premise
string
hypothesis
string
label
int64
| Intrusion | No.ofMFSs<br>ofEachRun | No.of<br>SharedMFSs | | --- | --- | --- | | decode | {2,5} | 2 |
| bufferoverflowintoxlock | {68,68} | 68 | | --- | --- | --- | | bufferoverflowintonamed | {59,38} | 33 | | sunsendmailcp | {24,24,24} | 24 | | forwardloops | {33,11,30,33,4} | 0 | | syslog-local | {55,71} | 52 | | syslog-remote | {78,42} | 42 |
1
| Intrusion | No.ofMFSs<br>ofEachRun | No.of<br>SharedMFSs | | --- | --- | --- | | decode | {2,5} | 2 |
| Step | Description | Time | Messages | | --- | --- | --- | --- | | ??,?? | BFSconvergecast | O(D) | O(m) | | ??,?? | BFSupcastoffmessages | O(D+f) | O(f·D) | | ??,?? | Localcomputation | 0 | none | | ?? | BFSdowncastoffmessages(eachofsizelogn) | O(D+f·logn) | O(f·logn·D) | | ?? | BroadcastineachoftheMSTfragments | O(k+logn) | O(n·logn) | | ?? | Communicationbetweenneighbors | O(logn) | O(logn·m) |
0
| Intrusion | No.ofMFSs<br>ofEachRun | No.of<br>SharedMFSs | | --- | --- | --- | | decode | {2,5} | 2 | | bufferoverflowintoxlock | {68,68} | 68 | | bufferoverflowintonamed | {59,38} | 33 |
| sunsendmailcp | {24,24,24} | 24 | | --- | --- | --- | | forwardloops | {33,11,30,33,4} | 0 | | syslog-local | {55,71} | 52 | | syslog-remote | {78,42} | 42 |
1
| Intrusion | No.ofMFSs<br>ofEachRun | No.of<br>SharedMFSs | | --- | --- | --- | | decode | {2,5} | 2 | | bufferoverflowintoxlock | {68,68} | 68 | | bufferoverflowintonamed | {59,38} | 33 |
| ?? | BFSdowncastoffmessages(eachofsizelogn) | O(D+f·logn) | O(f·logn·D) | | --- | --- | --- | --- | | ?? | BroadcastineachoftheMSTfragments | O(k+logn) | O(n·logn) | | ?? | Communicationbetweenneighbors | O(logn) | O(logn·m) |
0
| FineTuning | GradualTuning | | | | | | | --- | --- | --- | --- | --- | --- | --- | | Reg | Task-B | Task-A | Epochs | Task-B | Task-A | Epochs |
| No | 2.25±0.04 | 6.7→13.3±0.2 | 73±52 | 2.33±0.09 | 6.7→9.5±0.3 | 47±16 | | --- | --- | --- | --- | --- | --- | --- | | L1 | 1.60±0.05 | 4.7→20.5±2.9 | 23±13 | 1.61±0.06 | 4.7→11.9±3.2 | 37±15 | | Drop | 1.58±0.10 | 5.9→20.5±1.1 | 113±21 | 1.55±0.18 | 5.9→20.0±1.5 | 145±46 |
1
| FineTuning | GradualTuning | | | | | | | --- | --- | --- | --- | --- | --- | --- | | Reg | Task-B | Task-A | Epochs | Task-B | Task-A | Epochs |
| FineTuning | GradualTuning | | | | | | | --- | --- | --- | --- | --- | --- | --- | | Reg | Task-B | Task-A | Epochs | Task-B | Task-A | Epochs | | No | 4.31±0.12 | 9.1→27.1±0.3 | 78±16 | 4.65±0.12 | 9.1→24.1±0.1 | 120±28 | | L1 | 2.32±0.33 | 7.1→40.2±3.7 | 77±48 | 2.09±0.28 | 7.1→36.6±1.9 | 108±20 | | Drop | 8.21±1.10 | 7.7→38.0±2.6 | 158±46 | 4.29±0.14 | 7.7→46.2±0.2 | 293±4 |
0
