
| L2RReader | 64.3 | 65.8 | 69.1 | 67.3 | | 1 |
| | CNN | DailyMail | | |
| --- | --- | --- | --- | --- |
| | Train | Test | Train | Test |
| DeepLSTM | 55 | 57 | 63.3 | 62.2 | | | Frequency | 33.2 | 35.0 | 33.4 | 32.4 |
| --- | --- | --- | --- | --- |
| WA | 47.3 | 50.6 | 54.3 | 53.4 |
| nBOW | 40.3 | 43.5 | 48.7 | 47.8 |
| WMD | 41.2 | 44.0 | 49.3 | 48.5 |
| FS | 18.9 | 22.0 | 25.2 | 24.3 | | 0 |
| Name | Abbreviation | #ofinstances |
| --- | --- | --- |
| wcsp/spot5/dir | wcsp-dir | 21 |
| wcsp/spot5/log | wcsp-log | 21 |
| haplotyping-pedigrees | HT | 100 |
| upgradeability-problem | UP | 100 |
| preferenceplanning | PP | 29 | | | packup-wpms | PWPMS | 99 |
| --- | --- | --- |
| timetabling | TT | 26 | | 1 |
| Name | Abbreviation | #ofinstances |
| --- | --- | --- |
| wcsp/spot5/dir | wcsp-dir | 21 |
| wcsp/spot5/log | wcsp-log | 21 |
| haplotyping-pedigrees | HT | 100 |
| upgradeability-problem | UP | 100 |
| preferenceplanning | PP | 29 | | | Solver | wcsp-dir | wcsp-log | HT | UP | PP | PWPMS | TT |
| --- | --- | --- | --- | --- | --- | --- | --- |
| WMiFuMax | 6 | 6 | 85 | 100 | 11 | 46 | 0 |
| QWMaxSAT | 14 | 13 | 20 | 0 | 29 | 17 | 8 |
| Sat4j | 3 | 3 | 15 | 37 | 28 | 2 | 8 |
| MSUnCore | 14 | 14 | 89 | 100 | 25 | 0 | 0 |
| MaxSatz2013f | 4 | 4 | 0 | 0 | 5 | 25 | 0 |
| WMaxSatz-2009 | 4 | 3 | 0 | 41 | 5 | 12 | 0 |
| WMaxSatz+ | 4 | 3 | 0 | 41 | 5 | 12 | 0 |
| ISAC+ | 17 | 7 | 15 | 100 | 9 | 99 | 9 | | 0 |
| Name | Abbreviation | #ofinstances |
| --- | --- | --- |
| wcsp/spot5/dir | wcsp-dir | 21 |
| wcsp/spot5/log | wcsp-log | 21 |
| haplotyping-pedigrees | HT | 100 | | | upgradeability-problem | UP | 100 |
| --- | --- | --- |
| preferenceplanning | PP | 29 |
| packup-wpms | PWPMS | 99 |
| timetabling | TT | 26 | | 1 |
| Name | Abbreviation | #ofinstances |
| --- | --- | --- |
| wcsp/spot5/dir | wcsp-dir | 21 |
| wcsp/spot5/log | wcsp-log | 21 |
| haplotyping-pedigrees | HT | 100 | | | WMaxSatz-2009 | 4 | 3 | 0 | 41 | 5 | 12 | 0 |
| --- | --- | --- | --- | --- | --- | --- | --- |
| WMaxSatz+ | 4 | 3 | 0 | 41 | 5 | 12 | 0 |
| ISAC+ | 17 | 7 | 15 | 100 | 9 | 99 | 9 | | 0 |
| Downsampling | 32×32 | 64×64 | | |
| --- | --- | --- | --- | --- |
| nθ | 8 | 16 | 8 | 16 |
| RBC | 0.006 | 0.006 | 0.006 | 0.007 |
| ARBC1/2 | 0.243 | 0.869 | 0.762 | 5.408 | | | ARBC1/4 | 0.139 | 0.455 | 0.431 | 1.843 |
| --- | --- | --- | --- | --- |
| ARBC3 | 0.364 | 1.163 | 1.102 | 6.791 | | 1 |
| Downsampling | 32×32 | 64×64 | | |
| --- | --- | --- | --- | --- |
| nθ | 8 | 16 | 8 | 16 |
| RBC | 0.006 | 0.006 | 0.006 | 0.007 |
| ARBC1/2 | 0.243 | 0.869 | 0.762 | 5.408 | | | N | fnorm1 | f | ftwo | fone |
| --- | --- | --- | --- | --- |
| 3 | 0.8275 | 0.8199 | 0.5808 | 0.4444 |
| 4 | 0.8235 | 0.8139 | 0.5541 | 0.4219 |
| 5 | 0.8214 | 0.8104 | 0.5391 | 0.4096 |
| 10 | 0.8175 | 0.8038 | 0.5116 | 0.3874 |
| 15 | 0.8163 | 0.8017 | 0.5030 | 0.3806 |
| 20 | 0.8157 | 0.8007 | 0.4988 | 0.3774 | | 0 |
| Downsampling | 32×32 | 64×64 | | |
| --- | --- | --- | --- | --- |
| nθ | 8 | 16 | 8 | 16 |
| RBC | 0.006 | 0.006 | 0.006 | 0.007 |
| ARBC1/2 | 0.243 | 0.869 | 0.762 | 5.408 | | | ARBC1/4 | 0.139 | 0.455 | 0.431 | 1.843 |
| --- | --- | --- | --- | --- |
| ARBC3 | 0.364 | 1.163 | 1.102 | 6.791 | | 1 |
| Downsampling | 32×32 | 64×64 | | |
| --- | --- | --- | --- | --- |
| nθ | 8 | 16 | 8 | 16 |
| RBC | 0.006 | 0.006 | 0.006 | 0.007 |
| ARBC1/2 | 0.243 | 0.869 | 0.762 | 5.408 | | | 5 | 0.8214 | 0.8104 | 0.5391 | 0.4096 |
| --- | --- | --- | --- | --- |
| 10 | 0.8175 | 0.8038 | 0.5116 | 0.3874 |
| 15 | 0.8163 | 0.8017 | 0.5030 | 0.3806 |
| 20 | 0.8157 | 0.8007 | 0.4988 | 0.3774 | | 0 |
| Algorithm\SNRRange | 0.6-1.0 | 1.2-2.0 | 2.2-2.6 |
| --- | --- | --- | --- |
| OurO(N)detector | 0.47 | 0.75 | 0.88 |
| OurO(NlogN)detector | 0.46 | 0.72 | 0.87 |
| Canny | 0.24 | 0.67 | 0.85 |
| BM3D+Canny | 0.12 | 0.67 | 0.84 | | | Crisp | 0.3 | 0.32 | 0.46 |
| --- | --- | --- | --- |
| Dollar | 0.18 | 0.32 | 0.43 |
| MCG | 0.25 | 0.28 | 0.41 | | 1 |
| Algorithm\SNRRange | 0.6-1.0 | 1.2-2.0 | 2.2-2.6 |
| --- | --- | --- | --- |
| OurO(N)detector | 0.47 | 0.75 | 0.88 |
| OurO(NlogN)detector | 0.46 | 0.72 | 0.87 |
| Canny | 0.24 | 0.67 | 0.85 |
| BM3D+Canny | 0.12 | 0.67 | 0.84 | | | Model/Algorithm | MNIST | Caltech101 | US-CT | | | |
| --- | --- | --- | --- | --- | --- | --- |
| | DC | mIoU | DC | mIoU | DC | mIoU |
| DetectionAccuracy | 0.87 | 0.78 | 0.95 | 0.91 | 0.97 | .0.94 |
| MatchingAccuracy | 0.82 | 0.71 | 0.96 | 0.93 | 0.97 | 0.95 |
| DSPaccw/oseg | 0.58 | 0.44 | 0.60 | 0.48 | 0.29 | 0.17 |
| DSPaccwithseg | - | - | - | - | 0.63 | 0.49 | | 0 |
| Algorithm\SNRRange | 0.6-1.0 | 1.2-2.0 | 2.2-2.6 |
| --- | --- | --- | --- |
| OurO(N)detector | 0.47 | 0.75 | 0.88 | | | OurO(NlogN)detector | 0.46 | 0.72 | 0.87 |
| --- | --- | --- | --- |
| Canny | 0.24 | 0.67 | 0.85 |
| BM3D+Canny | 0.12 | 0.67 | 0.84 |
| Crisp | 0.3 | 0.32 | 0.46 |
| Dollar | 0.18 | 0.32 | 0.43 |
| MCG | 0.25 | 0.28 | 0.41 | | 1 |
| Algorithm\SNRRange | 0.6-1.0 | 1.2-2.0 | 2.2-2.6 |
| --- | --- | --- | --- |
| OurO(N)detector | 0.47 | 0.75 | 0.88 | | | DSPaccw/oseg | 0.58 | 0.44 | 0.60 | 0.48 | 0.29 | 0.17 |
| --- | --- | --- | --- | --- | --- | --- |
| DSPaccwithseg | - | - | - | - | 0.63 | 0.49 | | 0 |
| MethodNameEntitytypeSample |
| --- |
| NameofCityCITYParisCITY |
| NameofContinentcontinentAsiacontinent |
| NameofCountryCOUNTRYUSACOUNTRY |
| NameofDrugDRUGAcarboseDRUG |
| NameofCompanyCOMPANYAsusCOMPANY |
