premise
string
hypothesis
string
label
int64
| DataSet | WSJsec.IDs | Sentences# | Tokens# | | --- | --- | --- | --- | | Training | 15-18 | 8,936 | 211,727 | | Develop | N/A | N/A | N/A |
| Test | 20 | 2,012 | 47,377 | | --- | --- | --- | --- | | #oftagtypes(IOBESscheme) | 42 | | |
1
| DataSet | WSJsec.IDs | Sentences# | Tokens# | | --- | --- | --- | --- | | Training | 15-18 | 8,936 | 211,727 | | Develop | N/A | N/A | N/A |
| DataSet | WSJsec.IDs | Sentences# | Tokens# | | --- | --- | --- | --- | | Training | 0-18 | 38,219 | 912,344 | | Develop | 19-21 | 5,527 | 131,768 | | Test | 22-24 | 5,462 | 129,654 | | #oftagtypes | 45 | | |
0
| DataSet | WSJsec.IDs | Sentences# | Tokens# | | --- | --- | --- | --- | | Training | 15-18 | 8,936 | 211,727 |
| Develop | N/A | N/A | N/A | | --- | --- | --- | --- | | Test | 20 | 2,012 | 47,377 | | #oftagtypes(IOBESscheme) | 42 | | |
1
| DataSet | WSJsec.IDs | Sentences# | Tokens# | | --- | --- | --- | --- | | Training | 15-18 | 8,936 | 211,727 |
| Test | 22-24 | 5,462 | 129,654 | | --- | --- | --- | --- | | #oftagtypes | 45 | | |
0
| | Throughput | | | | --- | --- | --- | --- | | (Client-Server) | Host-Network | LinuxBridge | OpenvSwitch | | Host-Host | 35.71Gbpsσ=0.32 | - | - |
| Container-Host | 35.13Gbpsσ=0.48 | 15.82Gbpsσ=0.36 | 16.01Gbpsσ=0.47 | | --- | --- | --- | --- | | Host-Container | 34.96Gbpsσ=0.63 | 15.96Gbpsσ=0.51 | 16.86Gbpsσ=0.35 | | Virtualmachine-Host | - | 8.64Gbpsσ=0.28 | 7.94Gbpsσ=0.69 | | Host-Virtualmachine | - | 9.24Gbpsσ=0.27 | 8.77Gbpsσ=0.55 |
1
| | Throughput | | | | --- | --- | --- | --- | | (Client-Server) | Host-Network | LinuxBridge | OpenvSwitch | | Host-Host | 35.71Gbpsσ=0.32 | - | - |
| TotalNodes | 8 | Packetsize | 2000bytes | | --- | --- | --- | --- | | DataSlots | 13 | PacketgenerationInterval | 1msec | | Tc | 1.5msec | Queuelength | 100 | | Td | 2msec | Routing | AODV | | Ta | 0.5msec | Simulationtime | 20sec | | Tq | 20msec | Source | CBR | | Flow1 | Node1to2 | Flow3 | Node5to6 | | Flow2 | Node3to4 | Flow4 | Node7to8 | | Throughputflow1 | 89.79kbps | Throughputflow3 | 91.21kbps | | Throughputflow2 | 84.08kbps | Throughputflow4 | 89.79kbps |
0
| | Throughput | | | | --- | --- | --- | --- | | (Client-Server) | Host-Network | LinuxBridge | OpenvSwitch | | Host-Host | 35.71Gbpsσ=0.32 | - | - | | Container-Host | 35.13Gbpsσ=0.48 | 15.82Gbpsσ=0.36 | 16.01Gbpsσ=0.47 |
| Host-Container | 34.96Gbpsσ=0.63 | 15.96Gbpsσ=0.51 | 16.86Gbpsσ=0.35 | | --- | --- | --- | --- | | Virtualmachine-Host | - | 8.64Gbpsσ=0.28 | 7.94Gbpsσ=0.69 | | Host-Virtualmachine | - | 9.24Gbpsσ=0.27 | 8.77Gbpsσ=0.55 |
1
| | Throughput | | | | --- | --- | --- | --- | | (Client-Server) | Host-Network | LinuxBridge | OpenvSwitch | | Host-Host | 35.71Gbpsσ=0.32 | - | - | | Container-Host | 35.13Gbpsσ=0.48 | 15.82Gbpsσ=0.36 | 16.01Gbpsσ=0.47 |
| Flow1 | Node1to2 | Flow3 | Node5to6 | | --- | --- | --- | --- | | Flow2 | Node3to4 | Flow4 | Node7to8 | | Throughputflow1 | 89.79kbps | Throughputflow3 | 91.21kbps | | Throughputflow2 | 84.08kbps | Throughputflow4 | 89.79kbps |
0
| Method | EdgeCost | EP1 | EP2 | EP3 | EP4 | EP5 | EP6 | avg | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 1NN | Euc | 66.9 | 63.5 | 58.5 | 65.4 | 73.5 | 70.0 | 66.3 | | AVG | Euc | 75.1 | 74.0 | 70.9 | 76.8 | 82.8 | 84.5 | 77.3 | | TopTen | Euc | 93.4 | 90.3 | 66.9 | 92.5 | 90.7 | 94.5 | 88.0 | | TopTen | NC | 95.2 | 93.8 | 69.7 | 92.2 | 92.0 | 94.0 | 89.4 | | HSL(Our) | Euc | 94.7 | 94.3 | 56.4 | 93.4 | 91.6 | 94.6 | 87.5 |
| HSL(Our) | NC | 95.9 | 94.9 | 72.6 | 91.9 | 91.9 | 94.6 | 90.3 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | HCSL(Our) | NC | 95.5 | 95.1 | 88.8 | 93.2 | 91.6 | 94.3 | 93.0 |
1
| Method | EdgeCost | EP1 | EP2 | EP3 | EP4 | EP5 | EP6 | avg | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 1NN | Euc | 66.9 | 63.5 | 58.5 | 65.4 | 73.5 | 70.0 | 66.3 | | AVG | Euc | 75.1 | 74.0 | 70.9 | 76.8 | 82.8 | 84.5 | 77.3 | | TopTen | Euc | 93.4 | 90.3 | 66.9 | 92.5 | 90.7 | 94.5 | 88.0 | | TopTen | NC | 95.2 | 93.8 | 69.7 | 92.2 | 92.0 | 94.0 | 89.4 | | HSL(Our) | Euc | 94.7 | 94.3 | 56.4 | 93.4 | 91.6 | 94.6 | 87.5 |
| Method | AVG-<br>AUC | M-<br>AUC | SK-<br>AUC | M-<br>SP82 | M-<br>SP89 | M-<br>SP95 | M-<br>SENS | M-<br>SPEC | SK-<br>SENS | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | [24]TopAVG | 0.911 | 0.868 | 0.953 | 0.729 | 0.588 | 0.366 | 0.735 | 0.851 | 0.978 | | [25]TopSK | 0.910 | 0.856 | 0.965 | 0.727 | 0.555 | 0.404 | 0.103 | 0.998 | 0.178 | | [26]TopM | 0.908 | 0.874 | 0.943 | 0.747 | 0.590 | 0.395 | 0.547 | 0.950 | 0.356 | | AVGSC | 0.913 | 0.872 | 0.954 | 0.778 | 0.605 | 0.435 | 0.214 | 0.988 | 0.600 | | L-SVM | 0.926 | 0.892 | 0.960 | 0.834 | 0.692 | 0.571 | 0.718 | 0.901 | 0.878 | | NL-SVM | 0.904 | 0.853 | 0.955 | 0.801 | 0.449 | 0.168 | 0.675 | 0.909 | 0.889 |
0
| Method | EdgeCost | EP1 | EP2 | EP3 | EP4 | EP5 | EP6 | avg | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 1NN | Euc | 66.9 | 63.5 | 58.5 | 65.4 | 73.5 | 70.0 | 66.3 | | AVG | Euc | 75.1 | 74.0 | 70.9 | 76.8 | 82.8 | 84.5 | 77.3 | | TopTen | Euc | 93.4 | 90.3 | 66.9 | 92.5 | 90.7 | 94.5 | 88.0 | | TopTen | NC | 95.2 | 93.8 | 69.7 | 92.2 | 92.0 | 94.0 | 89.4 |
| HSL(Our) | Euc | 94.7 | 94.3 | 56.4 | 93.4 | 91.6 | 94.6 | 87.5 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | HSL(Our) | NC | 95.9 | 94.9 | 72.6 | 91.9 | 91.9 | 94.6 | 90.3 | | HCSL(Our) | NC | 95.5 | 95.1 | 88.8 | 93.2 | 91.6 | 94.3 | 93.0 |
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| Method | EdgeCost | EP1 | EP2 | EP3 | EP4 | EP5 | EP6 | avg | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 1NN | Euc | 66.9 | 63.5 | 58.5 | 65.4 | 73.5 | 70.0 | 66.3 | | AVG | Euc | 75.1 | 74.0 | 70.9 | 76.8 | 82.8 | 84.5 | 77.3 | | TopTen | Euc | 93.4 | 90.3 | 66.9 | 92.5 | 90.7 | 94.5 | 88.0 | | TopTen | NC | 95.2 | 93.8 | 69.7 | 92.2 | 92.0 | 94.0 | 89.4 |
| L-SVM | 0.926 | 0.892 | 0.960 | 0.834 | 0.692 | 0.571 | 0.718 | 0.901 | 0.878 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | NL-SVM | 0.904 | 0.853 | 0.955 | 0.801 | 0.449 | 0.168 | 0.675 | 0.909 | 0.889 |
0
| Benign | | | | --- | --- | --- | | Min. | Max. | Min. | | 43 | 57 | 44 | | 3,020 | 26,924 | 3,020 | | 941 | 8,387 | 939 |
| 941 | 14,040 | 941 | | --- | --- | --- | | 0.3 | 110 | 0.3 | | 2.9 | 737 | 2.9 | | 4 | 1,116 | 4 | | 0.4 | 1,434 | 0.4 |
1
| Benign | | | | --- | --- | --- | | Min. | Max. | Min. | | 43 | 57 | 44 | | 3,020 | 26,924 | 3,020 | | 941 | 8,387 | 939 |
| HigherBetter | | | | | --- | --- | --- | --- | | Pct.<1.25 | Pct.<1.25 | Pct.<1.25 | MeanAbsoluteError | | 80.55 | 94.65 | 98.26 | 0.399 | | 79.88 | 94.45 | 98.15 | 0.411 | | 78.70 | 94.06 | 98.13 | 0.419 | | 78.72 | 94.13 | 98.08 | 0.423 | | 80.17 | 94.74 | 98.27 | 0.401 | | 79.26 | 94.19 | 98.07 | 0.422 |
0
| Benign | | | | --- | --- | --- | | Min. | Max. | Min. | | 43 | 57 | 44 | | 3,020 | 26,924 | 3,020 | | 941 | 8,387 | 939 | | 941 | 14,040 | 941 | | 0.3 | 110 | 0.3 | | 2.9 | 737 | 2.9 |
| 4 | 1,116 | 4 | | --- | --- | --- | | 0.4 | 1,434 | 0.4 |
1
| Benign | | | | --- | --- | --- | | Min. | Max. | Min. | | 43 | 57 | 44 | | 3,020 | 26,924 | 3,020 | | 941 | 8,387 | 939 | | 941 | 14,040 | 941 | | 0.3 | 110 | 0.3 | | 2.9 | 737 | 2.9 |
| 80.17 | 94.74 | 98.27 | 0.401 | | --- | --- | --- | --- | | 79.26 | 94.19 | 98.07 | 0.422 |
0
| Solution | Buildspace(bits) | Buildtime | | --- | --- | --- | | prev.(worst-case) | O((n+\|L\|)logn) | O(n+\|L\|logσ) | | theorems??,??(worst-case) | O((n+\|L\|+\|F\|logσ)logn)C | O(n+\|L\|logσ)C |
| theorem??(randomizedexpected) | O((n+\|F\|logσ)logn) | O(n+\|L\|logσ)) | | --- | --- | --- | | theorem??(Monte-Carlo) | O((n+\|F\|)logn) | O(n+\|L\|) |
1
| Solution | Buildspace(bits) | Buildtime | | --- | --- | --- | | prev.(worst-case) | O((n+\|L\|)logn) | O(n+\|L\|logσ) | | theorems??,??(worst-case) | O((n+\|L\|+\|F\|logσ)logn)C | O(n+\|L\|logσ)C |