| FineTuning | GradualTuning | | | | | | | --- | --- | --- | --- | --- | --- | --- | | Reg | Task-B | Task-A | Epochs | Task-B | Task-A | Epochs | | No | 2.25±0.04 | 6.7→13.3±0.2 | 73±52 | 2.33±0.09 | 6.7→9.5±0.3 | 47±16 |
| L1 | 1.60±0.05 | 4.7→20.5±2.9 | 23±13 | 1.61±0.06 | 4.7→11.9±3.2 | 37±15 | | --- | --- | --- | --- | --- | --- | --- | | Drop | 1.58±0.10 | 5.9→20.5±1.1 | 113±21 | 1.55±0.18 | 5.9→20.0±1.5 | 145±46 |
1
| FineTuning | GradualTuning | | | | | | | --- | --- | --- | --- | --- | --- | --- | | Reg | Task-B | Task-A | Epochs | Task-B | Task-A | Epochs | | No | 2.25±0.04 | 6.7→13.3±0.2 | 73±52 | 2.33±0.09 | 6.7→9.5±0.3 | 47±16 |
| L1 | 2.32±0.33 | 7.1→40.2±3.7 | 77±48 | 2.09±0.28 | 7.1→36.6±1.9 | 108±20 | | --- | --- | --- | --- | --- | --- | --- | | Drop | 8.21±1.10 | 7.7→38.0±2.6 | 158±46 | 4.29±0.14 | 7.7→46.2±0.2 | 293±4 |
0
| Reference | Lexicon | LM | CH | SW | | --- | --- | --- | --- | --- | | Current | N | N | 26.4 | 17.2 | | Current | N | CharNG | 21.8 | 13.8 | | (ensemble) | Y | WordNG | 19.3 | 12.6 |
| Current | Y | WordNG | 18.7 | 11.3 | | --- | --- | --- | --- | --- | | Current | Y | WordRNN | 17.7 | 10.2 |
1
| Reference | Lexicon | LM | CH | SW | | --- | --- | --- | --- | --- | | Current | N | N | 26.4 | 17.2 | | Current | N | CharNG | 21.8 | 13.8 | | (ensemble) | Y | WordNG | 19.3 | 12.6 |
| LM | #succ<br>words | dev | eval | | | | --- | --- | --- | --- | --- | --- | | Vit | CN | Vit | CN | | | | ng4 | | 25.00 | 24.19 | 25.19 | 24.44 | | +uni-rnn | | 23.11 | 22.33 | 22.95 | 22.30 | | +su-rnn | 1<br>3 | 22.92<br>22.67 | 22.12<br>21.77 | 22.77<br>22.40 | 22.11<br>21.53 |
0
| Reference | Lexicon | LM | CH | SW | | --- | --- | --- | --- | --- | | Current | N | N | 26.4 | 17.2 | | Current | N | CharNG | 21.8 | 13.8 |
| (ensemble) | Y | WordNG | 19.3 | 12.6 | | --- | --- | --- | --- | --- | | Current | Y | WordNG | 18.7 | 11.3 | | Current | Y | WordRNN | 17.7 | 10.2 |
1
| Reference | Lexicon | LM | CH | SW | | --- | --- | --- | --- | --- | | Current | N | N | 26.4 | 17.2 | | Current | N | CharNG | 21.8 | 13.8 |
| +uni-rnn | | 23.11 | 22.33 | 22.95 | 22.30 | | --- | --- | --- | --- | --- | --- | | +su-rnn | 1<br>3 | 22.92<br>22.67 | 22.12<br>21.77 | 22.77<br>22.40 | 22.11<br>21.53 |
0
| Model | Evaluation | | | | | --- | --- | --- | --- | --- | | MAE | MedAE | R | Acc.@10 | | | SVR-RBF | 6.8 | 3.2 | 0.03 | 0.84 | | LASSO@1 | 7.9 | 5.2 | 0.05 | 0.80 | | LASSO@0.5 | 7.7 | 4.9 | 0.09 | 0.80 |
| LASSO@0.25 | 7.6 | 4.8 | 0.10 | 0.79 | | --- | --- | --- | --- | --- | | LASSO@0.125 | 7.5 | 4.7 | 0.11 | 0.79 | | Baseline(mean) | 8.1 | 5.8 | 0.0 | 0.81 |
1
| Model | Evaluation | | | | | --- | --- | --- | --- | --- | | MAE | MedAE | R | Acc.@10 | | | SVR-RBF | 6.8 | 3.2 | 0.03 | 0.84 | | LASSO@1 | 7.9 | 5.2 | 0.05 | 0.80 | | LASSO@0.5 | 7.7 | 4.9 | 0.09 | 0.80 |