| NameofCrimeCrimeLarcenyCrime |
| NameofSportSportArcherySport |
| NameofHolidayholidayChristmasholiday |
| NameofProductproductBagProduct |
| NameofNaturaldisasterdisasterFlooddisaster |
| NameofOperatingSystemosUbuntuos |
| NameofSportEventsportevAsianCupsportev | | | NameofGeographicFeaturegeoCliffgeo |
| --- |
| RegionRegionRegionSuncoastregion |
| NameofStatestateNewSouthWalesState |
| NameofadegreedegreeSeniorLecturerdegree | | 1 |
| MethodNameEntitytypeSample |
| --- |
| NameofCityCITYParisCITY |
| NameofContinentcontinentAsiacontinent |
| NameofCountryCOUNTRYUSACOUNTRY |
| NameofDrugDRUGAcarboseDRUG |
| NameofCompanyCOMPANYAsusCOMPANY |
| NameofCrimeCrimeLarcenyCrime |
| NameofSportSportArcherySport |
| NameofHolidayholidayChristmasholiday |
| NameofProductproductBagProduct |
| NameofNaturaldisasterdisasterFlooddisaster |
| NameofOperatingSystemosUbuntuos |
| NameofSportEventsportevAsianCupsportev | | | # | Features | Description |
| --- | --- | --- |
| 1 | TF | Termfrequencyofwintheshorttext |
| 2 | IDF | Inversedocumentfrequencyofwinthewholecollection |
| 3 | SF | Numberofsentencesintheshorttextthatcontainw |
| 4 | First | Whetherwexistsinthefirstsentence |
| 5 | Last | Whetherwexistsinthelastsentence |
| 6 | NE | Whetherwisanamedentity(NE) |
| 7 | NEFirst | WhetherwisNEinthefirstsentence |
| 8 | NELast | WhetherwisNEinthelastsentence |
| 9 | POS | Partofspeechofw | | 0 |
| MethodNameEntitytypeSample |
| --- |
| NameofCityCITYParisCITY |
| NameofContinentcontinentAsiacontinent |
| NameofCountryCOUNTRYUSACOUNTRY |
| NameofDrugDRUGAcarboseDRUG |
| NameofCompanyCOMPANYAsusCOMPANY |
| NameofCrimeCrimeLarcenyCrime |
| NameofSportSportArcherySport |
| NameofHolidayholidayChristmasholiday |
| NameofProductproductBagProduct |
| NameofNaturaldisasterdisasterFlooddisaster | | | NameofOperatingSystemosUbuntuos |
| --- |
| NameofSportEventsportevAsianCupsportev |
| NameofGeographicFeaturegeoCliffgeo |
| RegionRegionRegionSuncoastregion |
| NameofStatestateNewSouthWalesState |
| NameofadegreedegreeSeniorLecturerdegree | | 1 |
| MethodNameEntitytypeSample |
| --- |
| NameofCityCITYParisCITY |
| NameofContinentcontinentAsiacontinent |
| NameofCountryCOUNTRYUSACOUNTRY |
| NameofDrugDRUGAcarboseDRUG |
| NameofCompanyCOMPANYAsusCOMPANY |
| NameofCrimeCrimeLarcenyCrime |
| NameofSportSportArcherySport |
| NameofHolidayholidayChristmasholiday |
| NameofProductproductBagProduct |
| NameofNaturaldisasterdisasterFlooddisaster | | | 2 | IDF | Inversedocumentfrequencyofwinthewholecollection |
| --- | --- | --- |
| 3 | SF | Numberofsentencesintheshorttextthatcontainw |
| 4 | First | Whetherwexistsinthefirstsentence |
| 5 | Last | Whetherwexistsinthelastsentence |
| 6 | NE | Whetherwisanamedentity(NE) |
| 7 | NEFirst | WhetherwisNEinthefirstsentence |
| 8 | NELast | WhetherwisNEinthelastsentence |
| 9 | POS | Partofspeechofw | | 0 |
| Model | Still-image | +MGP | +MGP<br>+MCS | +MGP+MCS<br>+Rescoring | Model<br>Combination | TestSet |
| --- | --- | --- | --- | --- | --- | --- |
| CRAFT | 67.7 | 68.7 | 72.4 | 73.6 | 73.8 | 67.8 |
| DeepID-net | 65.8 | 68.3 | 72.1 | 72.5 | | | | | CRAFT | 69.5 | 70.3 | 74.1 | 75.0 | 77.0 | 69.7 |
| --- | --- | --- | --- | --- | --- | --- |
| DeepID-net | 70.7 | 72.7 | 74.9 | 75.4 | | | | 1 |
| Model | Still-image | +MGP | +MGP<br>+MCS | +MGP+MCS<br>+Rescoring | Model<br>Combination | TestSet |
| --- | --- | --- | --- | --- | --- | --- |
| CRAFT | 67.7 | 68.7 | 72.4 | 73.6 | 73.8 | 67.8 |
| DeepID-net | 65.8 | 68.3 | 72.1 | 72.5 | | | | | Code<br>size | Model | With<br>bigrams | 20Newsgroups | RCV1 | EnglishWikipedia | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| MAP | NDCG@10 | MAP | NDCG@10 | MAP | NDCG@10 | | | |
| 128 | PV-DBOW | no | 0.4 | 0.75 | 0.25 | 0.79 | 0.25 | 0.59 |
| yes | 0.45 | 0.75 | 0.27 | 0.8 | 0.26 | 0.6 | | |
| Binary<br>PV-DBOW | no | 0.34 | 0.69 | 0.22 | 0.74 | 0.18 | 0.48 | |
| yes | 0.35 | 0.69 | 0.24 | 0.77 | 0.18 | 0.49 | | |
| PV-DM | N/A | 0.41 | 0.73 | 0.23 | 0.78 | 0.24 | 0.59 | |
| BinaryPV-DM | 0.34 | 0.65 | 0.18 | 0.69 | 0.16 | 0.46 | | |
| 32 | PV-DBOW | no | 0.43 | 0.71 | 0.26 | 0.75 | 0.23 | 0.55 |
| yes | 0.46 | 0.72 | 0.27 | 0.77 | 0.25 | 0.58 | | |
| Binary<br>PV-DBOW | no | 0.32 | 0.53 | 0.22 | 0.6 | 0.16 | 0.41 | |
| yes | 0.32 | 0.54 | 0.25 | 0.66 | 0.17 | 0.44 | | |
| PV-DM | N/A | 0.43 | 0.7 | 0.23 | 0.77 | 0.23 | 0.55 | |
| BinaryPV-DM | 0.29 | 0.49 | 0.17 | 0.53 | 0.15 | 0.41 | | | | 0 |
| Model | Still-image | +MGP | +MGP<br>+MCS | +MGP+MCS<br>+Rescoring | Model<br>Combination | TestSet |
| --- | --- | --- | --- | --- | --- | --- |
| CRAFT | 67.7 | 68.7 | 72.4 | 73.6 | 73.8 | 67.8 | | | DeepID-net | 65.8 | 68.3 | 72.1 | 72.5 | | |
| --- | --- | --- | --- | --- | --- | --- |
| CRAFT | 69.5 | 70.3 | 74.1 | 75.0 | 77.0 | 69.7 |
| DeepID-net | 70.7 | 72.7 | 74.9 | 75.4 | | | | 1 |
| Model | Still-image | +MGP | +MGP<br>+MCS | +MGP+MCS<br>+Rescoring | Model<br>Combination | TestSet |
| --- | --- | --- | --- | --- | --- | --- |
| CRAFT | 67.7 | 68.7 | 72.4 | 73.6 | 73.8 | 67.8 | | | yes | 0.45 | 0.75 | 0.27 | 0.8 | 0.26 | 0.6 | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Binary<br>PV-DBOW | no | 0.34 | 0.69 | 0.22 | 0.74 | 0.18 | 0.48 | |
| yes | 0.35 | 0.69 | 0.24 | 0.77 | 0.18 | 0.49 | | |
| PV-DM | N/A | 0.41 | 0.73 | 0.23 | 0.78 | 0.24 | 0.59 | |
| BinaryPV-DM | 0.34 | 0.65 | 0.18 | 0.69 | 0.16 | 0.46 | | |