| | ExactlyK-sparsesignal | | | | | --- | --- | --- | --- | --- | | Samples | Complexity | Assumption | Samples | | | | 4<br>O(KlogN) | 5<br>O(KlogN) | K=O(N) | 4<br>O(KlogN) | | | O(K) | O(KlogN) | K=O(N) | N<br>O(Klog()/loglogN)<br>K | | | O(K) | O(KlogK+K(loglogN)) | K=O(N) | O(KlogN) | | | O(K) | 3O(KlogN) | K=O(N) | void | | | O(K) | O(KlogK) | α<br>K=O(N),α<1 | void | | Thispaper | O(K) | O(KlogK) | K=O(N) | O(K) |
0
| Solution | Buildspace(bits) | Buildtime | | --- | --- | --- | | prev.(worst-case) | O((n+\|L\|)logn) | O(n+\|L\|logσ) | | theorems??,??(worst-case) | O((n+\|L\|+\|F\|logσ)logn)C | O(n+\|L\|logσ)C |
| theorem??(randomizedexpected) | O((n+\|F\|logσ)logn) | O(n+\|L\|logσ)) | | --- | --- | --- | | theorem??(Monte-Carlo) | O((n+\|F\|)logn) | O(n+\|L\|) |
1
| Solution | Buildspace(bits) | Buildtime | | --- | --- | --- | | prev.(worst-case) | O((n+\|L\|)logn) | O(n+\|L\|logσ) | | theorems??,??(worst-case) | O((n+\|L\|+\|F\|logσ)logn)C | O(n+\|L\|logσ)C |
| | O(K) | O(KlogN) | K=O(N) | N<br>O(Klog()/loglogN)<br>K | | --- | --- | --- | --- | --- | | | O(K) | O(KlogK+K(loglogN)) | K=O(N) | O(KlogN) | | | O(K) | 3O(KlogN) | K=O(N) | void | | | O(K) | O(KlogK) | α<br>K=O(N),α<1 | void | | Thispaper | O(K) | O(KlogK) | K=O(N) | O(K) |
0
| Heuristic | | | | | --- | --- | --- | --- | | Connection | Connection | Connection | Connection |
| Average<br>(±StdError) | Average<br>(±StdError) | Average<br>(±StdError) | Average<br>(±StdError) | | | --- | --- | --- | --- | --- | | Spanning-tree<br>Hitting-distance | 122.747(±2.812)<br>103.945(±1.320) | 130.998(±2.917)<br>105.797(±2.322) | 0.369(±0.023)<br>0.454(±0.027) | 0.360(±0.023)<br>0.459(±0.027) | | Greedy<br>Degreebased<br>PageRankbased | 101.969(±0.429)<br>114.182(±2.386)<br>114.894(±2.452) | 102.785(±0.426)<br>113.285(±2.305)<br>112.392(±2.266) | 0.428(±0.025)<br>0.411(±0.024)<br>0.407(±0.025) | 0.426(±0.026)<br>0.394(±0.023)<br>0.398(±0.023) | | | 115.117(±1.782) | 119.243(±1.873) | | |
1
| Heuristic | | | | | --- | --- | --- | --- | | Connection | Connection | Connection | Connection |
| (a)Digg:correlation | | | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | filter | #edges | CN | JC | AA | CS | CSAL | NC | NCAL | | co-votes¡200<br>co-votes¡400<br>co-votes¡800<br>all | 1,410,590<br>1,429,712<br>1,438,320<br>1,439,842 | 0.256<br>0.277<br>0.283<br>0.279 | 0.129<br>0.158<br>0.170<br>0.163 | 0.232<br>0.246<br>0.249<br>0.246 | 0.015<br>0.019<br>0.024<br>0.025 | -0.010<br>-0.009<br>-0.008<br>-0.008 | 0.256<br>0.277<br>0.283<br>0.279 | -0.028<br>-0.027<br>-0.025<br>-0.023 | | (b)Twitter:correlation | | | | | | | | | | | #edges | CN | JC | AA | CS | CSAL | NC | NCAL | | | 28M | -0.769 | -0.339 | -0.755 | 0.523 | 0.350 | -0.769 | 0.406 |
0
| Heuristic | | | | | --- | --- | --- | --- | | Connection | Connection | Connection | Connection | | Average<br>(±StdError) | Average<br>(±StdError) | Average<br>(±StdError) | Average<br>(±StdError) |
| Spanning-tree<br>Hitting-distance | 122.747(±2.812)<br>103.945(±1.320) | 130.998(±2.917)<br>105.797(±2.322) | 0.369(±0.023)<br>0.454(±0.027) | 0.360(±0.023)<br>0.459(±0.027) | | --- | --- | --- | --- | --- | | Greedy<br>Degreebased<br>PageRankbased | 101.969(±0.429)<br>114.182(±2.386)<br>114.894(±2.452) | 102.785(±0.426)<br>113.285(±2.305)<br>112.392(±2.266) | 0.428(±0.025)<br>0.411(±0.024)<br>0.407(±0.025) | 0.426(±0.026)<br>0.394(±0.023)<br>0.398(±0.023) | | | 115.117(±1.782) | 119.243(±1.873) | | |
1
| Heuristic | | | | | --- | --- | --- | --- | | Connection | Connection | Connection | Connection | | Average<br>(±StdError) | Average<br>(±StdError) | Average<br>(±StdError) | Average<br>(±StdError) |
| (b)Twitter:correlation | | | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | | #edges | CN | JC | AA | CS | CSAL | NC | NCAL | | | 28M | -0.769 | -0.339 | -0.755 | 0.523 | 0.350 | -0.769 | 0.406 |
0
| Parameter | One | Two | | | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | Height | FamilySize | IPED2 | IPED | COP | FamilySize | IPED2 | IPED | COP | FamilySize | IPED2 |
| g=2 | 32 | 0.962 | 0.995 | 0.83 | 34 | 0.976 | 0.964 | 0.842 | 63 | 0.972 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | g=3 | 42 | 0.780 | 0.789 | 0.428 | 50 | 0.684 | 0.631 | 0.422 | 82 | 0.750 | | g=4 | 52 | 0.714 | 0.772 | 0.323 | 62 | 0.618 | 0.569 | 0.339 | 102 | 0.624 | | g=5 | 64 | 0.704 | 0.771 | 0.322 | 72 | 0.603 | 0.569 | 0.337 | 122 | 0.616 |
1
| Parameter | One | Two | | | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | Height | FamilySize | IPED2 | IPED | COP | FamilySize | IPED2 | IPED | COP | FamilySize | IPED2 |
| network | τ(G) | σ(G) | θ(G) | | --- | --- | --- | --- | | cithepph | 0.22 | 0.56 | 0.37 | | cithepth | 0.2 | 0.53 | 0.36 | | colastroph | 0.24 | 0.51 | 0.49 | | colcondmat | 0.37 | 0.64 | 0.76 | | colgrqc | 0.44 | 0.79 | 0.89 | | colhepph | 0.26 | 0.58 | 0.7 | | colhepth | 0.39 | 0.69 | 0.83 | | emailenron | 0.21 | 0.5 | 0.63 | | emaileuall | 0.39 | 0.73 | 0.76 | | p2p4 | 0.11 | 0.38 | 0.36 | | p2p5 | 0.11 | 0.4 | 0.36 | | p2p6 | 0.12 | 0.39 | 0.38 | | p2p8 | 0.15 | 0.46 | 0.46 | | p2p9 | 0.15 | 0.46 | 0.42 | | p2p24 | 0.21 | 0.47 | 0.48 | | p2p25 | 0.23 | 0.49 | 0.5 | | p2p30 | 0.24 | 0.5 | 0.53 | | p2p31 | 0.25 | 0.5 | 0.52 | | roadnetca | 0.67 | 0.99 | 0.98 | | roadnetpa | 0.66 | 0.99 | 0.98 | | roadnettx | 0.67 | 0.99 | 0.98 |
0
| Parameter | One | Two | | | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | Height | FamilySize | IPED2 | IPED | COP | FamilySize | IPED2 | IPED | COP | FamilySize | IPED2 | | g=2 | 32 | 0.962 | 0.995 | 0.83 | 34 | 0.976 | 0.964 | 0.842 | 63 | 0.972 |
| g=3 | 42 | 0.780 | 0.789 | 0.428 | 50 | 0.684 | 0.631 | 0.422 | 82 | 0.750 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | g=4 | 52 | 0.714 | 0.772 | 0.323 | 62 | 0.618 | 0.569 | 0.339 | 102 | 0.624 | | g=5 | 64 | 0.704 | 0.771 | 0.322 | 72 | 0.603 | 0.569 | 0.337 | 122 | 0.616 |
1
| Parameter | One | Two | | | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | Height | FamilySize | IPED2 | IPED | COP | FamilySize | IPED2 | IPED | COP | FamilySize | IPED2 | | g=2 | 32 | 0.962 | 0.995 | 0.83 | 34 | 0.976 | 0.964 | 0.842 | 63 | 0.972 |
| roadnetpa | 0.66 | 0.99 | 0.98 | | --- | --- | --- | --- | | roadnettx | 0.67 | 0.99 | 0.98 |
0
| Scripts | NumberofSamples | | | | | --- | --- | --- | --- | --- | | CharacterLevel | WordLevel | | | | | Online | Offline | Online | Offline | | | Bangla | 10,509 | 10,897 | 10,589 | 10,687 | | Devanagari | 10,897 | 11,021 | 10,847 | 10,645 | | Gurumukhi | 9,897 | 9,789 | 9,569 | 9,657 |
| Odia | 9,457 | 9,789 | 9,147 | 9,234 | | --- | --- | --- | --- | --- | | Tamil | 9,456 | 9,476 | 9,874 | 9,476 | | Telegu | 10,486 | 10,789 | 10,687 | 10,694 | | English | 10,489 | 10,879 | 11,023 | 11,458 |
1
| Scripts | NumberofSamples | | | | | --- | --- | --- | --- | --- | | CharacterLevel | WordLevel | | | | | Online | Offline | Online | Offline | | | Bangla | 10,509 | 10,897 | 10,589 | 10,687 | | Devanagari | 10,897 | 11,021 | 10,847 | 10,645 | | Gurumukhi | 9,897 | 9,789 | 9,569 | 9,657 |
| 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
| Scripts | NumberofSamples | | | | | --- | --- | --- | --- | --- | | CharacterLevel | WordLevel | | | | | Online | Offline | Online | Offline | | | Bangla | 10,509 | 10,897 | 10,589 | 10,687 | | Devanagari | 10,897 | 11,021 | 10,847 | 10,645 | | Gurumukhi | 9,897 | 9,789 | 9,569 | 9,657 | | Odia | 9,457 | 9,789 | 9,147 | 9,234 |
| Tamil | 9,456 | 9,476 | 9,874 | 9,476 | | --- | --- | --- | --- | --- | | Telegu | 10,486 | 10,789 | 10,687 | 10,694 | | English | 10,489 | 10,879 | 11,023 | 11,458 |
1
| Scripts | NumberofSamples | | | | | --- | --- | --- | --- | --- | | CharacterLevel | WordLevel | | | | | Online | Offline | Online | Offline | | | Bangla | 10,509 | 10,897 | 10,589 | 10,687 | | Devanagari | 10,897 | 11,021 | 10,847 | 10,645 | | Gurumukhi | 9,897 | 9,789 | 9,569 | 9,657 | | Odia | 9,457 | 9,789 | 9,147 | 9,234 |