| Model | Evaluation | | | | | --- | --- | --- | --- | --- | | MAE | MedAE | R | Acc.@10 | | | SVR-RBF | 6.8 | 3.2 | 0.02 | 0.84 | | SVR-L | 6.9 | 3.3 | 0.004 | 0.83 | | LASSO@0.25 | 7.6 | 4.9 | 0.08 | 0.81 | | Baseline(mean) | 8.1 | 5.8 | 0.0 | 0.81 |
0
| Model | Evaluation | | | | | --- | --- | --- | --- | --- | | MAE | MedAE | R | Acc.@10 | | | SVR-RBF | 6.8 | 3.2 | 0.03 | 0.84 | | LASSO@1 | 7.9 | 5.2 | 0.05 | 0.80 |
| LASSO@0.5 | 7.7 | 4.9 | 0.09 | 0.80 | | --- | --- | --- | --- | --- | | LASSO@0.25 | 7.6 | 4.8 | 0.10 | 0.79 | | LASSO@0.125 | 7.5 | 4.7 | 0.11 | 0.79 | | Baseline(mean) | 8.1 | 5.8 | 0.0 | 0.81 |
1
| Model | Evaluation | | | | | --- | --- | --- | --- | --- | | MAE | MedAE | R | Acc.@10 | | | SVR-RBF | 6.8 | 3.2 | 0.03 | 0.84 | | LASSO@1 | 7.9 | 5.2 | 0.05 | 0.80 |
| LASSO@0.25 | 7.6 | 4.9 | 0.08 | 0.81 | | --- | --- | --- | --- | --- | | Baseline(mean) | 8.1 | 5.8 | 0.0 | 0.81 |
0
| | Willow | PASCAL2010 | PASCAL2012 | Stanford-40 | HAT-27 | | --- | --- | --- | --- | --- | --- | | VGG-19FC | 87.1 | 72.0 | 74.0 | 70.3 | 61.2 | | MOP | 87.6 | 74.8 | 75.3 | 74.2 | 64.1 |
| FV-CNN | 87.9 | 75.4 | 75.6 | 74.6 | 64.5 | | --- | --- | --- | --- | --- | --- | | FV-CNN-SP | 88.4 | 78.1 | 77.3 | 76.9 | 66.6 | | Absolute-ScaleCoding | 89.3 | 79.7 | 78.1 | 77.5 | 67.3 | | Relative-ScaleCoding | 89.7 | 79.9 | 78.4 | 77.8 | 67.4 | | Absolute+Relative+FC | 92.1 | 82.7 | 80.3 | 80.0 | 70.6 |
1
| | Willow | PASCAL2010 | PASCAL2012 | Stanford-40 | HAT-27 | | --- | --- | --- | --- | --- | --- | | VGG-19FC | 87.1 | 72.0 | 74.0 | 70.3 | 61.2 | | MOP | 87.6 | 74.8 | 75.3 | 74.2 | 64.1 |
| CNNsName | VGG-F | VGG-M | VGG-S | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | | | PostReLU | PreReLU | PostReLU | PreReLU | PostReLU | PreReLU | PostReLU | | Dimensions | 4096 | 4096 | 4096 | 4096 | 4096 | 4096 | 4096 | | Selection | RF(5) | SU(5) | SU(10) | SU(10) | RF(10) | SU(5) | SU(15) | | Classifier | SVMs | NB | RFT | NB | NB | RFT | kNN | | Accuracy | 83.86 | 89.29 | 83.13 | 83.86 | 90.41 | 87.10 | 90.34 | | AUC | 0.741 | 0.744 | 0.740 | 0.750 | 0.742 | 0.716 | 0.841 |
0
| | Willow | PASCAL2010 | PASCAL2012 | Stanford-40 | HAT-27 | | --- | --- | --- | --- | --- | --- | | VGG-19FC | 87.1 | 72.0 | 74.0 | 70.3 | 61.2 | | MOP | 87.6 | 74.8 | 75.3 | 74.2 | 64.1 |
| FV-CNN | 87.9 | 75.4 | 75.6 | 74.6 | 64.5 | | --- | --- | --- | --- | --- | --- | | FV-CNN-SP | 88.4 | 78.1 | 77.3 | 76.9 | 66.6 | | Absolute-ScaleCoding | 89.3 | 79.7 | 78.1 | 77.5 | 67.3 | | Relative-ScaleCoding | 89.7 | 79.9 | 78.4 | 77.8 | 67.4 | | Absolute+Relative+FC | 92.1 | 82.7 | 80.3 | 80.0 | 70.6 |
1