| 32 | PV-DBOW | no | 0.43 | 0.71 | 0.26 | 0.75 | 0.23 | 0.55 |
| yes | 0.46 | 0.72 | 0.27 | 0.77 | 0.25 | 0.58 | | |
| Binary<br>PV-DBOW | no | 0.32 | 0.53 | 0.22 | 0.6 | 0.16 | 0.41 | |
| yes | 0.32 | 0.54 | 0.25 | 0.66 | 0.17 | 0.44 | | |
| PV-DM | N/A | 0.43 | 0.7 | 0.23 | 0.77 | 0.23 | 0.55 | |
| BinaryPV-DM | 0.29 | 0.49 | 0.17 | 0.53 | 0.15 | 0.41 | | | | 0 |
| Crimes(MUC): | murder(s),crime(s),killing(s),trafficking,kidnapping(s) |
| --- | --- |
| Crimes(WSJ): | murder(s),crime(s),theft(s),fraud(s),embezzlement |
| Vehicle: | plane(s),helicopter(s),car(s),bus(es),aircraft(s),airplane(s),vehicle(s) | | | Weapon: | bomb(s),weapon(s),rifle(s),missile(s),grenade(s),machinegun(s),dynamite |
| --- | --- |
| Machines: | computer(s),machine(s),equipment,chip(s),machinery | | 1 |
| Crimes(MUC): | murder(s),crime(s),killing(s),trafficking,kidnapping(s) |
| --- | --- |
| Crimes(WSJ): | murder(s),crime(s),theft(s),fraud(s),embezzlement |
| Vehicle: | plane(s),helicopter(s),car(s),bus(es),aircraft(s),airplane(s),vehicle(s) | | | free | explode |
| --- | --- |
| kill | kidnap |
| enter | arrest |
| negotiate | encircle |
| escapefrom | blocktheway |
| givedeadline | | | 0 |
| Crimes(MUC): | murder(s),crime(s),killing(s),trafficking,kidnapping(s) |
| --- | --- |
| Crimes(WSJ): | murder(s),crime(s),theft(s),fraud(s),embezzlement | | | Vehicle: | plane(s),helicopter(s),car(s),bus(es),aircraft(s),airplane(s),vehicle(s) |
| --- | --- |
| Weapon: | bomb(s),weapon(s),rifle(s),missile(s),grenade(s),machinegun(s),dynamite |
| Machines: | computer(s),machine(s),equipment,chip(s),machinery | | 1 |
| Crimes(MUC): | murder(s),crime(s),killing(s),trafficking,kidnapping(s) |
| --- | --- |
| Crimes(WSJ): | murder(s),crime(s),theft(s),fraud(s),embezzlement | | | escapefrom | blocktheway |
| --- | --- |
| givedeadline | | | 0 |
| Non-Intruder | Intruder |
| --- | --- |
| falconiformes | turonianfirstappearances |
| birdsofprey | snakes | | | seabirds | squamata |
| --- | --- |
| ypresianfirstappearances | predators |
| psittaciformes | lepidosaurs |
| parrots | predation |
| rupelianfirstappearances | carnivorousanimals |
| gulls | venomoussnakes |
| birdfamilies | snakesinart | | 1 |
| Non-Intruder | Intruder |
| --- | --- |
| falconiformes | turonianfirstappearances |
| birdsofprey | snakes | | | | O-NL-SDA | BP | Proposed |
| --- | --- | --- | --- |
| Damselfly | 30.85 | 26.49 | 31.56 |
| Birds | 26.62 | 22.75 | 27.17 |
| Rabbit | 27.24 | 22.63 | 27.89 |
| Turtle | 34.65 | 26.31 | 35.59 |
| Dog | 21.55 | 16.97 | 22.33 |
| EagleRay | 26.57 | 22.65 | 27.20 |
| Boat | 33.11 | 25.48 | 33.94 |
| Monkey | 30.32 | 23.51 | 30.70 |
| Panda | 21.00 | 17.85 | 21.53 |
| Snake | 17.71 | 14.67 | 18.23 |
| MeanPSNR | 26.96 | 21.93 | 27.61 | | 0 |
| Non-Intruder | Intruder |
| --- | --- |
| falconiformes | turonianfirstappearances |
| birdsofprey | snakes |
| seabirds | squamata |
| ypresianfirstappearances | predators |
| psittaciformes | lepidosaurs |
| parrots | predation |
| rupelianfirstappearances | carnivorousanimals | | | gulls | venomoussnakes |
| --- | --- |
| birdfamilies | snakesinart | | 1 |
| Non-Intruder | Intruder |
| --- | --- |
| falconiformes | turonianfirstappearances |
| birdsofprey | snakes |
| seabirds | squamata |
| ypresianfirstappearances | predators |
| psittaciformes | lepidosaurs |
| parrots | predation |
| rupelianfirstappearances | carnivorousanimals | | | EagleRay | 26.57 | 22.65 | 27.20 |
| --- | --- | --- | --- |
| Boat | 33.11 | 25.48 | 33.94 |
| Monkey | 30.32 | 23.51 | 30.70 |
| Panda | 21.00 | 17.85 | 21.53 |
| Snake | 17.71 | 14.67 | 18.23 |
| MeanPSNR | 26.96 | 21.93 | 27.61 | | 0 |
| Model | Beam | bottle | bus | couch | microwave | pizza | racket | suitcase |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| DCC<br>KGA-CGM | 1<br>1 | 4.6<br>26.4<br>17.7<br>16.3<br>29.6<br>22.2 | 29.8<br>54.2<br>68.7<br>67.8<br>74.4<br>42.5 | 45.9<br>42.1<br>25.5<br>48.2<br>38.7<br>34.4 | 28.1<br>50.9<br>24.7<br>29.7<br>27.8<br>48.1 | 64.6<br>70.8<br>69.3<br>77.2<br>68.1<br>69.6 | 52.2<br>75.3<br>55.3<br>57.1<br>70.2<br>63.1 | 13.2<br>25.6<br>39.8<br>49.9<br>44.7<br>22.6 |
| NOC<br>CBS(T4)<br>LSTM-C<br>KGA-CGM | >1<br>>1<br>>1<br>>1 | | | | | | | |
| DCC<br>KGA-CGM | 1<br>1 | 18.1<br>21.5<br>21.2<br>21.3 | 21.6<br>20.3<br>20.4<br>19.2 | 23.1<br>23.0<br>21.4<br>23.5 | 22.1<br>22.6<br>21.5<br>23.2 | 22.2<br>21.4<br>21.8<br>21.7 | 20.3<br>27.0<br>24.6<br>22.5 | 18.3<br>18.7<br>18.0<br>18.0 | | | NOC<br>KGA-CGM | >1<br>>1 | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| KGA-CGM<br>KGA-CGM | 1<br>>1 | 13.1<br>12.6 | 12.6<br>11.6 | 14.9<br>14.6 | 13.3<br>13.6 | 13.2<br>13.1 | 19.8<br>16.7 | 10.6<br>10.3 | | 1 |
| Model | Beam | bottle | bus | couch | microwave | pizza | racket | suitcase |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| DCC<br>KGA-CGM | 1<br>1 | 4.6<br>26.4<br>17.7<br>16.3<br>29.6<br>22.2 | 29.8<br>54.2<br>68.7<br>67.8<br>74.4<br>42.5 | 45.9<br>42.1<br>25.5<br>48.2<br>38.7<br>34.4 | 28.1<br>50.9<br>24.7<br>29.7<br>27.8<br>48.1 | 64.6<br>70.8<br>69.3<br>77.2<br>68.1<br>69.6 | 52.2<br>75.3<br>55.3<br>57.1<br>70.2<br>63.1 | 13.2<br>25.6<br>39.8<br>49.9<br>44.7<br>22.6 |
| NOC<br>CBS(T4)<br>LSTM-C<br>KGA-CGM | >1<br>>1<br>>1<br>>1 | | | | | | | |