| Marathi | 204 | 14 | | --- | --- | --- | | Telugu | 338 | 18 | | Oriya | 98 | 6 | | Gujarati | 49 | 7 | | Konkani | 6 | 4 |
0
| TurnHold’emTurnBuckets: | 200 | 2,000 | 20,000 | | --- | --- | --- | --- | | TrunkStrategy | 684.6 | 465.1 | 345.5 | | Unsafe | 130.4 | 85.95 | 79.34 | | Resolve | 454.9 | 321.5 | 251.8 | | Maxmargin | 427.6 | 299.6 | 234.4 | | Reach-Maxmargin | 424.4 | 298.3 | 233.5 | | Reach-Maxmargin(notsplit) | 333.4 | 229.4 | 175.5 |
| Estimate | 120.6 | 89.43 | 76.44 | | --- | --- | --- | --- | | Estimate+Distributional | 119.4 | 87.83 | 74.35 | | Reach-Estimate+Distributional | 116.8 | 85.80 | 72.59 | | Reach-Estimate+Distributional(notsplit) | 113.3 | 83.24 | 70.68 |
1
| TurnHold’emTurnBuckets: | 200 | 2,000 | 20,000 | | --- | --- | --- | --- | | TrunkStrategy | 684.6 | 465.1 | 345.5 | | Unsafe | 130.4 | 85.95 | 79.34 | | Resolve | 454.9 | 321.5 | 251.8 | | Maxmargin | 427.6 | 299.6 | 234.4 | | Reach-Maxmargin | 424.4 | 298.3 | 233.5 | | Reach-Maxmargin(notsplit) | 333.4 | 229.4 | 175.5 |
| SmallFlopHold’emFlopBuckets: | 200 | 2,000 | 30,000 | | --- | --- | --- | --- | | TrunkStrategy | 88.69 | 37.374 | 9.128 | | Unsafe | 14.68 | 3.958 | 0.5514 | | Resolve | 60.16 | 17.79 | 5.407 | | Maxmargin | 30.05 | 13.99 | 4.343 | | Reach-Maxmargin | 29.88 | 13.90 | 4.147 | | Reach-Maxmargin(notsplit) | 24.87 | 9.807 | 2.588 | | Estimate | 11.66 | 6.261 | 2.423 | | Estimate+Distributional | 10.44 | 6.245 | 3.430 | | Reach-Estimate+Distributional | 10.21 | 5.798 | 2.258 | | Reach-Estimate+Distributional(notsplit) | 9.560 | 4.924 | 1.733 |
0
| TurnHold’emTurnBuckets: | 200 | 2,000 | 20,000 | | --- | --- | --- | --- | | TrunkStrategy | 684.6 | 465.1 | 345.5 |
| Unsafe | 130.4 | 85.95 | 79.34 | | --- | --- | --- | --- | | Resolve | 454.9 | 321.5 | 251.8 | | Maxmargin | 427.6 | 299.6 | 234.4 | | Reach-Maxmargin | 424.4 | 298.3 | 233.5 | | Reach-Maxmargin(notsplit) | 333.4 | 229.4 | 175.5 | | Estimate | 120.6 | 89.43 | 76.44 | | Estimate+Distributional | 119.4 | 87.83 | 74.35 | | Reach-Estimate+Distributional | 116.8 | 85.80 | 72.59 | | Reach-Estimate+Distributional(notsplit) | 113.3 | 83.24 | 70.68 |
1
| TurnHold’emTurnBuckets: | 200 | 2,000 | 20,000 | | --- | --- | --- | --- | | TrunkStrategy | 684.6 | 465.1 | 345.5 |
| Reach-Estimate+Distributional | 10.21 | 5.798 | 2.258 | | --- | --- | --- | --- | | Reach-Estimate+Distributional(notsplit) | 9.560 | 4.924 | 1.733 |
0
| CASE | TASK | CASE | TASK | | --- | --- | --- | --- | | 1 | T1 | 2 | T1 | | 1 | T2 | 2 | T2 | | 1 | T3 | 2 | T3 | | 1 | T4 | 2 | T5 | | 1 | T5 | 2 | T4 | | 1 | T6 | 2 | T7 | | 1 | T7 | 2 | T8 | | 1 | T8 | 2 | T6 | | 1 | T9 | 2 | T10 | | 1 | T10 | 2 | T9 | | 1 | T8’ | 2 | T11 |
| 1 | T11 | 2 | T12 | | --- | --- | --- | --- | | 1 | T9’ | 2 | T14 | | 1 | T12 | 2 | T15 | | 1 | T13 | 2 | T16 | | 1 | T14 | 2 | T17 | | 1 | T15 | 2 | T19 | | 1 | T16 | 2 | T18’ | | 1 | T17 | 2 | T20 | | 1 | T18 | - | - | | 1 | T18’ | - | - | | 1 | T19 | - | - | | 1 | T19’ | - | - | | 1 | T20 | - | - |
1
| CASE | TASK | CASE | TASK | | --- | --- | --- | --- | | 1 | T1 | 2 | T1 | | 1 | T2 | 2 | T2 | | 1 | T3 | 2 | T3 | | 1 | T4 | 2 | T5 | | 1 | T5 | 2 | T4 | | 1 | T6 | 2 | T7 | | 1 | T7 | 2 | T8 | | 1 | T8 | 2 | T6 | | 1 | T9 | 2 | T10 | | 1 | T10 | 2 | T9 | | 1 | T8’ | 2 | T11 |
| | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | a | b | c | d | e | f | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 0 | 00 | 01 | 04 | 0f | 0f | 08 | 02 | 0f | 02 | 04 | 08 | 04 | 01 | 01 | 02 | 08 | | 1 | cf | fa | c4 | fb | 12 | 21 | 10 | 29 | 7c | 4e | 79 | 41 | ad | 99 | a1 | 9f | | 2 | 38 | 58 | 8e | e4 | 93 | f5 | 2c | 40 | 32 | 55 | 8a | e7 | 95 | f4 | 24 | 4f | | 3 | a4 | f0 | 1d | 43 | dd | 8f | 6d | 35 | 1f | 4c | a8 | f1 | 6a | 3f | d4 | 8b | | 4 | a4 | 6a | f1 | 35 | 43 | 8b | 1f | dd | d4 | 1d | 8f | 4c | 3f | f0 | 6d | a8 | | 5 | e2 | 18 | b8 | 48 | d7 | 2b | 84 | 72 | 23 | de | 77 | 80 | 1a | e1 | 47 | b6 | | 6 | b1 | 1e | 56 | f3 | f2 | 5b | 1c | bf | c9 | 61 | 20 | 82 | 86 | 28 | 66 | c2 | | 7 | a4 | 3f | 4c | dd | 35 | a8 | d4 | 43 | 6d | f1 | 8b | 1d | f0 | 6a | 1f | 8f | | 8 | b1 | 28 | 61 | f2 | bf | 20 | 66 | f3 | 1c | 82 | c2 | 56 | 1e | 86 | c9 | 5b | | 9 | 38 | 95 | e7 | 40 | e4 | 4f | 32 | 93 | 24 | 8e | f5 | 55 | f4 | 58 | 2c | 8a | | a | e2 | 1a | 80 | 72 | 48 | b6 | 23 | d7 | 47 | b8 | 2b | de | e1 | 18 | 84 | 77 | | b | 38 | f4 | 55 | 93 | 40 | 8a | 24 | e4 | 2c | e7 | 4f | 8e | 58 | 95 | 32 | f5 | | c | cf | 99 | 4e | 12 | 29 | 79 | a1 | fb | 10 | 41 | 9f | c4 | fa | ad | 7c | 21 | | d | cf | ad | 41 | 29 | fb | 9f | 7c | 12 | a1 | c4 | 21 | 4e | 99 | fa | 10 | 79 | | e | b1 | 86 | 82 | bf | f3 | c2 | c9 | f2 | 66 | 56 | 5b | 61 | 28 | 1e | 1c | 20 | | f | e2 | e1 | de | d7 | 72 | 77 | 47 | 48 | 84 | 80 | b6 | b8 | 18 | 1a | 23 | 2b |
0
| CASE | TASK | CASE | TASK | | --- | --- | --- | --- | | 1 | T1 | 2 | T1 | | 1 | T2 | 2 | T2 | | 1 | T3 | 2 | T3 | | 1 | T4 | 2 | T5 | | 1 | T5 | 2 | T4 | | 1 | T6 | 2 | T7 |
| 1 | T7 | 2 | T8 | | --- | --- | --- | --- | | 1 | T8 | 2 | T6 | | 1 | T9 | 2 | T10 | | 1 | T10 | 2 | T9 | | 1 | T8’ | 2 | T11 | | 1 | T11 | 2 | T12 | | 1 | T9’ | 2 | T14 | | 1 | T12 | 2 | T15 | | 1 | T13 | 2 | T16 | | 1 | T14 | 2 | T17 | | 1 | T15 | 2 | T19 | | 1 | T16 | 2 | T18’ | | 1 | T17 | 2 | T20 | | 1 | T18 | - | - | | 1 | T18’ | - | - | | 1 | T19 | - | - | | 1 | T19’ | - | - | | 1 | T20 | - | - |
1
| CASE | TASK | CASE | TASK | | --- | --- | --- | --- | | 1 | T1 | 2 | T1 | | 1 | T2 | 2 | T2 | | 1 | T3 | 2 | T3 | | 1 | T4 | 2 | T5 | | 1 | T5 | 2 | T4 | | 1 | T6 | 2 | T7 |
| 8 | b1 | 28 | 61 | f2 | bf | 20 | 66 | f3 | 1c | 82 | c2 | 56 | 1e | 86 | c9 | 5b | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 9 | 38 | 95 | e7 | 40 | e4 | 4f | 32 | 93 | 24 | 8e | f5 | 55 | f4 | 58 | 2c | 8a | | a | e2 | 1a | 80 | 72 | 48 | b6 | 23 | d7 | 47 | b8 | 2b | de | e1 | 18 | 84 | 77 | | b | 38 | f4 | 55 | 93 | 40 | 8a | 24 | e4 | 2c | e7 | 4f | 8e | 58 | 95 | 32 | f5 | | c | cf | 99 | 4e | 12 | 29 | 79 | a1 | fb | 10 | 41 | 9f | c4 | fa | ad | 7c | 21 | | d | cf | ad | 41 | 29 | fb | 9f | 7c | 12 | a1 | c4 | 21 | 4e | 99 | fa | 10 | 79 | | e | b1 | 86 | 82 | bf | f3 | c2 | c9 | f2 | 66 | 56 | 5b | 61 | 28 | 1e | 1c | 20 | | f | e2 | e1 | de | d7 | 72 | 77 | 47 | 48 | 84 | 80 | b6 | b8 | 18 | 1a | 23 | 2b |
0
| Notation | Definition | | --- | --- | | L | setoflinks | | L | totalnumberoflinks | | hlk | channelgainfromlinkl’stransmitter<br>tolinkk’sreceiver | | H | linkgainmatrix |
| p(invectorp)l | transmissionpoweroflinkl | | --- | --- | | n(invectorn)l | noisepowerforlinkl | | γl | SINRoflinkl | | γ(·)l | SINRfunctionoflinkl | | U(·)l | utilityfunctionoflinkl | | x(invectorx)l | ratiooflinkl’sutilitytothetotalnetworkutility | | r(invectorr)l | transmissionrateoflinkl | | r(·)l | transmissionratefunctionoflinkl | | α,β | penaltymultipliers |
1
| Notation | Definition | | --- | --- | | L | setoflinks | | L | totalnumberoflinks | | hlk | channelgainfromlinkl’stransmitter<br>tolinkk’sreceiver | | H | linkgainmatrix |
| c | disutilitycostparameters | | --- | --- | | R | reducedload | | S | maximumavailablepowersupply | | L | powerload | | f | maximumlinecapacity | | Hs | generationshiftfactormatrix | | Hl | loadshiftfactormatrix |
0
| Notation | Definition | | --- | --- | | L | setoflinks | | L | totalnumberoflinks | | hlk | channelgainfromlinkl’stransmitter<br>tolinkk’sreceiver | | H | linkgainmatrix | | p(invectorp)l | transmissionpoweroflinkl | | n(invectorn)l | noisepowerforlinkl |
| γl | SINRoflinkl | | --- | --- | | γ(·)l | SINRfunctionoflinkl | | U(·)l | utilityfunctionoflinkl | | x(invectorx)l | ratiooflinkl’sutilitytothetotalnetworkutility | | r(invectorr)l | transmissionrateoflinkl | | r(·)l | transmissionratefunctionoflinkl | | α,β | penaltymultipliers |
1