| | Willow | PASCAL2010 | PASCAL2012 | Stanford-40 | HAT-27 | | --- | --- | --- | --- | --- | --- | | VGG-19FC | 87.1 | 72.0 | 74.0 | 70.3 | 61.2 | | MOP | 87.6 | 74.8 | 75.3 | 74.2 | 64.1 |
| Accuracy | 83.86 | 89.29 | 83.13 | 83.86 | 90.41 | 87.10 | 90.34 | | --- | --- | --- | --- | --- | --- | --- | --- | | AUC | 0.741 | 0.744 | 0.740 | 0.750 | 0.742 | 0.716 | 0.841 |
0
| DataSet | \|D\| | \|Q\| | Vm | Em | d | Scale-free | | --- | --- | --- | --- | --- | --- | --- | | AIDS | 1896 | 100 | 95 | 103 | 2.1 | Yes | | Finger | 2159 | 114 | 26 | 26 | 1.7 | Yes | | GREC | 1045 | 55 | 24 | 29 | 2.1 | Yes | | AASD | 37995 | 100 | 93 | 99 | 2.1 | Yes |
| Syn-1 | 3430 | 70 | 100K | 1M | 9.6 | Yes | | --- | --- | --- | --- | --- | --- | --- | | Syn-2 | 3430 | 70 | 100K | 1M | 9.4 | No |
1
| DataSet | \|D\| | \|Q\| | Vm | Em | d | Scale-free | | --- | --- | --- | --- | --- | --- | --- | | AIDS | 1896 | 100 | 95 | 103 | 2.1 | Yes | | Finger | 2159 | 114 | 26 | 26 | 1.7 | Yes | | GREC | 1045 | 55 | 24 | 29 | 2.1 | Yes | | AASD | 37995 | 100 | 93 | 99 | 2.1 | Yes |
| Dataset | c | DPBook | EM | SVT | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 1:1 | 1:3 | 1:k | 1:k | 1:1 | | | | | | BMS-PO | 50 | 0.061 | 0.001 | 0.010 | 0.008 | 0.015 | 0.008 | 0.002 | | 100 | 0.561 | 0.006 | 0.242 | 0.087 | 0.070 | 0.046 | 0.049 | | | 150 | 0.674 | 0.048 | 0.502 | 0.339 | 0.243 | 0.209 | 0.184 | | | 200 | 0.691 | 0.093 | 0.632 | 0.571 | 0.518 | 0.481 | 0.302 | | | 250 | 0.658 | 0.123 | 0.645 | 0.596 | 0.574 | 0.554 | 0.312 | | | 300 | 0.619 | 0.140 | 0.645 | 0.599 | 0.557 | 0.581 | 0.283 | | | Kosarak | 50 | 0.731 | 0.000 | 0.027 | 0.010 | 0.008 | 0.006 | 0.004 | | 100 | 0.984 | 0.033 | 0.932 | 0.658 | 0.346 | 0.398 | 0.777 | | | 150 | 0.986 | 0.139 | 0.974 | 0.932 | 0.836 | 0.850 | 0.931 | | | 200 | 0.987 | 0.218 | 0.981 | 0.969 | 0.936 | 0.955 | 0.958 | | | 250 | 0.984 | 0.273 | 0.980 | 0.975 | 0.963 | 0.963 | 0.960 | | | 300 | 0.986 | 0.315 | 0.981 | 0.976 | 0.975 | 0.971 | 0.967 | | | AOL | 50 | 0.219 | 0.001 | 0.011 | 0.009 | 0.014 | 0.008 | 0.002 | | 100 | 0.995 | 0.004 | 0.746 | 0.066 | 0.078 | 0.022 | 0.548 | | | 150 | 1.000 | 0.153 | 0.987 | 0.901 | 0.531 | 0.587 | 0.978 | | | 200 | 1.000 | 0.412 | 0.998 | 0.989 | 0.952 | 0.961 | 0.996 | | | 250 | 1.000 | 0.572 | 1.000 | 0.997 | 0.991 | 0.992 | 0.998 | | | 300 | 1.000 | 0.683 | 0.999 | 0.999 | 0.995 | 0.997 | 0.999 | |
0
| DataSet | \|D\| | \|Q\| | Vm | Em | d | Scale-free | | --- | --- | --- | --- | --- | --- | --- | | AIDS | 1896 | 100 | 95 | 103 | 2.1 | Yes | | Finger | 2159 | 114 | 26 | 26 | 1.7 | Yes |