| DCC<br>KGA-CGM | 1<br>1 | 18.1<br>21.5<br>21.2<br>21.3 | 21.6<br>20.3<br>20.4<br>19.2 | 23.1<br>23.0<br>21.4<br>23.5 | 22.1<br>22.6<br>21.5<br>23.2 | 22.2<br>21.4<br>21.8<br>21.7 | 20.3<br>27.0<br>24.6<br>22.5 | 18.3<br>18.7<br>18.0<br>18.0 | | | | wall | floor | cabin | bed | chair | sofa | table | door | wdw | bslf | pic | cnter |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| SF5<br>DFCN<br>DFCN-DCRF | 74.94<br>74.72<br>74.29 | 87.41<br>87.41<br>86.78 | 41.70<br>41.52<br>43.44 | 66.53<br>62.49<br>64.25 | 64.45<br>64.58<br>64.80 | 50.36<br>48.78<br>51.6 | 49.01<br>44.94<br>45.73 | 33.35<br>31.54<br>31.67 | 44.77<br>46.18<br>47.64 | 28.12<br>31.08<br>32.55 | 46.84<br>47.71<br>46.43 | 27.73<br>31.09<br>32.00 |
| | desk | shelf | ctn | drssr | pillow | mirror | mat | clthes | ceiling | books | fridge | tv |
| SF5<br>DFCN<br>DFCN-DCRF | 18.31<br>20.47<br>21.28 | 9.20<br>7.16<br>7.23 | 52.68<br>53.58<br>55.5 | 34.61<br>35.65<br>39.49 | 37.77<br>35.50<br>34.41 | 38.87<br>28.57<br>28.55 | 0<br>0<br>0 | 16.67<br>26.18<br>28.64 | 67.34<br>64.46<br>63.11 | 27.29<br>33.32<br>33.12 | 31.31<br>37.82<br>42.33 | 31.64<br>36.34<br>42.96 |
| | towel | shwr | box | board | person | stand | toilet | sink | lamp | btub | bag | mean |
| SF5<br>DFCN<br>DFCN-DCRF | 16.55<br>28.43<br>29.77 | 6.06<br>0.21<br>0 | 15.77<br>23.62<br>25.69 | 49.23<br>45.03<br>45.21 | 14.59<br>29.64<br>35.14 | 19.55<br>16.27<br>18.52 | 67.06<br>65.94<br>67.72 | 54.99<br>48.84<br>49.91 | 35.07<br>33.74<br>33.24 | 63.06<br>56.08<br>60.64 | 9.52<br>15.41<br>16.52 | 37.29<br>38.0<br>39.3 | | 0 |
| Model | Beam | bottle | bus | couch | microwave | pizza | racket | suitcase |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| DCC<br>KGA-CGM | 1<br>1 | 4.6<br>26.4<br>17.7<br>16.3<br>29.6<br>22.2 | 29.8<br>54.2<br>68.7<br>67.8<br>74.4<br>42.5 | 45.9<br>42.1<br>25.5<br>48.2<br>38.7<br>34.4 | 28.1<br>50.9<br>24.7<br>29.7<br>27.8<br>48.1 | 64.6<br>70.8<br>69.3<br>77.2<br>68.1<br>69.6 | 52.2<br>75.3<br>55.3<br>57.1<br>70.2<br>63.1 | 13.2<br>25.6<br>39.8<br>49.9<br>44.7<br>22.6 | | | NOC<br>CBS(T4)<br>LSTM-C<br>KGA-CGM | >1<br>>1<br>>1<br>>1 | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| DCC<br>KGA-CGM | 1<br>1 | 18.1<br>21.5<br>21.2<br>21.3 | 21.6<br>20.3<br>20.4<br>19.2 | 23.1<br>23.0<br>21.4<br>23.5 | 22.1<br>22.6<br>21.5<br>23.2 | 22.2<br>21.4<br>21.8<br>21.7 | 20.3<br>27.0<br>24.6<br>22.5 | 18.3<br>18.7<br>18.0<br>18.0 |
| NOC<br>KGA-CGM | >1<br>>1 | | | | | | | |
| KGA-CGM<br>KGA-CGM | 1<br>>1 | 13.1<br>12.6 | 12.6<br>11.6 | 14.9<br>14.6 | 13.3<br>13.6 | 13.2<br>13.1 | 19.8<br>16.7 | 10.6<br>10.3 | | 1 |
| Model | Beam | bottle | bus | couch | microwave | pizza | racket | suitcase |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| DCC<br>KGA-CGM | 1<br>1 | 4.6<br>26.4<br>17.7<br>16.3<br>29.6<br>22.2 | 29.8<br>54.2<br>68.7<br>67.8<br>74.4<br>42.5 | 45.9<br>42.1<br>25.5<br>48.2<br>38.7<br>34.4 | 28.1<br>50.9<br>24.7<br>29.7<br>27.8<br>48.1 | 64.6<br>70.8<br>69.3<br>77.2<br>68.1<br>69.6 | 52.2<br>75.3<br>55.3<br>57.1<br>70.2<br>63.1 | 13.2<br>25.6<br>39.8<br>49.9<br>44.7<br>22.6 | | | SF5<br>DFCN<br>DFCN-DCRF | 18.31<br>20.47<br>21.28 | 9.20<br>7.16<br>7.23 | 52.68<br>53.58<br>55.5 | 34.61<br>35.65<br>39.49 | 37.77<br>35.50<br>34.41 | 38.87<br>28.57<br>28.55 | 0<br>0<br>0 | 16.67<br>26.18<br>28.64 | 67.34<br>64.46<br>63.11 | 27.29<br>33.32<br>33.12 | 31.31<br>37.82<br>42.33 | 31.64<br>36.34<br>42.96 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| | towel | shwr | box | board | person | stand | toilet | sink | lamp | btub | bag | mean |
| SF5<br>DFCN<br>DFCN-DCRF | 16.55<br>28.43<br>29.77 | 6.06<br>0.21<br>0 | 15.77<br>23.62<br>25.69 | 49.23<br>45.03<br>45.21 | 14.59<br>29.64<br>35.14 | 19.55<br>16.27<br>18.52 | 67.06<br>65.94<br>67.72 | 54.99<br>48.84<br>49.91 | 35.07<br>33.74<br>33.24 | 63.06<br>56.08<br>60.64 | 9.52<br>15.41<br>16.52 | 37.29<br>38.0<br>39.3 | | 0 |
| k-means<br>Hierarchicalclustering<br>SBM<br>WSBM<br>WSBM(known) | 0.68080.67930.5399<br>0.68640.76120.5681<br>0.39160.67520.5703<br>0.68640.76120.5681<br>0.51710.72060.6906 |
| --- | --- |
| k-means<br>Hierarchicalclustering<br>SBM<br>WSBM<br>WSBM(known) | 0.43030.65480.6860<br>0.41660.65370.6575<br>0.06940.48210.1801<br>0.42630.68270.7261<br>0.20220.57240.4363 |
| k-means<br>Hierarchicalclustering<br>SBM<br>WSBM<br>WSBM(known) | 0.41770.81720.8418<br>0.42880.84850.8483<br>0.38110.85030.8137<br>0.31910.79390.5243<br>0.12580.62290.3602 | | | k-means<br>Hierarchicalclustering<br>SBM<br>WSBM<br>WSBM(known) | 0.57530.57950.2533<br>0.57170.58070.2581<br>0.52930.49440.1180<br>0.56920.58000.2550<br>0.46860.20630.2675 |
| --- | --- |
| k-means<br>Hierarchicalclustering<br>SBM<br>WSBM<br>WSBM(known) | 0.54660.82380.7538<br>0.54660.82380.7538<br>0.40150.54680.1140<br>0.54660.82380.7538<br>0.44630.75290.6966 | | 1 |
| k-means<br>Hierarchicalclustering<br>SBM<br>WSBM<br>WSBM(known) | 0.68080.67930.5399<br>0.68640.76120.5681<br>0.39160.67520.5703<br>0.68640.76120.5681<br>0.51710.72060.6906 |
| --- | --- |
| k-means<br>Hierarchicalclustering<br>SBM<br>WSBM<br>WSBM(known) | 0.43030.65480.6860<br>0.41660.65370.6575<br>0.06940.48210.1801<br>0.42630.68270.7261<br>0.20220.57240.4363 |
| k-means<br>Hierarchicalclustering<br>SBM<br>WSBM<br>WSBM(known) | 0.41770.81720.8418<br>0.42880.84850.8483<br>0.38110.85030.8137<br>0.31910.79390.5243<br>0.12580.62290.3602 | | | k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.68080.67930.5399<br>0.68640.76120.5681<br>0.39160.67520.5703<br>0.38550.62830.5517<br>0.38890.66610.5673<br>0.68640.76120.5681<br>0.68640.76120.5681<br>0.68640.76120.5681 |