| Notation | Definition | | --- | --- | | L | setoflinks | | L | totalnumberoflinks | | hlk | channelgainfromlinkl’stransmitter<br>tolinkk’sreceiver | | H | linkgainmatrix | | p(invectorp)l | transmissionpoweroflinkl | | n(invectorn)l | noisepowerforlinkl |
| f | maximumlinecapacity | | --- | --- | | Hs | generationshiftfactormatrix | | Hl | loadshiftfactormatrix |
0
| Dataset | #Datapoints | #Classes | #Features | | --- | --- | --- | --- | | YaleB | 2,414 | 38 | 1,024 | | USPS | 9,298 | 10 | 256 | | COIL100 | 7,200 | 100 | 1,024 |
| Glass | 214 | 6 | 10 | | --- | --- | --- | --- | | Climate | 540 | 2 | 18 | | Ionosphere | 351 | 2 | 34 |
1
| Dataset | #Datapoints | #Classes | #Features | | --- | --- | --- | --- | | YaleB | 2,414 | 38 | 1,024 | | USPS | 9,298 | 10 | 256 | | COIL100 | 7,200 | 100 | 1,024 |
| Dataset | Proposedmethod | LapSc+LRGA | LRGA | LapSc | | --- | --- | --- | --- | --- | | YaleB | 0.7333 | 0.7130 | 0.7091 | 0.7032 | | USPS | 0.8524 | 0.8401 | 0.8365 | 0.8293 | | COIL100 | 0.9070 | 0.8834 | 0.8793 | 0.8637 | | Glass | 0.9666 | 0.9492 | 0.9403 | 0.9216 | | Climate | 0.6097 | 0.5902 | 0.5862 | 0.5821 | | Ionosphere | 0.6946 | 0.6692 | 0.6589 | 0.6362 |
0
| Dataset | #Datapoints | #Classes | #Features | | --- | --- | --- | --- | | YaleB | 2,414 | 38 | 1,024 | | USPS | 9,298 | 10 | 256 | | COIL100 | 7,200 | 100 | 1,024 |
| Glass | 214 | 6 | 10 | | --- | --- | --- | --- | | Climate | 540 | 2 | 18 | | Ionosphere | 351 | 2 | 34 |
1
| Dataset | #Datapoints | #Classes | #Features | | --- | --- | --- | --- | | YaleB | 2,414 | 38 | 1,024 | | USPS | 9,298 | 10 | 256 | | COIL100 | 7,200 | 100 | 1,024 |
| Glass | 0.9666 | 0.9492 | 0.9403 | 0.9216 | | --- | --- | --- | --- | --- | | Climate | 0.6097 | 0.5902 | 0.5862 | 0.5821 | | Ionosphere | 0.6946 | 0.6692 | 0.6589 | 0.6362 |
0
| Image | Method | CSr | | | | --- | --- | --- | --- | --- | | 0.02 | 0.04 | 0.06 | 0.08 | 0.10 |
| Barbara | BM3D-CS<br>TVAL3<br>NLR-CS<br>D-AMP<br>Ours | 16.44,0.389<br>21.32,0.588<br>16.79,0.400<br>15.08,0.354<br>26.15,0.812 | 18.03,0.422<br>22.58,0.620<br>18.90,0.433<br>17.76,0.417<br>27.29,0.835 | 19.70,0.470<br>23.28,0.639<br>20.56,0.501<br>20.44,0.496<br>27.40,0.837 | 21.85,0.561<br>23.78,0.654<br>24.00,0.659<br>22.66,0.623<br>28.05,0.848 | 23.70,0.635<br>24.25,0.667<br>25.13,0.725<br>24.05,0.660<br>28.30,0.852 | | --- | --- | --- | --- | --- | --- | --- | | Boats | BM3D-CS<br>TVAL3<br>NLR-CS<br>D-AMP<br>Ours | 16.76,0.398<br>21.58,0.634<br>17.20,0.409<br>15.52,0.365<br>30.79,0.898 | 17.98,0.440<br>23.66,0.681<br>19.41,0.489<br>18.41,0.456<br>31.73,0.909 | 20.11,0.507<br>24.57,0.699<br>21.76,0.559<br>20.76,0.528<br>31.84,0.910 | 23.21,0.624<br>25.22,0.713<br>23.76,0.638<br>22.85,0.600<br>32.35,0.916 | 24.65,0.687<br>25.75,0.725<br>25.52,0.711<br>25.22,0.703<br>32.33,0.912 | | Cameraman | BM3D-CS<br>TVAL3<br>NLR-CS<br>D-AMP<br>Ours | 16.84,0.432<br>20.33,0.557<br>17.00,0.436<br>16.13,0.401<br>25.88,0.828 | 18.34,0.496<br>21.53,0.579<br>19.10,0.531<br>17.51,0.461<br>26.47,0.829 | 20.62,0.585<br>22.02,0.580<br>21.60,0.620<br>19.84,0.562<br>26.66,0.823 | 22.32,0.654<br>22.37,0.578<br>23.99,0.709<br>21.74,0.629<br>27.16,0.824 | 23.85,0.711<br>23.19,0.688<br>26.25,0.789<br>23.61,0.705<br>27.64,0.819 | | Foreman | BM3D-CS<br>TVAL3<br>NLR-CS<br>D-AMP<br>Ours | 18.96,0.610<br>23.35,0.777<br>19.64,0.645<br>19.42,0.639<br>34.01,0.934 | 21.06,0.680<br>26.81,0.808<br>22.33,0.695<br>22.07,0.687<br>34.61,0.936 | 25.48,0.726<br>28.47,0.821<br>28.09,0.809<br>26.31,0.750<br>35.18,0.937 | 29.80,0.831<br>29.45,0.828<br>31.68,0.865<br>29.12,0.813<br>35.33,0.939 | 31.69,0.866<br>30.02,0.833<br>34.15,0.900<br>31.90,0.872<br>36.02,0.939 | | House | BM3D-CS<br>TVAL3<br>NLR-CS<br>D-AMP<br>Ours | 18.12,0.518<br>22.57,0.706<br>18.80,0.554<br>17.74,0.492<br>30.42,0.873 | 20.35,0.590<br>24.58,0.724<br>21.77,0.620<br>19.93,0.577<br>31.76,0.884 | 25.79,0.755<br>26.36,0.740<br>27.16,0.761<br>24.00,0.693<br>33.07,0.898 | 29.78,0.816<br>27.63,0.766<br>31.23,0.835<br>27.39,0.758<br>34.32,0.910 | 30.50,0.824<br>28.68,0.814<br>33.66,0.869<br>29.84,0.818<br>34.80,0.913 | | Lena | BM3D-CS<br>TVAL3<br>NLR-CS<br>D-AMP<br>Ours | 16.09,0.427<br>21.60,0.671<br>16.71,0.461<br>15.53,0.399<br>28.51,0.881 | 18.22,0.511<br>23.23,0.693<br>19.07,0.545<br>17.21,0.485<br>29.70,0.894 | 20.47,0.603<br>23.88,0.697<br>21.36,0.649<br>19.93,0.567<br>29.85,0.889 | 23.55,0.694<br>24.41,0.701<br>25.47,0.746<br>22.29,0.681<br>30.42,0.898 | 24.63,0.729<br>24.81,0.705<br>25.82,0.771<br>24.60,0.733<br>30.65,0.896 | | Monarch | BM3D-CS<br>TVAL3<br>NLR-CS<br>D-AMP<br>Ours | 14.55,0.352<br>17.31,0.537<br>14.69,0.357<br>14.01,0.334<br>26.14,0.884 | 15.24,0.390<br>18.91,0.577<br>16.03,0.413<br>14.86,0.366<br>27.28,0.895 | 17.65,0.500<br>19.82,0.595<br>18.53,0.552<br>17.55,0.497<br>28.21,0.901 | 19.75,0.581<br>20.56,0.611<br>21.84,0.686<br>19.84,0.587<br>28.97,0.904 | 21.64,0.666<br>21.24,0.624<br>25.12,0.796<br>21.77,0.675<br>29.25,0.904 | | Parrots | BM3D-CS<br>TVAL3<br>NLR-CS<br>D-AMP<br>Ours | 16.62,0.506<br>21.11,0.714<br>17.39,0.550<br>16.89,0.520<br>28.28,0.899 | 19.32,0.613<br>22.90,0.722<br>20.84,0.681<br>19.55,0.619<br>28.88,0.893 | 23.070.693<br>23.47,0.714<br>24.95,0.782<br>22.62,0.684<br>29.22,0.890 | 25.04,0.761<br>24.38,0.770<br>28.18,0.835<br>24.10,0.711<br>29.55,0.887 | 26.10,0.787<br>25.84,0.804<br>30.35,0.875<br>26.31,0.792<br>29.84,0.885 | | Average | BM3D-CS<br>TVAL3<br>NLR-CS<br>D-AMP<br>Ours | 16.80,0.454<br>21.15,0.648<br>17.28,0.477<br>16.29,0.438<br>28.77,0.876 | 18.57,0.518<br>23.02,0.676<br>19.68,0.551<br>18.41,0.509<br>29.71,0.884 | 21.61,0.605<br>23.98,0.685<br>23.00,0.654<br>21.43,0.610<br>30.18,0.886 | 24.42,0.690<br>24.72,0.703<br>26.27,0.747<br>23.75,0.675<br>30.77,0.891 | 25.85,0.738<br>25.47,0.732<br>28.25,0.805<br>25.91,0.745<br>31.10,0.890 |
1
| Image | Method | CSr | | | | --- | --- | --- | --- | --- | | 0.02 | 0.04 | 0.06 | 0.08 | 0.10 |
| | scale | CT-SRCNN-13 | Trim-S1 | Trim-S2 | Trim-S3 | | --- | --- | --- | --- | --- | --- | | Param. | - | 149,344 | 137,424 | 123,600 | 109,776 | | Set5 | 2<br>3<br>4 | 37.61/0.9590/0.019<br>33.76/0.9219/0.019<br>31.49/0.8849/0.020 | 37.61/0.9591/0.018<br>33.77/0.9219/0.018<br>31.49/0.8849/0.018 | 37.60/0.9590/0.016<br>33.75/0.9218/0.016<br>31.49/0.8848/0.017 | 37.59/0.9589/0.015<br>33.74/0.9216/0.014<br>31.48/0.8847/0.017 | | Set14 | 2<br>3<br>4 | 33.37/0.9131/0.032<br>29.91/0.8324/0.034<br>28.20/0.7680/0.032 | 33.38/0.9130/0.030<br>29.90/0.8326/0.031<br>28.20/0.7681/0.029 | 33.36/0.9130/0.028<br>29.89/0.8324/0.028<br>28.19/0.7679/0.027 | 33.36/0.9128/0.025<br>29.88/0.8322/0.026<br>28.18/0.7677/0.025 | | BSD | 2<br>3<br>4 | 31.87/0.8962/0.020<br>28.80/0.7980/0.021<br>27.30/0.7253/0.020 | 31.86/0.8964/0.018<br>28.81/0.7980/0.019<br>27.30/0.7254/0.018 | 31.86/0.8962/0.017<br>28.80/0.7979/0.017<br>27.30/0.7251/0.016 | 31.84/0.8960/0.015<br>28.78/0.7978/0.016<br>27.28/0.7249/0.015 |
0
| Image | Method | CSr | | | | | | --- | --- | --- | --- | --- | --- | --- | | 0.02 | 0.04 | 0.06 | 0.08 | 0.10 | | | | Barbara | BM3D-CS<br>TVAL3<br>NLR-CS<br>D-AMP<br>Ours | 16.44,0.389<br>21.32,0.588<br>16.79,0.400<br>15.08,0.354<br>26.15,0.812 | 18.03,0.422<br>22.58,0.620<br>18.90,0.433<br>17.76,0.417<br>27.29,0.835 | 19.70,0.470<br>23.28,0.639<br>20.56,0.501<br>20.44,0.496<br>27.40,0.837 | 21.85,0.561<br>23.78,0.654<br>24.00,0.659<br>22.66,0.623<br>28.05,0.848 | 23.70,0.635<br>24.25,0.667<br>25.13,0.725<br>24.05,0.660<br>28.30,0.852 | | Boats | BM3D-CS<br>TVAL3<br>NLR-CS<br>D-AMP<br>Ours | 16.76,0.398<br>21.58,0.634<br>17.20,0.409<br>15.52,0.365<br>30.79,0.898 | 17.98,0.440<br>23.66,0.681<br>19.41,0.489<br>18.41,0.456<br>31.73,0.909 | 20.11,0.507<br>24.57,0.699<br>21.76,0.559<br>20.76,0.528<br>31.84,0.910 | 23.21,0.624<br>25.22,0.713<br>23.76,0.638<br>22.85,0.600<br>32.35,0.916 | 24.65,0.687<br>25.75,0.725<br>25.52,0.711<br>25.22,0.703<br>32.33,0.912 | | Cameraman | BM3D-CS<br>TVAL3<br>NLR-CS<br>D-AMP<br>Ours | 16.84,0.432<br>20.33,0.557<br>17.00,0.436<br>16.13,0.401<br>25.88,0.828 | 18.34,0.496<br>21.53,0.579<br>19.10,0.531<br>17.51,0.461<br>26.47,0.829 | 20.62,0.585<br>22.02,0.580<br>21.60,0.620<br>19.84,0.562<br>26.66,0.823 | 22.32,0.654<br>22.37,0.578<br>23.99,0.709<br>21.74,0.629<br>27.16,0.824 | 23.85,0.711<br>23.19,0.688<br>26.25,0.789<br>23.61,0.705<br>27.64,0.819 |