| GREC | 1045 | 55 | 24 | 29 | 2.1 | Yes | | --- | --- | --- | --- | --- | --- | --- | | AASD | 37995 | 100 | 93 | 99 | 2.1 | Yes | | Syn-1 | 3430 | 70 | 100K | 1M | 9.6 | Yes | | Syn-2 | 3430 | 70 | 100K | 1M | 9.4 | No |
1
| DataSet | \|D\| | \|Q\| | Vm | Em | d | Scale-free | | --- | --- | --- | --- | --- | --- | --- | | AIDS | 1896 | 100 | 95 | 103 | 2.1 | Yes | | Finger | 2159 | 114 | 26 | 26 | 1.7 | Yes |
| 200 | 0.987 | 0.218 | 0.981 | 0.969 | 0.936 | 0.955 | 0.958 | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 250 | 0.984 | 0.273 | 0.980 | 0.975 | 0.963 | 0.963 | 0.960 | | | 300 | 0.986 | 0.315 | 0.981 | 0.976 | 0.975 | 0.971 | 0.967 | | | AOL | 50 | 0.219 | 0.001 | 0.011 | 0.009 | 0.014 | 0.008 | 0.002 | | 100 | 0.995 | 0.004 | 0.746 | 0.066 | 0.078 | 0.022 | 0.548 | | | 150 | 1.000 | 0.153 | 0.987 | 0.901 | 0.531 | 0.587 | 0.978 | | | 200 | 1.000 | 0.412 | 0.998 | 0.989 | 0.952 | 0.961 | 0.996 | | | 250 | 1.000 | 0.572 | 1.000 | 0.997 | 0.991 | 0.992 | 0.998 | | | 300 | 1.000 | 0.683 | 0.999 | 0.999 | 0.995 | 0.997 | 0.999 | |
0
| nc | nf | JV | ALG1 | ALG2 | | --- | --- | --- | --- | --- | | 100 | 20 | 1.004 | 1.0047 | 1.0001 | | 160 | 20 | 1.5116 | 1.0612 | 1.0009 | | 160 | 40 | 1.065 | 1.0063 | 1.0 | | 208 | 52 | 2.2537 | 1.074 | 1.019 | | 240 | 60 | 1.0083 | 1.0045 | 1.0001 | | 300 | 75 | 1.8088 | 1.0478 | 1.0006 | | 312 | 52 | 1.7593 | 1.0475 | 1.0008 |
| 320 | 32 | 1.0972 | 1.0015 | 1.0 | | --- | --- | --- | --- | --- | | 400 | 100 | 1.0058 | 1.0048 | 1.0 | | 416 | 52 | 1.0031 | 1.0048 | 1.0 |
1
| nc | nf | JV | ALG1 | ALG2 | | --- | --- | --- | --- | --- | | 100 | 20 | 1.004 | 1.0047 | 1.0001 | | 160 | 20 | 1.5116 | 1.0612 | 1.0009 | | 160 | 40 | 1.065 | 1.0063 | 1.0 | | 208 | 52 | 2.2537 | 1.074 | 1.019 | | 240 | 60 | 1.0083 | 1.0045 | 1.0001 | | 300 | 75 | 1.8088 | 1.0478 | 1.0006 | | 312 | 52 | 1.7593 | 1.0475 | 1.0008 |
| nc | nf | JV | ALG1 | ALG2 | | --- | --- | --- | --- | --- | | 50 | 16 | 1.0642 | 1.0156 | 1.0 | | 50 | 16 | 1.127 | 1.0363 | 1.0 | | 50 | 16 | 1.1968 | 1.0258 | 1.0 | | 50 | 16 | 1.2649 | 1.0258 | 1.0022 | | 50 | 25 | 1.1167 | 1.006 | 1.0028 | | 50 | 25 | 1.2206 | 1.0393 | 1.0 | | 50 | 25 | 1.3246 | 1.0277 | 1.0 | | 50 | 25 | 1.4535 | 1.0318 | 1.0049 | | 50 | 50 | 1.3566 | 1.0101 | 1.0017 | | 50 | 50 | 1.5762 | 1.0348 | 1.0061 | | 50 | 50 | 1.7648 | 1.0378 | 1.0022 | | 50 | 50 | 2.0543 | 1.0494 | 1.0075 | | 1000 | 100 | 1.0453 | 1.0542 | 1.0023 | | 1000 | 100 | 1.0155 | 1.0226 | 1.0 | | 1000 | 100 | 1.0055 | 1.0101 | 1.0 |
0
| nc | nf | JV | ALG1 | ALG2 | | --- | --- | --- | --- | --- | | 100 | 20 | 1.004 | 1.0047 | 1.0001 |