| --- | --- |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.43030.65480.6860<br>0.41660.65370.6575<br>0.06940.48210.1801<br>0.14580.1964-0.0182<br>0.55240.20570.0380<br>0.42630.68270.7261<br>0.42880.68600.7310<br>0.41150.64250.6803 |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.41770.81720.8418<br>0.42880.84850.8483<br>0.38110.85030.8137<br>0.39990.80110.8089<br>0.30650.47780.3143<br>0.31910.79390.5243<br>0.32290.74810.5077<br>0.33170.60160.4964 |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.58910.44090.2549<br>0.58880.39530.2311<br>0.11870.35460.1308<br>0.10420.36620.1619<br>0.33980.36150.2345<br>0.38640.23030.1368<br>0.44010.28110.1898<br>0.54460.36120.2259 |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.23990.47500.2385<br>0.24000.52190.2241<br>-0.08420.14020.0052<br>0.14970.62130.3114<br>0.10940.63570.2575<br>-0.01480.09230.0074<br>0.19750.25790.0639<br>0.08460.47980.2517 |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.57530.57950.2533<br>0.57170.58070.2581<br>0.52930.49440.1180<br>0.54890.51620.1486<br>0.47320.49370.1198<br>0.56920.58000.2550<br>0.56560.56540.2316<br>0.53770.62270.3322 |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.54660.82380.7538<br>0.54660.82380.7538<br>0.40150.54680.1140<br>0.37800.54580.1128<br>0.29460.53200.1132<br>0.54660.82380.7538<br>0.54660.82380.7538<br>0.54660.82380.7538 | | 0 |
| k-means<br>Hierarchicalclustering<br>SBM<br>WSBM<br>WSBM(known) | 0.68080.67930.5399<br>0.68640.76120.5681<br>0.39160.67520.5703<br>0.68640.76120.5681<br>0.51710.72060.6906 |
| --- | --- |
| k-means<br>Hierarchicalclustering<br>SBM<br>WSBM<br>WSBM(known) | 0.43030.65480.6860<br>0.41660.65370.6575<br>0.06940.48210.1801<br>0.42630.68270.7261<br>0.20220.57240.4363 |
| k-means<br>Hierarchicalclustering<br>SBM<br>WSBM<br>WSBM(known) | 0.41770.81720.8418<br>0.42880.84850.8483<br>0.38110.85030.8137<br>0.31910.79390.5243<br>0.12580.62290.3602 | | | k-means<br>Hierarchicalclustering<br>SBM<br>WSBM<br>WSBM(known) | 0.57530.57950.2533<br>0.57170.58070.2581<br>0.52930.49440.1180<br>0.56920.58000.2550<br>0.46860.20630.2675 |
| --- | --- |
| k-means<br>Hierarchicalclustering<br>SBM<br>WSBM<br>WSBM(known) | 0.54660.82380.7538<br>0.54660.82380.7538<br>0.40150.54680.1140<br>0.54660.82380.7538<br>0.44630.75290.6966 | | 1 |
| k-means<br>Hierarchicalclustering<br>SBM<br>WSBM<br>WSBM(known) | 0.68080.67930.5399<br>0.68640.76120.5681<br>0.39160.67520.5703<br>0.68640.76120.5681<br>0.51710.72060.6906 |
| --- | --- |
| k-means<br>Hierarchicalclustering<br>SBM<br>WSBM<br>WSBM(known) | 0.43030.65480.6860<br>0.41660.65370.6575<br>0.06940.48210.1801<br>0.42630.68270.7261<br>0.20220.57240.4363 |
| k-means<br>Hierarchicalclustering<br>SBM<br>WSBM<br>WSBM(known) | 0.41770.81720.8418<br>0.42880.84850.8483<br>0.38110.85030.8137<br>0.31910.79390.5243<br>0.12580.62290.3602 | | | k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.58910.44090.2549<br>0.58880.39530.2311<br>0.11870.35460.1308<br>0.10420.36620.1619<br>0.33980.36150.2345<br>0.38640.23030.1368<br>0.44010.28110.1898<br>0.54460.36120.2259 |
| --- | --- |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.23990.47500.2385<br>0.24000.52190.2241<br>-0.08420.14020.0052<br>0.14970.62130.3114<br>0.10940.63570.2575<br>-0.01480.09230.0074<br>0.19750.25790.0639<br>0.08460.47980.2517 |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.57530.57950.2533<br>0.57170.58070.2581<br>0.52930.49440.1180<br>0.54890.51620.1486<br>0.47320.49370.1198<br>0.56920.58000.2550<br>0.56560.56540.2316<br>0.53770.62270.3322 |
| k-means<br>Hierarchicalclustering<br>SBM(Manhattan)<br>SBM(Euclidean)<br>SBM(Chebyshev)<br>WSBM(Manhattan)<br>WSBM(Euclidean)<br>WSBM(Chebyshev) | 0.54660.82380.7538<br>0.54660.82380.7538<br>0.40150.54680.1140<br>0.37800.54580.1128<br>0.29460.53200.1132<br>0.54660.82380.7538<br>0.54660.82380.7538<br>0.54660.82380.7538 | | 0 |
| Methods | CIFAR-10<br>16bits32bits48bits64bits | NUS-WIDE<br>16bits32bits48bits64bits |
| --- | --- | --- |
| Ours | 0.83370.85550.86470.8690 | 0.74580.77480.78310.7898 | | | DTH | 0.81670.83840.84920.8532 | 0.73250.75330.76250.7684 |
| --- | --- | --- |
| DSH | 0.82320.82680.83700.8327 | 0.71300.71790.71500.7210 |
| FastH | 0.63570.68100.69930.7097 | 0.71190.73870.75030.7560 |
| ITQ-CCA | 0.61030.63480.64670.6577 | 0.70260.72200.72680.7297 |
| KSH | 0.40300.42450.43600.4423 | 0.69780.71360.71470.7175 |
| SSH | 0.22130.17900.16560.1587 | 0.49840.46070.44510.4356 |
| ITQ | 0.29050.31200.32380.3292 | 0.58380.58540.58640.5870 | | 1 |
| Methods | CIFAR-10<br>16bits32bits48bits64bits | NUS-WIDE<br>16bits32bits48bits64bits |
| --- | --- | --- |
| Ours | 0.83370.85550.86470.8690 | 0.74580.77480.78310.7898 | | | Method | CIFAR-10 | NUS-WIDE |
| --- | --- | --- |
| 16bits24bits32bits48bits | 16bits24bits32bits48bits | |
| Ours | 0.9150.9230.9250.926 | 0.7560.7760.7850.799 |
| DPSH | 0.7630.7810.7950.807 | 0.7150.7220.7360.741 |
| DRSCH | 0.6150.6220.6290.631 | 0.6180.6220.6230.628 |
| DSCH | 0.6090.6130.6170.62 | 0.5920.5970.6110.609 |
| DSRH | 0.6080.6110.6170.618 | 0.6090.6180.6210.631 |
| DPSH* | 0.9030.8850.9150.911 | N/A | | 0 |
| Methods | CIFAR-10<br>16bits32bits48bits64bits | NUS-WIDE<br>16bits32bits48bits64bits |
| --- | --- | --- |
| Ours | 0.83370.85550.86470.8690 | 0.74580.77480.78310.7898 |
| DTH | 0.81670.83840.84920.8532 | 0.73250.75330.76250.7684 |
| DSH | 0.82320.82680.83700.8327 | 0.71300.71790.71500.7210 |