| Foreman | BM3D-CS<br>TVAL3<br>NLR-CS<br>D-AMP<br>Ours | 18.96,0.610<br>23.35,0.777<br>19.64,0.645<br>19.42,0.639<br>34.01,0.934 | 21.06,0.680<br>26.81,0.808<br>22.33,0.695<br>22.07,0.687<br>34.61,0.936 | 25.48,0.726<br>28.47,0.821<br>28.09,0.809<br>26.31,0.750<br>35.18,0.937 | 29.80,0.831<br>29.45,0.828<br>31.68,0.865<br>29.12,0.813<br>35.33,0.939 | 31.69,0.866<br>30.02,0.833<br>34.15,0.900<br>31.90,0.872<br>36.02,0.939 | | --- | --- | --- | --- | --- | --- | --- | | House | BM3D-CS<br>TVAL3<br>NLR-CS<br>D-AMP<br>Ours | 18.12,0.518<br>22.57,0.706<br>18.80,0.554<br>17.74,0.492<br>30.42,0.873 | 20.35,0.590<br>24.58,0.724<br>21.77,0.620<br>19.93,0.577<br>31.76,0.884 | 25.79,0.755<br>26.36,0.740<br>27.16,0.761<br>24.00,0.693<br>33.07,0.898 | 29.78,0.816<br>27.63,0.766<br>31.23,0.835<br>27.39,0.758<br>34.32,0.910 | 30.50,0.824<br>28.68,0.814<br>33.66,0.869<br>29.84,0.818<br>34.80,0.913 | | Lena | BM3D-CS<br>TVAL3<br>NLR-CS<br>D-AMP<br>Ours | 16.09,0.427<br>21.60,0.671<br>16.71,0.461<br>15.53,0.399<br>28.51,0.881 | 18.22,0.511<br>23.23,0.693<br>19.07,0.545<br>17.21,0.485<br>29.70,0.894 | 20.47,0.603<br>23.88,0.697<br>21.36,0.649<br>19.93,0.567<br>29.85,0.889 | 23.55,0.694<br>24.41,0.701<br>25.47,0.746<br>22.29,0.681<br>30.42,0.898 | 24.63,0.729<br>24.81,0.705<br>25.82,0.771<br>24.60,0.733<br>30.65,0.896 | | Monarch | BM3D-CS<br>TVAL3<br>NLR-CS<br>D-AMP<br>Ours | 14.55,0.352<br>17.31,0.537<br>14.69,0.357<br>14.01,0.334<br>26.14,0.884 | 15.24,0.390<br>18.91,0.577<br>16.03,0.413<br>14.86,0.366<br>27.28,0.895 | 17.65,0.500<br>19.82,0.595<br>18.53,0.552<br>17.55,0.497<br>28.21,0.901 | 19.75,0.581<br>20.56,0.611<br>21.84,0.686<br>19.84,0.587<br>28.97,0.904 | 21.64,0.666<br>21.24,0.624<br>25.12,0.796<br>21.77,0.675<br>29.25,0.904 | | Parrots | BM3D-CS<br>TVAL3<br>NLR-CS<br>D-AMP<br>Ours | 16.62,0.506<br>21.11,0.714<br>17.39,0.550<br>16.89,0.520<br>28.28,0.899 | 19.32,0.613<br>22.90,0.722<br>20.84,0.681<br>19.55,0.619<br>28.88,0.893 | 23.070.693<br>23.47,0.714<br>24.95,0.782<br>22.62,0.684<br>29.22,0.890 | 25.04,0.761<br>24.38,0.770<br>28.18,0.835<br>24.10,0.711<br>29.55,0.887 | 26.10,0.787<br>25.84,0.804<br>30.35,0.875<br>26.31,0.792<br>29.84,0.885 | | Average | BM3D-CS<br>TVAL3<br>NLR-CS<br>D-AMP<br>Ours | 16.80,0.454<br>21.15,0.648<br>17.28,0.477<br>16.29,0.438<br>28.77,0.876 | 18.57,0.518<br>23.02,0.676<br>19.68,0.551<br>18.41,0.509<br>29.71,0.884 | 21.61,0.605<br>23.98,0.685<br>23.00,0.654<br>21.43,0.610<br>30.18,0.886 | 24.42,0.690<br>24.72,0.703<br>26.27,0.747<br>23.75,0.675<br>30.77,0.891 | 25.85,0.738<br>25.47,0.732<br>28.25,0.805<br>25.91,0.745<br>31.10,0.890 |
1
| Image | Method | CSr | | | | | | --- | --- | --- | --- | --- | --- | --- | | 0.02 | 0.04 | 0.06 | 0.08 | 0.10 | | | | Barbara | BM3D-CS<br>TVAL3<br>NLR-CS<br>D-AMP<br>Ours | 16.44,0.389<br>21.32,0.588<br>16.79,0.400<br>15.08,0.354<br>26.15,0.812 | 18.03,0.422<br>22.58,0.620<br>18.90,0.433<br>17.76,0.417<br>27.29,0.835 | 19.70,0.470<br>23.28,0.639<br>20.56,0.501<br>20.44,0.496<br>27.40,0.837 | 21.85,0.561<br>23.78,0.654<br>24.00,0.659<br>22.66,0.623<br>28.05,0.848 | 23.70,0.635<br>24.25,0.667<br>25.13,0.725<br>24.05,0.660<br>28.30,0.852 | | Boats | BM3D-CS<br>TVAL3<br>NLR-CS<br>D-AMP<br>Ours | 16.76,0.398<br>21.58,0.634<br>17.20,0.409<br>15.52,0.365<br>30.79,0.898 | 17.98,0.440<br>23.66,0.681<br>19.41,0.489<br>18.41,0.456<br>31.73,0.909 | 20.11,0.507<br>24.57,0.699<br>21.76,0.559<br>20.76,0.528<br>31.84,0.910 | 23.21,0.624<br>25.22,0.713<br>23.76,0.638<br>22.85,0.600<br>32.35,0.916 | 24.65,0.687<br>25.75,0.725<br>25.52,0.711<br>25.22,0.703<br>32.33,0.912 | | Cameraman | BM3D-CS<br>TVAL3<br>NLR-CS<br>D-AMP<br>Ours | 16.84,0.432<br>20.33,0.557<br>17.00,0.436<br>16.13,0.401<br>25.88,0.828 | 18.34,0.496<br>21.53,0.579<br>19.10,0.531<br>17.51,0.461<br>26.47,0.829 | 20.62,0.585<br>22.02,0.580<br>21.60,0.620<br>19.84,0.562<br>26.66,0.823 | 22.32,0.654<br>22.37,0.578<br>23.99,0.709<br>21.74,0.629<br>27.16,0.824 | 23.85,0.711<br>23.19,0.688<br>26.25,0.789<br>23.61,0.705<br>27.64,0.819 |
| Set5 | 2<br>3<br>4 | 37.61/0.9590/0.019<br>33.76/0.9219/0.019<br>31.49/0.8849/0.020 | 37.61/0.9591/0.018<br>33.77/0.9219/0.018<br>31.49/0.8849/0.018 | 37.60/0.9590/0.016<br>33.75/0.9218/0.016<br>31.49/0.8848/0.017 | 37.59/0.9589/0.015<br>33.74/0.9216/0.014<br>31.48/0.8847/0.017 | | --- | --- | --- | --- | --- | --- | | Set14 | 2<br>3<br>4 | 33.37/0.9131/0.032<br>29.91/0.8324/0.034<br>28.20/0.7680/0.032 | 33.38/0.9130/0.030<br>29.90/0.8326/0.031<br>28.20/0.7681/0.029 | 33.36/0.9130/0.028<br>29.89/0.8324/0.028<br>28.19/0.7679/0.027 | 33.36/0.9128/0.025<br>29.88/0.8322/0.026<br>28.18/0.7677/0.025 | | BSD | 2<br>3<br>4 | 31.87/0.8962/0.020<br>28.80/0.7980/0.021<br>27.30/0.7253/0.020 | 31.86/0.8964/0.018<br>28.81/0.7980/0.019<br>27.30/0.7254/0.018 | 31.86/0.8962/0.017<br>28.80/0.7979/0.017<br>27.30/0.7251/0.016 | 31.84/0.8960/0.015<br>28.78/0.7978/0.016<br>27.28/0.7249/0.015 |
0
| Stride | -Difficulty | +Difficulty | | --- | --- | --- | | 1 | 0.77 | 0.86 |
| 2 | 0.77 | 0.86 | | --- | --- | --- | | 4 | 0.78 | 0.86 | | 8 | 0.75 | 0.81 | | 16 | 0.74 | 0.80 |
1
| Stride | -Difficulty | +Difficulty | | --- | --- | --- | | 1 | 0.77 | 0.86 |
| 0∼10px | | --- | | PRH | | 0.120.100.11 | | 0.170.190.18 | | 0.630.570.60 |
0
| Stride | -Difficulty | +Difficulty | | --- | --- | --- | | 1 | 0.77 | 0.86 | | 2 | 0.77 | 0.86 | | 4 | 0.78 | 0.86 |
| 8 | 0.75 | 0.81 | | --- | --- | --- | | 16 | 0.74 | 0.80 |
1
| Stride | -Difficulty | +Difficulty | | --- | --- | --- | | 1 | 0.77 | 0.86 | | 2 | 0.77 | 0.86 | | 4 | 0.78 | 0.86 |
| 0.170.190.18 | | --- | | 0.630.570.60 |
0
| English→Germantask | BLEU | German→Englishtask | BLEU | | --- | --- | --- | --- | | Existingend-to-endsystem | | | | | RNNSearch-LV<br>MRT<br>Global-att<br>GNMT | 19.40<br>20.45<br>20.90<br>24.61 | BSO<br>NMPT<br>NMPT+LM<br>ActorCritic | 26.36<br>28.96<br>29.16<br>28.53 |
| Ourend-to-endsystem | | | | | --- | --- | --- | --- | | Baseline<br>SharpenedSigmoid<br>2<br>G-LSTM | 21.89<br>21.64<br>22.43 | -<br>-<br>- | 31.00<br>29.73<br>31.95 |
1
| English→Germantask | BLEU | German→Englishtask | BLEU | | --- | --- | --- | --- | | Existingend-to-endsystem | | | | | RNNSearch-LV<br>MRT<br>Global-att<br>GNMT | 19.40<br>20.45<br>20.90<br>24.61 | BSO<br>NMPT<br>NMPT+LM<br>ActorCritic | 26.36<br>28.96<br>29.16<br>28.53 |
| Captions | IToC<br>Recall@5Recall@10Recall@50 | | --- | --- | | English | 0.1180.1900.456 | | French<br>French<br>French<br>French | 0.0080.0170.069<br>0.0180.0240.085<br>0.0720.1350.335<br>0.1010.1630.414 | | German<br>German<br>German<br>German | 0.0050.0090.053<br>0.0090.0130.071<br>0.0630.1050.298<br>0.0840.1630.420 | | | 0.0060.0090.044 |
0
| English→Germantask | BLEU | German→Englishtask | BLEU | | --- | --- | --- | --- | | Existingend-to-endsystem | | | |
| RNNSearch-LV<br>MRT<br>Global-att<br>GNMT | 19.40<br>20.45<br>20.90<br>24.61 | BSO<br>NMPT<br>NMPT+LM<br>ActorCritic | 26.36<br>28.96<br>29.16<br>28.53 | | --- | --- | --- | --- | | Ourend-to-endsystem | | | | | Baseline<br>SharpenedSigmoid<br>2<br>G-LSTM | 21.89<br>21.64<br>22.43 | -<br>-<br>- | 31.00<br>29.73<br>31.95 |
1
| English→Germantask | BLEU | German→Englishtask | BLEU | | --- | --- | --- | --- | | Existingend-to-endsystem | | | |
| German<br>German<br>German<br>German | 0.0050.0090.053<br>0.0090.0130.071<br>0.0630.1050.298<br>0.0840.1630.420 | | --- | --- | | | 0.0060.0090.044 |
0
| α | G | Capacity | Bandwidth | γ(α)c | | --- | --- | --- | --- | --- | | 0.125 | 2 | 1.14 | 8.56 | 0.133 | | 0.25 | 4 | 1.01 | 9.51 | 0.106 | | 0.375 | 5 | 0.96 | 10.46 | 0.091 | | 0.5 | 7 | 0.92 | 11.42 | 0.081 | | 0.625 | 8 | 0.90 | 12.37 | 0.073 | | 0.75 | 9 | 0.89 | 13.32 | 0.067 |