| 160 | 20 | 1.5116 | 1.0612 | 1.0009 | | --- | --- | --- | --- | --- | | 160 | 40 | 1.065 | 1.0063 | 1.0 | | 208 | 52 | 2.2537 | 1.074 | 1.019 | | 240 | 60 | 1.0083 | 1.0045 | 1.0001 | | 300 | 75 | 1.8088 | 1.0478 | 1.0006 | | 312 | 52 | 1.7593 | 1.0475 | 1.0008 | | 320 | 32 | 1.0972 | 1.0015 | 1.0 | | 400 | 100 | 1.0058 | 1.0048 | 1.0 | | 416 | 52 | 1.0031 | 1.0048 | 1.0 |
1
| nc | nf | JV | ALG1 | ALG2 | | --- | --- | --- | --- | --- | | 100 | 20 | 1.004 | 1.0047 | 1.0001 |
| 50 | 25 | 1.2206 | 1.0393 | 1.0 | | --- | --- | --- | --- | --- | | 50 | 25 | 1.3246 | 1.0277 | 1.0 | | 50 | 25 | 1.4535 | 1.0318 | 1.0049 | | 50 | 50 | 1.3566 | 1.0101 | 1.0017 | | 50 | 50 | 1.5762 | 1.0348 | 1.0061 | | 50 | 50 | 1.7648 | 1.0378 | 1.0022 | | 50 | 50 | 2.0543 | 1.0494 | 1.0075 | | 1000 | 100 | 1.0453 | 1.0542 | 1.0023 | | 1000 | 100 | 1.0155 | 1.0226 | 1.0 | | 1000 | 100 | 1.0055 | 1.0101 | 1.0 |
0
| Algorithm | Precision | Recall | F-measure | | --- | --- | --- | --- | | Proposed | 0.7651 | 0.7531 | 0.7591 | | Zhangetal. | 0.83 | 0.67 | 0.74 | | Yinetal. | 0.81 | 0.63 | 0.71 | | Kangetal. | 0.71 | 0.62 | 0.66 | | Yinetal. | 0.71 | 0.61 | 0.66 |
| Unified | 0.64 | 0.62 | 0.61 | | --- | --- | --- | --- | | TD-Mixture | 0.63 | 0.63 | 0.60 | | TD-ICDAR | 0.53 | 0.52 | 0.50 | | Epshteinetal. | 0.25 | 0.25 | 0.25 | | Chenetal. | 0.05 | 0.05 | 0.05 |
1
| Algorithm | Precision | Recall | F-measure | | --- | --- | --- | --- | | Proposed | 0.7651 | 0.7531 | 0.7591 | | Zhangetal. | 0.83 | 0.67 | 0.74 | | Yinetal. | 0.81 | 0.63 | 0.71 | | Kangetal. | 0.71 | 0.62 | 0.66 | | Yinetal. | 0.71 | 0.61 | 0.66 |
| Algorithm | Precision | Recall | F-measure | | --- | --- | --- | --- | | Proposed | 0.88 | 0.78 | 0.83 | | Zhangetal. | 0.88 | 0.74 | 0.80 | | Tianetal. | 0.85 | 0.76 | 0.80 | | Luetal. | 0.89 | 0.70 | 0.78 | | iwrr2014 | 0.86 | 0.70 | 0.77 | | USTBTexStar | 0.88 | 0.66 | 0.76 | | TextSpotter | 0.88 | 0.65 | 0.74 | | Yinetal. | 0.84 | 0.65 | 0.73 | | CASIANLPR | 0.79 | 0.68 | 0.73 | | TextDetectorCASIA | 0.85 | 0.63 | 0.72 | | I2RNUSFAR | 0.75 | 0.69 | 0.72 | | I2RNUS | 0.73 | 0.66 | 0.69 | | TH-TextLoc | 0.70 | 0.65 | 0.67 |
0
| Algorithm | Precision | Recall | F-measure | | --- | --- | --- | --- | | Proposed | 0.7651 | 0.7531 | 0.7591 | | Zhangetal. | 0.83 | 0.67 | 0.74 | | Yinetal. | 0.81 | 0.63 | 0.71 | | Kangetal. | 0.71 | 0.62 | 0.66 |
| Yinetal. | 0.71 | 0.61 | 0.66 | | --- | --- | --- | --- | | Unified | 0.64 | 0.62 | 0.61 | | TD-Mixture | 0.63 | 0.63 | 0.60 | | TD-ICDAR | 0.53 | 0.52 | 0.50 | | Epshteinetal. | 0.25 | 0.25 | 0.25 | | Chenetal. | 0.05 | 0.05 | 0.05 |
1
| Algorithm | Precision | Recall | F-measure | | --- | --- | --- | --- | | Proposed | 0.7651 | 0.7531 | 0.7591 | | Zhangetal. | 0.83 | 0.67 | 0.74 | | Yinetal. | 0.81 | 0.63 | 0.71 | | Kangetal. | 0.71 | 0.62 | 0.66 |