| FastH | 0.63570.68100.69930.7097 | 0.71190.73870.75030.7560 |
| ITQ-CCA | 0.61030.63480.64670.6577 | 0.70260.72200.72680.7297 | | | KSH | 0.40300.42450.43600.4423 | 0.69780.71360.71470.7175 |
| --- | --- | --- |
| SSH | 0.22130.17900.16560.1587 | 0.49840.46070.44510.4356 |
| ITQ | 0.29050.31200.32380.3292 | 0.58380.58540.58640.5870 | | 1 |
| Methods | CIFAR-10<br>16bits32bits48bits64bits | NUS-WIDE<br>16bits32bits48bits64bits |
| --- | --- | --- |
| Ours | 0.83370.85550.86470.8690 | 0.74580.77480.78310.7898 |
| DTH | 0.81670.83840.84920.8532 | 0.73250.75330.76250.7684 |
| DSH | 0.82320.82680.83700.8327 | 0.71300.71790.71500.7210 |
| FastH | 0.63570.68100.69930.7097 | 0.71190.73870.75030.7560 |
| ITQ-CCA | 0.61030.63480.64670.6577 | 0.70260.72200.72680.7297 | | | DSCH | 0.6090.6130.6170.62 | 0.5920.5970.6110.609 |
| --- | --- | --- |
| DSRH | 0.6080.6110.6170.618 | 0.6090.6180.6210.631 |
| DPSH* | 0.9030.8850.9150.911 | N/A | | 0 |
| Data | r | s | t | nnz(A) | nnz(B) | nnz(C) |
| --- | --- | --- | --- | --- | --- | --- |
| square | 1.5E5 | 1.5E5 | 1.5E5 | 6E5 | 6E5 | 2.4E6 |
| tall | 3E5 | 1.5E5 | 3E6 | 6E5 | 6E5 | 2.4E6 | | | fat | 1.5E5 | 3E5 | 1.5E5 | 6E5 | 6E5 | 1.2E6 |
| --- | --- | --- | --- | --- | --- | --- |
| amazon-08/web-google | 735320 | 735323 | 916428 | 5158379 | 4101329 | 28679400 |
| cont1/cont11 | 1918396 | 1468599 | 1961392 | 2592597 | 5382995 | 10254724 |
| cit-patents/patents | 3774768 | 3774768 | 3774768 | 16518948 | 14970767 | 64796579 |
| hugetrace-00/-01 | 4588484 | 4588484 | 12057440 | 13758266 | 13763443 | 38255405 | | 1 |
| Data | r | s | t | nnz(A) | nnz(B) | nnz(C) |
| --- | --- | --- | --- | --- | --- | --- |
| square | 1.5E5 | 1.5E5 | 1.5E5 | 6E5 | 6E5 | 2.4E6 |
| tall | 3E5 | 1.5E5 | 3E6 | 6E5 | 6E5 | 2.4E6 | | | | ax1 | bx2 | ax+bx12 | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| latencyperiod | a | R | b | R | a | b | R |
| papers | | | | | | | |
| LP=2yrs<br>LP=5yrs | 0.804<br>0.2783 | 0.5453<br>0.5377 | 0.1677<br>0.0954 | 0.3666<br>0.4956 | 0.6739<br>0.1751 | 0.0366<br>0.0432 | 0.5555<br>0.5778 |
| patents | | | | | | | |
| LP=2yrs<br>LP=5yrs | 2.4686<br>0.7454 | 0.006<br>0.1431 | -<br>0.27 | -<br>0.1013 | 1.8833<br>0.4833 | 0.3935<br>0.1254 | 0.0389<br>0.1803 |
| legal | | | | | | | |
| LP=2yrs | 0.9337 | 0.5437 | 0.2486 | 0.2317 | 0.8782 | 0.0301 | 0.5464 | | 0 |
| Data | r | s | t | nnz(A) | nnz(B) | nnz(C) |
| --- | --- | --- | --- | --- | --- | --- |
| square | 1.5E5 | 1.5E5 | 1.5E5 | 6E5 | 6E5 | 2.4E6 |
| tall | 3E5 | 1.5E5 | 3E6 | 6E5 | 6E5 | 2.4E6 |
| fat | 1.5E5 | 3E5 | 1.5E5 | 6E5 | 6E5 | 1.2E6 |
| amazon-08/web-google | 735320 | 735323 | 916428 | 5158379 | 4101329 | 28679400 | | | cont1/cont11 | 1918396 | 1468599 | 1961392 | 2592597 | 5382995 | 10254724 |
| --- | --- | --- | --- | --- | --- | --- |
| cit-patents/patents | 3774768 | 3774768 | 3774768 | 16518948 | 14970767 | 64796579 |
| hugetrace-00/-01 | 4588484 | 4588484 | 12057440 | 13758266 | 13763443 | 38255405 | | 1 |
| Data | r | s | t | nnz(A) | nnz(B) | nnz(C) |
| --- | --- | --- | --- | --- | --- | --- |
| square | 1.5E5 | 1.5E5 | 1.5E5 | 6E5 | 6E5 | 2.4E6 |
| tall | 3E5 | 1.5E5 | 3E6 | 6E5 | 6E5 | 2.4E6 |
| fat | 1.5E5 | 3E5 | 1.5E5 | 6E5 | 6E5 | 1.2E6 |
| amazon-08/web-google | 735320 | 735323 | 916428 | 5158379 | 4101329 | 28679400 | | | patents | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| LP=2yrs<br>LP=5yrs | 2.4686<br>0.7454 | 0.006<br>0.1431 | -<br>0.27 | -<br>0.1013 | 1.8833<br>0.4833 | 0.3935<br>0.1254 | 0.0389<br>0.1803 |
| legal | | | | | | | |
| LP=2yrs | 0.9337 | 0.5437 | 0.2486 | 0.2317 | 0.8782 | 0.0301 | 0.5464 | | 0 |
| Method | Accuracy |
| --- | --- |
| B1-ImageClassification<br>B2-PersonClassification<br>B3-Fine-tunedPersonClassification | 63.0<br>61.8<br>66.3 | | | B4-TemporalModelwithImageFeatures<br>B5-TemporalModelwithPersonFeatures | 64.2<br>62.2 |
| --- | --- |
| B6-Two-stageModelwithoutLSTM1<br>B7-Two-stageModelwithoutLSTM2 | 70.1<br>76.8 |
| Two-stageHierarchicalModel | 81.5 | | 1 |
| Method | Accuracy |
| --- | --- |
| B1-ImageClassification<br>B2-PersonClassification<br>B3-Fine-tunedPersonClassification | 63.0<br>61.8<br>66.3 | | | Method | Accuracy |
| --- | --- |
| B1-ImageClassification<br>B2-PersonClassification<br>B3-Fine-tunedPersonClassification | 63.0<br>61.8<br>66.3 |
| B4-TemporalModelwithImageFeatures<br>B5-TemporalModelwithPersonFeatures | 64.2<br>64.0 |
| B6-Two-stageModelwithoutLSTM1<br>B7-Two-stageModelwithoutLSTM2 | 70.1<br>76.8 |
| Two-stageHierarchicalModel | 81.5 | | 0 |
| Method | Accuracy |
| --- | --- |
| B1-ImageClassification<br>B2-PersonClassification<br>B3-Fine-tunedPersonClassification | 63.0<br>61.8<br>66.3 | | | B4-TemporalModelwithImageFeatures<br>B5-TemporalModelwithPersonFeatures | 64.2<br>62.2 |
| --- | --- |
| B6-Two-stageModelwithoutLSTM1<br>B7-Two-stageModelwithoutLSTM2 | 70.1<br>76.8 |
| Two-stageHierarchicalModel | 81.5 | | 1 |
| Method | Accuracy |
| --- | --- |
| B1-ImageClassification<br>B2-PersonClassification<br>B3-Fine-tunedPersonClassification | 63.0<br>61.8<br>66.3 | | | B4-TemporalModelwithImageFeatures<br>B5-TemporalModelwithPersonFeatures | 64.2<br>64.0 |
| --- | --- |
| B6-Two-stageModelwithoutLSTM1<br>B7-Two-stageModelwithoutLSTM2 | 70.1<br>76.8 |
| Two-stageHierarchicalModel | 81.5 | | 0 |
| Model | mAP(iou=0.1) |
| --- | --- |
| SelectiveSearch(withFCNClassifier) | - | | | SlidingWindow(withFCNClassifier) | 0.278 |
| --- | --- |