| 0.875 | 11 | 0.88 | 14.27 | 0.061 | | --- | --- | --- | --- | --- | | 1 | 12 | 0.87 | 15.22 | 0.057 |
1
| α | G | Capacity | Bandwidth | γ(α)c | | --- | --- | --- | --- | --- | | 0.125 | 2 | 1.14 | 8.56 | 0.133 | | 0.25 | 4 | 1.01 | 9.51 | 0.106 | | 0.375 | 5 | 0.96 | 10.46 | 0.091 | | 0.5 | 7 | 0.92 | 11.42 | 0.081 | | 0.625 | 8 | 0.90 | 12.37 | 0.073 | | 0.75 | 9 | 0.89 | 13.32 | 0.067 |
| K | PCA | NMF | SNMF | SSC | LRR | MFC10 | MFC20 | | --- | --- | --- | --- | --- | --- | --- | --- | | 2 | 0.51 | 0.80 | 1.00 | 0.98 | 1.00 | 1.00 | 1.00 | | 4 | 0.35 | 0.59 | 0.63 | 0.88 | 0.86 | 0.85 | 0.89 | | 6 | 0.30 | 0.72 | 0.57 | 0.84 | 0.82 | 0.84 | 0.86 | | 8 | 0.20 | 0.37 | 0.48 | 0.76 | 0.74 | 0.69 | 0.76 | | 10 | 0.23 | 0.45 | 0.41 | 0.74 | 0.71 | 0.68 | 0.75 | | 12 | 0.22 | 0.37 | 0.41 | 0.67 | 0.70 | 0.70 | 0.70 | | 14 | 0.18 | 0.36 | 0.39 | 0.64 | 0.68 | 0.77 | 0.72 | | 16 | 0.18 | 0.37 | 0.39 | 0.63 | 0.67 | 0.72 | 0.73 | | 18 | 0.15 | 0.35 | 0.35 | 0.63 | 0.68 | 0.74 | 0.74 | | 20 | 0.15 | 0.37 | 0.37 | 0.60 | 0.66 | 0.72 | 0.72 | | Avg. | 0.25 | 0.47 | 0.49 | 0.74 | 0.75 | 0.77 | 0.79 |
0
| α | G | Capacity | Bandwidth | γ(α)c | | --- | --- | --- | --- | --- | | 0.125 | 2 | 1.14 | 8.56 | 0.133 | | 0.25 | 4 | 1.01 | 9.51 | 0.106 | | 0.375 | 5 | 0.96 | 10.46 | 0.091 | | 0.5 | 7 | 0.92 | 11.42 | 0.081 | | 0.625 | 8 | 0.90 | 12.37 | 0.073 | | 0.75 | 9 | 0.89 | 13.32 | 0.067 |
| 0.875 | 11 | 0.88 | 14.27 | 0.061 | | --- | --- | --- | --- | --- | | 1 | 12 | 0.87 | 15.22 | 0.057 |
1
| α | G | Capacity | Bandwidth | γ(α)c | | --- | --- | --- | --- | --- | | 0.125 | 2 | 1.14 | 8.56 | 0.133 | | 0.25 | 4 | 1.01 | 9.51 | 0.106 | | 0.375 | 5 | 0.96 | 10.46 | 0.091 | | 0.5 | 7 | 0.92 | 11.42 | 0.081 | | 0.625 | 8 | 0.90 | 12.37 | 0.073 | | 0.75 | 9 | 0.89 | 13.32 | 0.067 |
| 18 | 0.15 | 0.35 | 0.35 | 0.63 | 0.68 | 0.74 | 0.74 | | --- | --- | --- | --- | --- | --- | --- | --- | | 20 | 0.15 | 0.37 | 0.37 | 0.60 | 0.66 | 0.72 | 0.72 | | Avg. | 0.25 | 0.47 | 0.49 | 0.74 | 0.75 | 0.77 | 0.79 |
0
| | Performance | RocAuc | F1 | | | | | --- | --- | --- | --- | --- | --- | --- | | Classifier | mean | std | mean | std | mean | std | | LogisticRegression | 0.7500 | 0.2738 | 0.7000 | 0.4153 | 0.6166 | 0.4349 | | LDA | 0.6750 | 0.2968 | 0.7000 | 0.4153 | 0.6066 | 0.4103 | | SVC | 0.6500 | 0.3000 | 0.7000 | 0.4153 | 0.5766 | 0.4060 | | GaussianNB | 0.6500 | 0.3000 | 0.6750 | 0.4038 | 0.5766 | 0.4060 | | DecisionTreeClassifier | 0.5500 | 0.2915 | 0.5250 | 0.2610 | 0.5533 | 0.3357 | | GradientBoostingClassifier | 0.5750 | 0.2750 | 0.6375 | 0.2589 | 0.5266 | 0.3362 | | BaggingClassifier | 0.5750 | 0.1600 | 0.5875 | 0.2907 | 0.5066 | 0.2950 |
| KNeighborsClassifier | 0.5500 | 0.1500 | 0.5500 | 0.1500 | 0.4300 | 0.2956 | | --- | --- | --- | --- | --- | --- | --- | | RandomForestClassifier | 0.5000 | 0.2500 | 0.6000 | 0.3570 | 0.4833 | 0.2833 |
1
| | Performance | RocAuc | F1 | | | | | --- | --- | --- | --- | --- | --- | --- | | Classifier | mean | std | mean | std | mean | std | | LogisticRegression | 0.7500 | 0.2738 | 0.7000 | 0.4153 | 0.6166 | 0.4349 | | LDA | 0.6750 | 0.2968 | 0.7000 | 0.4153 | 0.6066 | 0.4103 | | SVC | 0.6500 | 0.3000 | 0.7000 | 0.4153 | 0.5766 | 0.4060 | | GaussianNB | 0.6500 | 0.3000 | 0.6750 | 0.4038 | 0.5766 | 0.4060 | | DecisionTreeClassifier | 0.5500 | 0.2915 | 0.5250 | 0.2610 | 0.5533 | 0.3357 | | GradientBoostingClassifier | 0.5750 | 0.2750 | 0.6375 | 0.2589 | 0.5266 | 0.3362 | | BaggingClassifier | 0.5750 | 0.1600 | 0.5875 | 0.2907 | 0.5066 | 0.2950 |
| | NSL-KDD | UNSW-NB15 | | | | | | --- | --- | --- | --- | --- | --- | --- | | ACC | PPV | TPR | ACC | PPV | TPR | | | DecisionTree | 87.91 | 63.62 | 68.50 | 93.78 | 76.42 | 68.92 | | K-means | 82.78 | 84.96 | 56.95 | 87.05 | 74.01 | 35.23 | | KNeighboursClassifier | 88.56 | 77.19 | 71.39 | 94.31 | 77.42 | 71.52 | | LogisticRegression | 89.52 | 62.04 | 73.79 | 92.52 | 71.05 | 62.61 | | MultilayerPerceptron(MLP) | 87.91 | 63.62 | 68.5 | 90.16 | 76.72 | 75.39 | | GaussianNaiveBayes | 88.33 | 73.98 | 41.67 | 88.34 | 73.98 | 41.67 | | MultinomialNaiveBayes | 83.96 | 65.52 | 59.90 | 90.97 | 55.40 | 54.86 | | BernoulliNaiveBayes | 74.60 | 87.47 | 36.49 | 91.31 | 55.07 | 56.52 | | RandomForestClassifier | 88.39 | 71.21 | 70.99 | 94.44 | 80.29 | 72.21 | | SupportVectorMachine(SVM) | 88.32 | 64.70 | 70.80 | 93.38 | 76.91 | 66.90 | | OurProposedDeepLearningApproach | 90.99 | 81.95 | 77.48 | 95.84 | 83.40 | 79.19 |
0
| | Performance | RocAuc | F1 | | | | | --- | --- | --- | --- | --- | --- | --- | | Classifier | mean | std | mean | std | mean | std |
| LogisticRegression | 0.7500 | 0.2738 | 0.7000 | 0.4153 | 0.6166 | 0.4349 | | --- | --- | --- | --- | --- | --- | --- | | LDA | 0.6750 | 0.2968 | 0.7000 | 0.4153 | 0.6066 | 0.4103 | | SVC | 0.6500 | 0.3000 | 0.7000 | 0.4153 | 0.5766 | 0.4060 | | GaussianNB | 0.6500 | 0.3000 | 0.6750 | 0.4038 | 0.5766 | 0.4060 | | DecisionTreeClassifier | 0.5500 | 0.2915 | 0.5250 | 0.2610 | 0.5533 | 0.3357 | | GradientBoostingClassifier | 0.5750 | 0.2750 | 0.6375 | 0.2589 | 0.5266 | 0.3362 | | BaggingClassifier | 0.5750 | 0.1600 | 0.5875 | 0.2907 | 0.5066 | 0.2950 | | KNeighborsClassifier | 0.5500 | 0.1500 | 0.5500 | 0.1500 | 0.4300 | 0.2956 | | RandomForestClassifier | 0.5000 | 0.2500 | 0.6000 | 0.3570 | 0.4833 | 0.2833 |
1
| | Performance | RocAuc | F1 | | | | | --- | --- | --- | --- | --- | --- | --- | | Classifier | mean | std | mean | std | mean | std |
| K-means | 82.78 | 84.96 | 56.95 | 87.05 | 74.01 | 35.23 | | --- | --- | --- | --- | --- | --- | --- | | KNeighboursClassifier | 88.56 | 77.19 | 71.39 | 94.31 | 77.42 | 71.52 | | LogisticRegression | 89.52 | 62.04 | 73.79 | 92.52 | 71.05 | 62.61 | | MultilayerPerceptron(MLP) | 87.91 | 63.62 | 68.5 | 90.16 | 76.72 | 75.39 | | GaussianNaiveBayes | 88.33 | 73.98 | 41.67 | 88.34 | 73.98 | 41.67 | | MultinomialNaiveBayes | 83.96 | 65.52 | 59.90 | 90.97 | 55.40 | 54.86 | | BernoulliNaiveBayes | 74.60 | 87.47 | 36.49 | 91.31 | 55.07 | 56.52 | | RandomForestClassifier | 88.39 | 71.21 | 70.99 | 94.44 | 80.29 | 72.21 | | SupportVectorMachine(SVM) | 88.32 | 64.70 | 70.80 | 93.38 | 76.91 | 66.90 | | OurProposedDeepLearningApproach | 90.99 | 81.95 | 77.48 | 95.84 | 83.40 | 79.19 |
0
| input(1,96,1360) | | | --- | --- | | Conv2dandMax-Pooling | (32,(3,3))and(2,4) | | Batchnormalization-ELUactivation | | | Conv2dandMax-Pooling | (32,(3,3))and(4,4) | | Batchnormalization-ELUactivation | | | Conv2dandMax-Pooling | (32,(3,3))and(4,5) |
| Batchnormalization-ELUactivation | | | --- | --- | | Conv2dandMax-Pooling | (32,(3,3))and(2,4) | | Batchnormalization-ELUactivation | | | Conv2dandMax-Pooling | (32,(3,3))and(4,4) | | Batchnormalization-ELUactivation | | | Fully-connectedlayer | (50) | | output(50) | |
1
| input(1,96,1360) | | | --- | --- | | Conv2dandMax-Pooling | (32,(3,3))and(2,4) | | Batchnormalization-ELUactivation | | | Conv2dandMax-Pooling | (32,(3,3))and(4,4) | | Batchnormalization-ELUactivation | | | Conv2dandMax-Pooling | (32,(3,3))and(4,5) |
| input(1,96,1360) | | | --- | --- | | Conv2dandMax-Pooling | (32,(3,3))and(2,4) | | Conv2dandMax-Pooling | (32,(3,3))and(4,4) | | Conv2dandMax-Pooling | (32,(3,3))and(4,5) | | Conv2dandMax-Pooling | (32,(3,3))and(2,4) | | Conv2dandMax-Pooling | (32,(3,3))and(4,4) | | Fully-connectedlayer | (50) | | output(50) | |
0
| input(1,96,1360) | | | --- | --- | | Conv2dandMax-Pooling | (32,(3,3))and(2,4) | | Batchnormalization-ELUactivation | | | Conv2dandMax-Pooling | (32,(3,3))and(4,4) | | Batchnormalization-ELUactivation | |
| Conv2dandMax-Pooling | (32,(3,3))and(4,5) | | --- | --- | | Batchnormalization-ELUactivation | | | Conv2dandMax-Pooling | (32,(3,3))and(2,4) | | Batchnormalization-ELUactivation | | | Conv2dandMax-Pooling | (32,(3,3))and(4,4) | | Batchnormalization-ELUactivation | | | Fully-connectedlayer | (50) | | output(50) | |