| Yinetal. | 0.84 | 0.65 | 0.73 | | --- | --- | --- | --- | | CASIANLPR | 0.79 | 0.68 | 0.73 | | TextDetectorCASIA | 0.85 | 0.63 | 0.72 | | I2RNUSFAR | 0.75 | 0.69 | 0.72 | | I2RNUS | 0.73 | 0.66 | 0.69 | | TH-TextLoc | 0.70 | 0.65 | 0.67 |
0
| | mbb/h | | --- | --- | | RandomizedPseudo-HarmonicMapping | 1,465 | | Resolve | 150.2 | | Reach-Maxmargin(Expensive) | 149.2 |
| Unsafe(Expensive) | 148.3 | | --- | --- | | Maxmargin | 122.0 | | Reach-Maxmargin | 119.1 |
1
| | mbb/h | | --- | --- | | RandomizedPseudo-HarmonicMapping | 1,465 | | Resolve | 150.2 | | Reach-Maxmargin(Expensive) | 149.2 |
| 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 |
0
| | mbb/h | | --- | --- | | RandomizedPseudo-HarmonicMapping | 1,465 | | Resolve | 150.2 | | Reach-Maxmargin(Expensive) | 149.2 | | Unsafe(Expensive) | 148.3 |
| Maxmargin | 122.0 | | --- | --- | | Reach-Maxmargin | 119.1 |
1
| | mbb/h | | --- | --- | | RandomizedPseudo-HarmonicMapping | 1,465 | | Resolve | 150.2 | | Reach-Maxmargin(Expensive) | 149.2 | | Unsafe(Expensive) | 148.3 |
| Reach-Estimate+Distributional | 116.8 | 85.80 | 72.59 | | --- | --- | --- | --- | | Reach-Estimate+Distributional(notsplit) | 113.3 | 83.24 | 70.68 |
0
| | CRDI(-) | CKDI(-) | CADI(+) | PNA(-) | CAAI(+) | DDI(+) | EDI(+) | ACC(+) | ABC(+) | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 8 | 0.65 | 0.53 | 0.61 | 0.57 | 0.74 | 0.55 | 0.40 | 0.68 | 0.70 | | 9 | 0.55 | 0.46 | 0.57 | 0.57 | 0.68 | 0.53 | 0.27 | 0.63 | 0.68 |
| 10 | 0.40 | 0.46 | 0.53 | 0.46 | 0.57 | 0.42 | 0.17 | 0.53 | 0.61 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 11 | 0.38 | 0.46 | 0.44 | 0.38 | 0.48 | 0.31 | 0.10 | 0.38 | 0.51 | | 12 | 0.27 | 0.34 | 0.27 | 0.27 | 0.29 | 0.23 | 0.04 | 0.31 | 0.42 |
1
| | CRDI(-) | CKDI(-) | CADI(+) | PNA(-) | CAAI(+) | DDI(+) | EDI(+) | ACC(+) | ABC(+) | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 8 | 0.65 | 0.53 | 0.61 | 0.57 | 0.74 | 0.55 | 0.40 | 0.68 | 0.70 | | 9 | 0.55 | 0.46 | 0.57 | 0.57 | 0.68 | 0.53 | 0.27 | 0.63 | 0.68 |
| Feature | Non-toptier | Toptier | | | | --- | --- | --- | --- | --- | | Mean | Std.Dev. | Mean | Std.Dev. | | | CRDI | 0.25 | 0.259 | 0.173 | 0.178 | | CKDI | 0.536 | 0.504 | 0.396 | 0.419 | | CADI | 0.121 | 0.146 | 0.076 | 0.068 | | PNA | 0.1 | 0.077 | 0.097 | 0.068 | | CAAI | 0.206 | 0.232 | 0.175 | 0.16 | | DDI | 0.386 | 0.323 | 0.335 | 0.28 | | EDI | 0.323 | 0.292 | 0.23 | 0.265 | | ACC | 0.02 | 0.034 | 0.018 | 0.019 | | ABC | 0.034 | 0.087 | 0.015 | 0.034 |
0
| | CRDI(-) | CKDI(-) | CADI(+) | PNA(-) | CAAI(+) | DDI(+) | EDI(+) | ACC(+) | ABC(+) | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 8 | 0.65 | 0.53 | 0.61 | 0.57 | 0.74 | 0.55 | 0.40 | 0.68 | 0.70 | | 9 | 0.55 | 0.46 | 0.57 | 0.57 | 0.68 | 0.53 | 0.27 | 0.63 | 0.68 | | 10 | 0.40 | 0.46 | 0.53 | 0.46 | 0.57 | 0.42 | 0.17 | 0.53 | 0.61 |