| PyramidFCNModelwithoutAE | 0.2805 |
| PyramidFCNModelwithConvAE | 0.3069 | | 1 |
| Model | mAP(iou=0.1) |
| --- | --- |
| SelectiveSearch(withFCNClassifier) | - | | | Model | 3questions | 4questions |
| --- | --- | --- |
| Tree | 0.9767 | 0.9683 |
| TreeU | 0.9913 | 0.9887 |
| fMF | 0.9509 | 0.9480 |
| Q-Embeddingmodel | 0.9507 | 0.9486 |
| Q-Ratingmodel | 0.9472 | 0.9469 | | 0 |
| Model | mAP(iou=0.1) |
| --- | --- |
| SelectiveSearch(withFCNClassifier) | - | | | SlidingWindow(withFCNClassifier) | 0.278 |
| --- | --- |
| PyramidFCNModelwithoutAE | 0.2805 |
| PyramidFCNModelwithConvAE | 0.3069 | | 1 |
| Model | mAP(iou=0.1) |
| --- | --- |
| SelectiveSearch(withFCNClassifier) | - | | | Q-Embeddingmodel | 0.9507 | 0.9486 |
| --- | --- | --- |
| Q-Ratingmodel | 0.9472 | 0.9469 | | 0 |
| | Gradual | Sharp | | | | | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Video | #T | TP | FP | FN | P | R | F | #T | TP | FP | FN | P | R |
| LNA | 198 | 147 | 11 | 51 | 0.93 | 0.742 | 0.826 | 45 | 31 | 26 | 14 | 0.544 | 0.689 |
| NFC | 77 | 57 | 11 | 20 | 0.838 | 0.74 | 0.786 | 121 | 115 | 8 | 6 | 0.935 | 0.95 |
| NEC | 94 | 88 | 3 | 6 | 0.967 | 0.936 | 0.951 | 74 | 57 | 5 | 17 | 0.919 | 0.77 |
| HNA | 124 | 107 | 4 | 17 | 0.964 | 0.863 | 0.911 | 24 | 21 | 8 | 3 | 0.724 | 0.875 |
| 3PGC | 228 | 171 | 32 | 57 | 0.842 | 0.75 | 0.794 | 132 | 112 | 48 | 20 | 0.7 | 0.848 |
| CLE | 123 | 98 | 22 | 25 | 0.817 | 0.797 | 0.807 | 244 | 236 | 33 | 8 | 0.877 | 0.967 |
| CDC | 302 | 231 | 27 | 71 | 0.895 | 0.765 | 0.825 | 139 | 129 | 65 | 10 | 0.665 | 0.928 |
| 8NNE | 214 | 184 | 44 | 30 | 0.807 | 0.86 | 0.833 | 424 | 418 | 36 | 6 | 0.921 | 0.986 |
| CLE | 37 | 28 | 7 | 9 | 0.8 | 0.757 | 0.778 | 57 | 54 | 7 | 3 | 0.885 | 0.947 |
| 5PGC | 190 | 155 | 44 | 35 | 0.779 | 0.816 | 0.797 | 81 | 75 | 30 | 6 | 0.714 | 0.926 | | | MNE | 181 | 156 | 11 | 25 | 0.934 | 0.862 | 0.897 | 339 | 323 | 21 | 16 | 0.939 | 0.953 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| CLE | 27 | 25 | 4 | 2 | 0.862 | 0.926 | 0.893 | 44 | 42 | 0 | 2 | 1 | 0.955 |
| 1NNE | 146 | 134 | 11 | 12 | 0.924 | 0.918 | 0.921 | 120 | 118 | 5 | 2 | 0.959 | 0.983 |
| Total | 1941 | 1581 | 231 | 360 | 0.873 | 0.815 | 0.843 | 1844 | 1731 | 292 | 113 | 0.856 | 0.939 | | 1 |
| | Gradual | Sharp | | | | | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Video | #T | TP | FP | FN | P | R | F | #T | TP | FP | FN | P | R |
| LNA | 198 | 147 | 11 | 51 | 0.93 | 0.742 | 0.826 | 45 | 31 | 26 | 14 | 0.544 | 0.689 |
| NFC | 77 | 57 | 11 | 20 | 0.838 | 0.74 | 0.786 | 121 | 115 | 8 | 6 | 0.935 | 0.95 |
| NEC | 94 | 88 | 3 | 6 | 0.967 | 0.936 | 0.951 | 74 | 57 | 5 | 17 | 0.919 | 0.77 |
| HNA | 124 | 107 | 4 | 17 | 0.964 | 0.863 | 0.911 | 24 | 21 | 8 | 3 | 0.724 | 0.875 |
| 3PGC | 228 | 171 | 32 | 57 | 0.842 | 0.75 | 0.794 | 132 | 112 | 48 | 20 | 0.7 | 0.848 |
| CLE | 123 | 98 | 22 | 25 | 0.817 | 0.797 | 0.807 | 244 | 236 | 33 | 8 | 0.877 | 0.967 |
| CDC | 302 | 231 | 27 | 71 | 0.895 | 0.765 | 0.825 | 139 | 129 | 65 | 10 | 0.665 | 0.928 |
| 8NNE | 214 | 184 | 44 | 30 | 0.807 | 0.86 | 0.833 | 424 | 418 | 36 | 6 | 0.921 | 0.986 |
| CLE | 37 | 28 | 7 | 9 | 0.8 | 0.757 | 0.778 | 57 | 54 | 7 | 3 | 0.885 | 0.947 |
| 5PGC | 190 | 155 | 44 | 35 | 0.779 | 0.816 | 0.797 | 81 | 75 | 30 | 6 | 0.714 | 0.926 | | | | Gradual | Sharp | | | | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Video | #T | TP | FP | FN | P | R | F | #T | TP | FP | FN | P |
| 203CNN | 171 | 143 | 57 | 28 | 0.715 | 0.836 | 0.771 | 280 | 230 | 9 | 50 | 0.962 |
| 222CNN | 101 | 80 | 24 | 21 | 0.769 | 0.792 | 0.78 | 309 | 275 | 11 | 34 | 0.962 |
| 224ABC | 131 | 116 | 14 | 15 | 0.892 | 0.885 | 0.889 | 296 | 282 | 8 | 14 | 0.972 |
| 412ABC | 137 | 122 | 11 | 15 | 0.917 | 0.891 | 0.904 | 345 | 323 | 11 | 22 | 0.967 |
| 425ABC | 180 | 170 | 28 | 10 | 0.859 | 0.944 | 0.899 | 295 | 265 | 12 | 30 | 0.957 |
| 515CNN | 131 | 105 | 16 | 26 | 0.868 | 0.802 | 0.833 | 283 | 259 | 15 | 24 | 0.945 |
| 531CNN | 108 | 85 | 24 | 23 | 0.78 | 0.787 | 0.783 | 359 | 316 | 18 | 43 | 0.946 |
| 619ABC | 127 | 52 | 131 | 75 | 0.284 | 0.409 | 0.335 | 321 | 154 | 155 | 167 | 0.498 |
| Total | 1086 | 873 | 305 | 213 | 0.741 | 0.804 | 0.771 | 2488 | 2104 | 239 | 384 | 0.898 | | 0 |
| | Gradual | Sharp | | | | | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Video | #T | TP | FP | FN | P | R | F | #T | TP | FP | FN | P | R |
| LNA | 198 | 147 | 11 | 51 | 0.93 | 0.742 | 0.826 | 45 | 31 | 26 | 14 | 0.544 | 0.689 |
| NFC | 77 | 57 | 11 | 20 | 0.838 | 0.74 | 0.786 | 121 | 115 | 8 | 6 | 0.935 | 0.95 |
| NEC | 94 | 88 | 3 | 6 | 0.967 | 0.936 | 0.951 | 74 | 57 | 5 | 17 | 0.919 | 0.77 |
| HNA | 124 | 107 | 4 | 17 | 0.964 | 0.863 | 0.911 | 24 | 21 | 8 | 3 | 0.724 | 0.875 |
| 3PGC | 228 | 171 | 32 | 57 | 0.842 | 0.75 | 0.794 | 132 | 112 | 48 | 20 | 0.7 | 0.848 |
| CLE | 123 | 98 | 22 | 25 | 0.817 | 0.797 | 0.807 | 244 | 236 | 33 | 8 | 0.877 | 0.967 |
| CDC | 302 | 231 | 27 | 71 | 0.895 | 0.765 | 0.825 | 139 | 129 | 65 | 10 | 0.665 | 0.928 | | | 8NNE | 214 | 184 | 44 | 30 | 0.807 | 0.86 | 0.833 | 424 | 418 | 36 | 6 | 0.921 | 0.986 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| CLE | 37 | 28 | 7 | 9 | 0.8 | 0.757 | 0.778 | 57 | 54 | 7 | 3 | 0.885 | 0.947 |
| 5PGC | 190 | 155 | 44 | 35 | 0.779 | 0.816 | 0.797 | 81 | 75 | 30 | 6 | 0.714 | 0.926 |
| MNE | 181 | 156 | 11 | 25 | 0.934 | 0.862 | 0.897 | 339 | 323 | 21 | 16 | 0.939 | 0.953 |
| CLE | 27 | 25 | 4 | 2 | 0.862 | 0.926 | 0.893 | 44 | 42 | 0 | 2 | 1 | 0.955 |