1
| input(1,96,1360) | | | --- | --- | | Conv2dandMax-Pooling | (32,(3,3))and(2,4) | | Batchnormalization-ELUactivation | | | Conv2dandMax-Pooling | (32,(3,3))and(4,4) | | Batchnormalization-ELUactivation | |
| Conv2dandMax-Pooling | (32,(3,3))and(4,4) | | --- | --- | | Fully-connectedlayer | (50) | | output(50) | |
0
| | Nodes | Leaves | Levels | | --- | --- | --- | --- | | IGTree | 865 | 433 | 33 | | BS-tree | 719 | 360 | 86 | | C4.5 | 339 | 170 | 26 |
| BD-tree | 451 | 226 | 52 | | --- | --- | --- | --- | | SE-tree | 559 | 209 | 8 |
1
| | Nodes | Leaves | Levels | | --- | --- | --- | --- | | IGTree | 865 | 433 | 33 | | BS-tree | 719 | 360 | 86 | | C4.5 | 339 | 170 | 26 |
| p | tree | RRGnumerics | | --- | --- | --- | | 0.5 | 4.16 | 4.36±0.03 | | 0.45 | 4.22 | 4.45±0.05 | | 0.4 | 4.53 | 4.75±0.05 | | 0.35 | 5.13 | 5.30±0.05 | | 0.3 | 6.16 | 6.28±0.05 |
0
| | Nodes | Leaves | Levels | | --- | --- | --- | --- | | IGTree | 865 | 433 | 33 |
| BS-tree | 719 | 360 | 86 | | --- | --- | --- | --- | | C4.5 | 339 | 170 | 26 | | BD-tree | 451 | 226 | 52 | | SE-tree | 559 | 209 | 8 |
1
| | Nodes | Leaves | Levels | | --- | --- | --- | --- | | IGTree | 865 | 433 | 33 |
| 0.4 | 4.53 | 4.75±0.05 | | --- | --- | --- | | 0.35 | 5.13 | 5.30±0.05 | | 0.3 | 6.16 | 6.28±0.05 |
0
| MetricMaltParserStanfordRNNparserTurboParserYaraParser | | --- | | LAS88.3588.7791.3691.844321<br>UAS90.2790.4793.2993.344321<br>LA93.0193.5995.0295.724321 | | P(acomp)88.6688.3188.7591.033421<br>R(acomp)90.2989.2491.0893.183421 | | P(advmod)83.1882.3884.9685.853421<br>R(advmod)84.0481.9785.4685.223412 | | P(amod)95.4595.0196.2596.233412<br>R(amod)95.4595.4096.3096.603421 | | P(attr)87.1786.0089.0094.883421<br>R(attr)88.6386.2991.9792.983421 | | P(cc)77.0677.6883.5683.464312<br>R(cc)76.9577.0283.8283.974321 |
| P(mark)83.4484.2185.1588.474321<br>R(mark)83.4488.3190.2692.214321 | | --- | | P(neg)92.9992.6294.7792.682413<br>R(neg)94.7293.4895.6594.412413 | | P(nmod)80.6682.1784.4585.384321<br>R(nmod)79.6778.6679.4780.692431 |
1
| MetricMaltParserStanfordRNNparserTurboParserYaraParser | | --- | | LAS88.3588.7791.3691.844321<br>UAS90.2790.4793.2993.344321<br>LA93.0193.5995.0295.724321 | | P(acomp)88.6688.3188.7591.033421<br>R(acomp)90.2989.2491.0893.183421 | | P(advmod)83.1882.3884.9685.853421<br>R(advmod)84.0481.9785.4685.223412 | | P(amod)95.4595.0196.2596.233412<br>R(amod)95.4595.4096.3096.603421 | | P(attr)87.1786.0089.0094.883421<br>R(attr)88.6386.2991.9792.983421 | | P(cc)77.0677.6883.5683.464312<br>R(cc)76.9577.0283.8283.974321 |
| MRCRSUBJMPQATREC | MSRP(Acc/F1) | | --- | --- | | 71.578.490.183.485.2<br>71.979.390.885.288.8<br>73.680.291.485.789.0 | 72.1/81.7<br>72.8/81.5<br>73.5/82.1 | | 72.177.890.584.286.0<br>72.979.390.685.287.6<br>74.080.491.586.187.8 | 71.5/80.8<br>72.9/81.6<br>73.7/81.7 | | 70.875.990.482.787.2<br>71.178.490.883.789.6<br>72.478.691.584.388.7 | 73.3/81.7<br>73.2/81.7<br>75.4/83.0 | | 68.476.589.481.481.6<br>70.076.489.681.486.0<br>71.678.090.783.283.2 | 72.2/81.4<br>72.8/81.4<br>73.2/81.4 | | 73.380.090.784.984.8<br>75.080.591.186.587.4<br>75.881.891.986.888.6 | 73.8/81.9<br>72.3/81.3<br>75.0/82.5 |
0
| MetricMaltParserStanfordRNNparserTurboParserYaraParser | | --- | | LAS88.3588.7791.3691.844321<br>UAS90.2790.4793.2993.344321<br>LA93.0193.5995.0295.724321 | | P(acomp)88.6688.3188.7591.033421<br>R(acomp)90.2989.2491.0893.183421 | | P(advmod)83.1882.3884.9685.853421<br>R(advmod)84.0481.9785.4685.223412 | | P(amod)95.4595.0196.2596.233412<br>R(amod)95.4595.4096.3096.603421 | | P(attr)87.1786.0089.0094.883421<br>R(attr)88.6386.2991.9792.983421 |
| P(cc)77.0677.6883.5683.464312<br>R(cc)76.9577.0283.8283.974321 | | --- | | P(mark)83.4484.2185.1588.474321<br>R(mark)83.4488.3190.2692.214321 | | P(neg)92.9992.6294.7792.682413<br>R(neg)94.7293.4895.6594.412413 | | P(nmod)80.6682.1784.4585.384321<br>R(nmod)79.6778.6679.4780.692431 |
1
| MetricMaltParserStanfordRNNparserTurboParserYaraParser | | --- | | LAS88.3588.7791.3691.844321<br>UAS90.2790.4793.2993.344321<br>LA93.0193.5995.0295.724321 | | P(acomp)88.6688.3188.7591.033421<br>R(acomp)90.2989.2491.0893.183421 | | P(advmod)83.1882.3884.9685.853421<br>R(advmod)84.0481.9785.4685.223412 | | P(amod)95.4595.0196.2596.233412<br>R(amod)95.4595.4096.3096.603421 | | P(attr)87.1786.0089.0094.883421<br>R(attr)88.6386.2991.9792.983421 |
| 70.875.990.482.787.2<br>71.178.490.883.789.6<br>72.478.691.584.388.7 | 73.3/81.7<br>73.2/81.7<br>75.4/83.0 | | --- | --- | | 68.476.589.481.481.6<br>70.076.489.681.486.0<br>71.678.090.783.283.2 | 72.2/81.4<br>72.8/81.4<br>73.2/81.4 | | 73.380.090.784.984.8<br>75.080.591.186.587.4<br>75.881.891.986.888.6 | 73.8/81.9<br>72.3/81.3<br>75.0/82.5 |
0
| Layer | Support | Filtdim. | #filts. | Stride | Datasize | | --- | --- | --- | --- | --- | --- | | conv1 | 3×3 | 5 | 96 | 1×1 | 109×109 | | pool1 | 3×3 | - | - | 2×2 | 54×54 | | conv2 | 3×3 | 96 | 256 | 2×2 | 27×27 | | pool2 | 3×3 | - | - | 2×2 | 13×13 |
| conv3 | 3×3 | 256 | 512 | 1×1 | 13×13 | | --- | --- | --- | --- | --- | --- | | conv4 | 3×3 | 512 | 512 | 1×1 | 13×13 | | conv5 | 3×3 | 512 | 512 | 1×1 | 13×13 | | pool5 | 3×3 | - | - | 2×2 | 6×6 | | fc6 | 6×6 | 512 | 512 | - | 1×1 |
1
| Layer | Support | Filtdim. | #filts. | Stride | Datasize | | --- | --- | --- | --- | --- | --- | | conv1 | 3×3 | 5 | 96 | 1×1 | 109×109 | | pool1 | 3×3 | - | - | 2×2 | 54×54 | | conv2 | 3×3 | 96 | 256 | 2×2 | 27×27 | | pool2 | 3×3 | - | - | 2×2 | 13×13 |
| Layer | Filter/Stride | #Channel | #Filter | | --- | --- | --- | --- | | Conv11 | 3×3/1 | 1 | 32 | | Conv12 | 3×3/1 | 32 | 64 | | MaxPool | 2×2/2 | 64 | – | | Conv21 | 3×3/1 | 64 | 64 | | Conv22 | 3×3/1 | 64 | 128 | | MaxPool | 2×2/2 | 128 | – | | Conv31 | 3×3/1 | 128 | 96 | | Conv32 | 3×3/1 | 96 | 192 | | MaxPool | 2×2/2 | 192 | – | | Conv41 | 3×3/1 | 192 | 128 | | Conv42 | 3×3/1 | 128 | 256 | | MaxPool | 2×2/2 | 256 | – | | Conv51 | 3×3/1 | 256 | 160 | | Conv52 | 3×3/1 | 160 | 320 | | AvgPool | 6×6/1 | 320 | – | | Dropout1-0.3 | – | – | – | | FC | 1×320/1 | 320 | 100 |
0
| Layer | Support | Filtdim. | #filts. | Stride | Datasize | | --- | --- | --- | --- | --- | --- | | conv1 | 3×3 | 5 | 96 | 1×1 | 109×109 | | pool1 | 3×3 | - | - | 2×2 | 54×54 | | conv2 | 3×3 | 96 | 256 | 2×2 | 27×27 | | pool2 | 3×3 | - | - | 2×2 | 13×13 | | conv3 | 3×3 | 256 | 512 | 1×1 | 13×13 |
| conv4 | 3×3 | 512 | 512 | 1×1 | 13×13 | | --- | --- | --- | --- | --- | --- | | conv5 | 3×3 | 512 | 512 | 1×1 | 13×13 | | pool5 | 3×3 | - | - | 2×2 | 6×6 | | fc6 | 6×6 | 512 | 512 | - | 1×1 |
1
| Layer | Support | Filtdim. | #filts. | Stride | Datasize | | --- | --- | --- | --- | --- | --- | | conv1 | 3×3 | 5 | 96 | 1×1 | 109×109 | | pool1 | 3×3 | - | - | 2×2 | 54×54 | | conv2 | 3×3 | 96 | 256 | 2×2 | 27×27 | | pool2 | 3×3 | - | - | 2×2 | 13×13 | | conv3 | 3×3 | 256 | 512 | 1×1 | 13×13 |
| Conv41 | 3×3/1 | 192 | 128 | | --- | --- | --- | --- | | Conv42 | 3×3/1 | 128 | 256 | | MaxPool | 2×2/2 | 256 | – | | Conv51 | 3×3/1 | 256 | 160 | | Conv52 | 3×3/1 | 160 | 320 | | AvgPool | 6×6/1 | 320 | – | | Dropout1-0.3 | – | – | – | | FC | 1×320/1 | 320 | 100 |
0
| Usecase | | --- | | DefaultPartitioningProblem | | CheckingGraphforCorrectness<br>EvaluatePartitioningMetrics<br>FastSequentialPartitioning,Mesh<br>GoodSequentialPartitioning,Mesh<br>VeryGoodSequentialPartitioning,Mesh | | FastSequentialPartitioning,Social<br>GoodSequentialPartitioning,Social<br>VeryGoodSequentialPartitioning,Social |
| MappingtoProcessorNetworks | | --- | | HighestQuality,Mesh<br>HighestQuality,Social | | ParallelPartitioning | | DistributedMemoryParallel,Mesh<br>DistributedMemoryParallel,Social<br>ConvertMetistoBinary<br>EvaluateandConvertPartitions | | NodeSeparators | | TwoNodeSeparators<br>k-waySeparators |
1
| Usecase | | --- | | DefaultPartitioningProblem | | CheckingGraphforCorrectness<br>EvaluatePartitioningMetrics<br>FastSequentialPartitioning,Mesh<br>GoodSequentialPartitioning,Mesh<br>VeryGoodSequentialPartitioning,Mesh | | FastSequentialPartitioning,Social<br>GoodSequentialPartitioning,Social<br>VeryGoodSequentialPartitioning,Social |
| Parameter | Values | | --- | --- | | NumberofnodesN | 1000,5000 | | Maximumnodedegreemaxk | 50 | | Averagenodedegreeavgk | 10 | | Degreedistributionτ1 | -2 | | Maximumcommunitysizemaxc | 50,100 | | Minimumcommunitysizeminc | 10,20 | | Communitysizedistributionτ2 | -1 | | Mixingparameterµ | [0.05,0.075]withstepof0.05 | | OverlappingNodesOn | 500 | | OverlappingMembershipsOm | [1,8]withstepof1 |
0
| Usecase | | --- | | DefaultPartitioningProblem | | CheckingGraphforCorrectness<br>EvaluatePartitioningMetrics<br>FastSequentialPartitioning,Mesh<br>GoodSequentialPartitioning,Mesh<br>VeryGoodSequentialPartitioning,Mesh | | FastSequentialPartitioning,Social<br>GoodSequentialPartitioning,Social<br>VeryGoodSequentialPartitioning,Social | | MappingtoProcessorNetworks |
| HighestQuality,Mesh<br>HighestQuality,Social | | --- | | ParallelPartitioning | | DistributedMemoryParallel,Mesh<br>DistributedMemoryParallel,Social<br>ConvertMetistoBinary<br>EvaluateandConvertPartitions | | NodeSeparators | | TwoNodeSeparators<br>k-waySeparators |
1
| Usecase | | --- | | DefaultPartitioningProblem | | CheckingGraphforCorrectness<br>EvaluatePartitioningMetrics<br>FastSequentialPartitioning,Mesh<br>GoodSequentialPartitioning,Mesh<br>VeryGoodSequentialPartitioning,Mesh | | FastSequentialPartitioning,Social<br>GoodSequentialPartitioning,Social<br>VeryGoodSequentialPartitioning,Social | | MappingtoProcessorNetworks |
| Communitysizedistributionτ2 | -1 | | --- | --- | | Mixingparameterµ | [0.05,0.075]withstepof0.05 | | OverlappingNodesOn | 500 | | OverlappingMembershipsOm | [1,8]withstepof1 |
0
| Command | ANumber | Comments | | --- | --- | --- | | \alignauthor | 100 | Authoralignment | | \numberofauthors | 200 | Authorenumeration |
| \table | 300 | Fortables | | --- | --- | --- | | \table* | 400 | Forwidertables |
1
| Command | ANumber | Comments | | --- | --- | --- | | \alignauthor | 100 | Authoralignment | | \numberofauthors | 200 | Authorenumeration |
| Command | ANumber | Comments | | --- | --- | --- | | \alignauthor | 100 | Authoralignment | | \numberofauthors | 200 | Authorenumeration | | \table | 300 | Fortables | | \table* | 400 | Forwidertables |
0
| Command | ANumber | Comments | | --- | --- | --- | | \alignauthor | 100 | Authoralignment | | \numberofauthors | 200 | Authorenumeration |
| \table | 300 | Fortables | | --- | --- | --- | | \table* | 400 | Forwidertables |
1
| Command | ANumber | Comments | | --- | --- | --- | | \alignauthor | 100 | Authoralignment | | \numberofauthors | 200 | Authorenumeration |
| \table | 300 | Fortables | | --- | --- | --- | | \table* | 400 | Forwidertables |
0
| Accuracy | Coverage | | | --- | --- | --- | | nikolaosted | 0.919 | 0.014 | | sentistrengthmyspace | 0.800 | 0.091 | | aisoposntua | 0.787 | 0.526 | | tweetsemevaltest | 0.693 | 0.071 | | englishdailabor | 0.687 | 0.064 |
| sentistrengthyoutube | 0.686 | 0.085 | | --- | --- | --- | | sentistrengthtwitter | 0.627 | 0.097 | | sentistrengthrw | 0.619 | 0.148 | | sentistrengthdigg | 0.600 | 0.028 | | sanders | 0.359 | 0.045 | | debate | 0.339 | 0.015 | | sentistrengthbbc | 0.173 | 0.006 | | vadernyt | - | - |
1
| Accuracy | Coverage | | | --- | --- | --- | | nikolaosted | 0.919 | 0.014 | | sentistrengthmyspace | 0.800 | 0.091 | | aisoposntua | 0.787 | 0.526 | | tweetsemevaltest | 0.693 | 0.071 | | englishdailabor | 0.687 | 0.064 |
| Dataset | BagofWords | BaseMethods | BoW+BaseMethods | | --- | --- | --- | --- | | englishdailabor | 68.4 | 67.1 | 72.4 | | aisoposntua | 72.3 | 62.0 | 69.9 | | tweetsemevaltest | 58.3 | 62.8 | 65.2 | | sentistrengthtwitter | 58.8 | 59.1 | 61.2 | | sentistrengthyoutube | 56.6 | 56.1 | 58.7 | | sanders | 61.5 | 54.1 | 56.4 | | sentistrengthmyspace | 50.2 | 52.3 | 52.2 | | sentistrengthdigg | 45.4 | 50.1 | 50.6 | | nikolaosted | 51.3 | 45.9 | 49.0 | | debate | 57.1 | 45.9 | 47.1 | | sentistrengthrw | 48.3 | 48.5 | 45.5 | | sentistrengthbbc | 34.8 | 45.5 | 43.8 | | vadernyt | 28.0 | 38.9 | 39.2 |
0
| Accuracy | Coverage | | | --- | --- | --- | | nikolaosted | 0.919 | 0.014 | | sentistrengthmyspace | 0.800 | 0.091 | | aisoposntua | 0.787 | 0.526 | | tweetsemevaltest | 0.693 | 0.071 | | englishdailabor | 0.687 | 0.064 |
| sentistrengthyoutube | 0.686 | 0.085 | | --- | --- | --- | | sentistrengthtwitter | 0.627 | 0.097 | | sentistrengthrw | 0.619 | 0.148 | | sentistrengthdigg | 0.600 | 0.028 | | sanders | 0.359 | 0.045 | | debate | 0.339 | 0.015 | | sentistrengthbbc | 0.173 | 0.006 | | vadernyt | - | - |
1
| Accuracy | Coverage | | | --- | --- | --- | | nikolaosted | 0.919 | 0.014 | | sentistrengthmyspace | 0.800 | 0.091 | | aisoposntua | 0.787 | 0.526 | | tweetsemevaltest | 0.693 | 0.071 | | englishdailabor | 0.687 | 0.064 |
| sentistrengthyoutube | 56.6 | 56.1 | 58.7 | | --- | --- | --- | --- | | sanders | 61.5 | 54.1 | 56.4 | | sentistrengthmyspace | 50.2 | 52.3 | 52.2 | | sentistrengthdigg | 45.4 | 50.1 | 50.6 | | nikolaosted | 51.3 | 45.9 | 49.0 | | debate | 57.1 | 45.9 | 47.1 | | sentistrengthrw | 48.3 | 48.5 | 45.5 | | sentistrengthbbc | 34.8 | 45.5 | 43.8 | | vadernyt | 28.0 | 38.9 | 39.2 |
0
| AverageF1score | | | | | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 10 | 30 | 50 | 100 | 200 | 500 | 10 | 30 | 50 | 100 | 200 |
| 53.17 | | | | | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 52.16 | 53.74 | 54.36 | 55.24 | 55.60 | 55.06 | 70.61 | 73.00 | 73.84 | 74.94 | 75.32 | | 56.54 | 57.42 | 57.85 | 57.87 | 58.22 | 58.39 | 76.45 | 77.64 | 78.14 | 78.52 | 79.07 | | 56.27 | 57.74 | 58.49 | 58.76 | 59.12 | 58.88 | 75.04 | 77.83 | 78.72 | 79.23 | 79.67 | | 58.66 | 60.04 | 60.56 | 60.18 | 60.48 | 60.17 | 78.25 | 80.15 | 80.59 | 80.20 | 80.27 |
1
| AverageF1score | | | | | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 10 | 30 | 50 | 100 | 200 | 500 | 10 | 30 | 50 | 100 | 200 |
| 114 | 114 | 2 | 0.020s | 0.008s | 0.017s | 0.028s | | --- | --- | --- | --- | --- | --- | --- | | 682 | 676 | 0 | 0.058s | 0.036s | 0.053s | 0.073s | | 2,286 | 2,254 | 8 | 0.22s | 0.10s | 0.11s | 0.16s | | 7,397 | 7,163 | 28 | 0.64s | 0.29s | 0.26s | 0.37s | | 19,619 | 18,315 | 94 | 2.87s | 0.79s | 0.49s | 0.70s | | 63,109 | 50,584 | 276 | 13.0s | 2.8s | 1.2s | 1.4s | | 269,223 | 160,203 | 712 | 1m22s | 9.8s | 4.4s | 3.7s | | 1,625,520 | 827,469 | 2,244 | 9m17s | 50s | 16.8s | 20.3s | | 11,040,912 | 5,044,441 | 5,582 | 82m33s | 5m2s | 1m5s | 1m3s | | | 36,633,391 | 14,872 | | 46m59s | 8m30s | 6m20s | | | 264,463,730 | 49,114 | | 6h22m56s | 67m31s | 46m37s | | | 1,852,158,881 | 145,276 | | | 10h25m45s | 7h43m57s |
0
| AverageF1score | | | | | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 10 | 30 | 50 | 100 | 200 | 500 | 10 | 30 | 50 | 100 | 200 | | 53.17 | | | | | | | | | | |
| 52.16 | 53.74 | 54.36 | 55.24 | 55.60 | 55.06 | 70.61 | 73.00 | 73.84 | 74.94 | 75.32 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 56.54 | 57.42 | 57.85 | 57.87 | 58.22 | 58.39 | 76.45 | 77.64 | 78.14 | 78.52 | 79.07 | | 56.27 | 57.74 | 58.49 | 58.76 | 59.12 | 58.88 | 75.04 | 77.83 | 78.72 | 79.23 | 79.67 | | 58.66 | 60.04 | 60.56 | 60.18 | 60.48 | 60.17 | 78.25 | 80.15 | 80.59 | 80.20 | 80.27 |
1
| AverageF1score | | | | | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 10 | 30 | 50 | 100 | 200 | 500 | 10 | 30 | 50 | 100 | 200 | | 53.17 | | | | | | | | | | |
| 1,625,520 | 827,469 | 2,244 | 9m17s | 50s | 16.8s | 20.3s | | --- | --- | --- | --- | --- | --- | --- | | 11,040,912 | 5,044,441 | 5,582 | 82m33s | 5m2s | 1m5s | 1m3s | | | 36,633,391 | 14,872 | | 46m59s | 8m30s | 6m20s | | | 264,463,730 | 49,114 | | 6h22m56s | 67m31s | 46m37s | | | 1,852,158,881 | 145,276 | | | 10h25m45s | 7h43m57s |
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