| 1NNE | 146 | 134 | 11 | 12 | 0.924 | 0.918 | 0.921 | 120 | 118 | 5 | 2 | 0.959 | 0.983 |
| Total | 1941 | 1581 | 231 | 360 | 0.873 | 0.815 | 0.843 | 1844 | 1731 | 292 | 113 | 0.856 | 0.939 | | 1 |
| | Gradual | Sharp | | | | | | | | | | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Video | #T | TP | FP | FN | P | R | F | #T | TP | FP | FN | P | R |
| LNA | 198 | 147 | 11 | 51 | 0.93 | 0.742 | 0.826 | 45 | 31 | 26 | 14 | 0.544 | 0.689 |
| NFC | 77 | 57 | 11 | 20 | 0.838 | 0.74 | 0.786 | 121 | 115 | 8 | 6 | 0.935 | 0.95 |
| NEC | 94 | 88 | 3 | 6 | 0.967 | 0.936 | 0.951 | 74 | 57 | 5 | 17 | 0.919 | 0.77 |
| HNA | 124 | 107 | 4 | 17 | 0.964 | 0.863 | 0.911 | 24 | 21 | 8 | 3 | 0.724 | 0.875 |
| 3PGC | 228 | 171 | 32 | 57 | 0.842 | 0.75 | 0.794 | 132 | 112 | 48 | 20 | 0.7 | 0.848 |
| CLE | 123 | 98 | 22 | 25 | 0.817 | 0.797 | 0.807 | 244 | 236 | 33 | 8 | 0.877 | 0.967 |
| CDC | 302 | 231 | 27 | 71 | 0.895 | 0.765 | 0.825 | 139 | 129 | 65 | 10 | 0.665 | 0.928 | | | 224ABC | 131 | 116 | 14 | 15 | 0.892 | 0.885 | 0.889 | 296 | 282 | 8 | 14 | 0.972 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| 412ABC | 137 | 122 | 11 | 15 | 0.917 | 0.891 | 0.904 | 345 | 323 | 11 | 22 | 0.967 |
| 425ABC | 180 | 170 | 28 | 10 | 0.859 | 0.944 | 0.899 | 295 | 265 | 12 | 30 | 0.957 |
| 515CNN | 131 | 105 | 16 | 26 | 0.868 | 0.802 | 0.833 | 283 | 259 | 15 | 24 | 0.945 |
| 531CNN | 108 | 85 | 24 | 23 | 0.78 | 0.787 | 0.783 | 359 | 316 | 18 | 43 | 0.946 |
| 619ABC | 127 | 52 | 131 | 75 | 0.284 | 0.409 | 0.335 | 321 | 154 | 155 | 167 | 0.498 |
| Total | 1086 | 873 | 305 | 213 | 0.741 | 0.804 | 0.771 | 2488 | 2104 | 239 | 384 | 0.898 | | 0 |
| Dataset | MMPC | HITON-PC | MMMB | HITON-MB | IAMB | mRMR | CMI | JMI |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| mushroom | 0.89 | 1.19 | 42.98 | 44.12 | 0.16 | 0.03 | 0.01 | 0.03 | | | kr-vs-kp | 0.31 | 0.33 | 6.87 | 6.21 | 0.43 | 0.04 | 0.03 | 0.07 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| madelon | 0.18 | 0.21 | 0.87 | 0.9448 | 3.07 | 0.4 | 0.03 | 1.53 |
| gisstee | 32,684 | 65,308 | 50,929 | 107,870 | 12.90 | 8.38 | 1.32 | 52 |
| spambase | 35 | 37 | 200 | 203 | 0.7648 | 0.09 | 0.06 | 0.24 |
| bankrupty | 112 | 95 | 296 | 239 | 2.06 | 0.31 | 0.11 | 1.27 | | 1 |
| Dataset | MMPC | HITON-PC | MMMB | HITON-MB | IAMB | mRMR | CMI | JMI |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| mushroom | 0.89 | 1.19 | 42.98 | 44.12 | 0.16 | 0.03 | 0.01 | 0.03 | | | Dataset | MMPC | HITON-PC | MMMB | HITON-MB | IAMB | mRMR | CMI | JMI |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| mushroom | 10 | 10 | 20 | 20 | 3 | 5/15 | 5/5 | 10/5 |
| kr-vs-kp | 8 | 8 | 19 | 19 | 7 | 10/25 | 5/15 | 5/15 |
| madelon | 5 | 5 | 6 | 5 | 6 | 25/20 | 5/15 | 20/20 |
| gisstee | 295 | 294 | 1384 | 1402 | 2 | 15/20 | 25/25 | 25/20 |
| spambase | 24 | 24 | 45 | 45 | 8 | 20/25 | 15/20 | 10/15 |
| bankrupty | 29 | 28 | 60 | 56 | 9 | 15/20 | 5/15 | 5/25 | | 0 |
| Dataset | MMPC | HITON-PC | MMMB | HITON-MB | IAMB | mRMR | CMI | JMI |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| mushroom | 0.89 | 1.19 | 42.98 | 44.12 | 0.16 | 0.03 | 0.01 | 0.03 | | | kr-vs-kp | 0.31 | 0.33 | 6.87 | 6.21 | 0.43 | 0.04 | 0.03 | 0.07 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| madelon | 0.18 | 0.21 | 0.87 | 0.9448 | 3.07 | 0.4 | 0.03 | 1.53 |
| gisstee | 32,684 | 65,308 | 50,929 | 107,870 | 12.90 | 8.38 | 1.32 | 52 |
| spambase | 35 | 37 | 200 | 203 | 0.7648 | 0.09 | 0.06 | 0.24 |
| bankrupty | 112 | 95 | 296 | 239 | 2.06 | 0.31 | 0.11 | 1.27 | | 1 |
| Dataset | MMPC | HITON-PC | MMMB | HITON-MB | IAMB | mRMR | CMI | JMI |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| mushroom | 0.89 | 1.19 | 42.98 | 44.12 | 0.16 | 0.03 | 0.01 | 0.03 | | | kr-vs-kp | 8 | 8 | 19 | 19 | 7 | 10/25 | 5/15 | 5/15 |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| madelon | 5 | 5 | 6 | 5 | 6 | 25/20 | 5/15 | 20/20 |
| gisstee | 295 | 294 | 1384 | 1402 | 2 | 15/20 | 25/25 | 25/20 |
| spambase | 24 | 24 | 45 | 45 | 8 | 20/25 | 15/20 | 10/15 |
| bankrupty | 29 | 28 | 60 | 56 | 9 | 15/20 | 5/15 | 5/25 | | 0 |
| Setting/Pmal | 0.50.60.70.80.91.0 |
| --- | --- |
| n=16,α=0.4375,T=4 | 0.01310.02210.03740.07770.18530.3162 |
| n=11,α=0.4545,T=9 | 0.02170.02780.03020.04440.13200.3708 | | | n=10,α=0.4,T=10 | 0.01760.02110.02000.03110.10030.2663 |
| --- | --- |
| n=5,α=0.4,T=15 | 0.08140.09510.09190.08690.16400.3189 | | 1 |
| Setting/Pmal | 0.50.60.70.80.91.0 |
| --- | --- |
| n=16,α=0.4375,T=4 | 0.01310.02210.03740.07770.18530.3162 |
| n=11,α=0.4545,T=9 | 0.02170.02780.03020.04440.13200.3708 | | | T=1 | T=3 |
| --- | --- |
| 1.6839 | 0.7567 |
| 1.6639 | 0.7684 |
| 1.6090 | 0.8258 |
| 1.6793 | 0.8017 |
| 1.5191 | 0.7784 |
| 1.4991 | 0.8218 |
| 1.4101 | 0.8027 |
| 1.3879 | 0.7786 |
| 1.4162 | 0.7408 | | 0 |
| Setting/Pmal | 0.50.60.70.80.91.0 |
| --- | --- |
| n=16,α=0.4375,T=4 | 0.01310.02210.03740.07770.18530.3162 | | | n=11,α=0.4545,T=9 | 0.02170.02780.03020.04440.13200.3708 |
| --- | --- |
| n=10,α=0.4,T=10 | 0.01760.02110.02000.03110.10030.2663 |
| n=5,α=0.4,T=15 | 0.08140.09510.09190.08690.16400.3189 | | 1 |
| Setting/Pmal | 0.50.60.70.80.91.0 |
| --- | --- |
| n=16,α=0.4375,T=4 | 0.01310.02210.03740.07770.18530.3162 | | | 1.5191 | 0.7784 |
| --- | --- |
| 1.4991 | 0.8218 |
| 1.4101 | 0.8027 |
| 1.3879 | 0.7786 |
| 1.4162 | 0.7408 | | 0 |
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