| 11 | 0.38 | 0.46 | 0.44 | 0.38 | 0.48 | 0.31 | 0.10 | 0.38 | 0.51 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 12 | 0.27 | 0.34 | 0.27 | 0.27 | 0.29 | 0.23 | 0.04 | 0.31 | 0.42 |
1
| | CRDI(-) | CKDI(-) | CADI(+) | PNA(-) | CAAI(+) | DDI(+) | EDI(+) | ACC(+) | ABC(+) | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 8 | 0.65 | 0.53 | 0.61 | 0.57 | 0.74 | 0.55 | 0.40 | 0.68 | 0.70 | | 9 | 0.55 | 0.46 | 0.57 | 0.57 | 0.68 | 0.53 | 0.27 | 0.63 | 0.68 | | 10 | 0.40 | 0.46 | 0.53 | 0.46 | 0.57 | 0.42 | 0.17 | 0.53 | 0.61 |
| PNA | 0.1 | 0.077 | 0.097 | 0.068 | | --- | --- | --- | --- | --- | | CAAI | 0.206 | 0.232 | 0.175 | 0.16 | | DDI | 0.386 | 0.323 | 0.335 | 0.28 | | EDI | 0.323 | 0.292 | 0.23 | 0.265 | | ACC | 0.02 | 0.034 | 0.018 | 0.019 | | ABC | 0.034 | 0.087 | 0.015 | 0.034 |
0
| hammingradius | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | #ofbuckets(24bits) | 1 | 24 | 276 | 2,024 | 10,626 | 42,504 | 134,596 | 346,104 | 735,471 | | #ofqueries(24bits)(0.234s) | 70 | 467 | 277 | 115 | 44 | 18 | 7 | 2 | 0 |
| #ofbuckets(40bits) | 1 | 40 | 780 | 9,880 | 91,390 | 658,008 | 3,838,380 | 18,643,560 | 76,904,685 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | #ofqueries(40bits)(240.0s) | 0 | 0 | 27 | 252 | 302 | 205 | 107 | 57 | 27 |
1
| hammingradius | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | #ofbuckets(24bits) | 1 | 24 | 276 | 2,024 | 10,626 | 42,504 | 134,596 | 346,104 | 735,471 | | #ofqueries(24bits)(0.234s) | 70 | 467 | 277 | 115 | 44 | 18 | 7 | 2 | 0 |
| hammingradius | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | #ofbuckets(16bits) | 1 | 16 | 120 | 560 | 1,820 | 4,368 | 8,008 | 11,440 | 12,870 | | #ofqueries(16bits)(1.752s) | 0 | 3637 | 4932 | 1230 | 169 | 30 | 1 | 1 | 0 | | #ofbuckets(32bits) | 1 | 32 | 496 | 4960 | 35,960 | 201,376 | 906,192 | 3,365,856 | 10,518,300 | | #ofqueries(32bits)(237.8s) | 0 | 0 | 0 | 4 | 1710 | 4282 | 2691 | 1021 | 241 |
0
| hammingradius | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | #ofbuckets(24bits) | 1 | 24 | 276 | 2,024 | 10,626 | 42,504 | 134,596 | 346,104 | 735,471 |
| #ofqueries(24bits)(0.234s) | 70 | 467 | 277 | 115 | 44 | 18 | 7 | 2 | 0 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | #ofbuckets(40bits) | 1 | 40 | 780 | 9,880 | 91,390 | 658,008 | 3,838,380 | 18,643,560 | 76,904,685 | | #ofqueries(40bits)(240.0s) | 0 | 0 | 27 | 252 | 302 | 205 | 107 | 57 | 27 |
1
| hammingradius | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | #ofbuckets(24bits) | 1 | 24 | 276 | 2,024 | 10,626 | 42,504 | 134,596 | 346,104 | 735,471 |
| #ofqueries(16bits)(1.752s) | 0 | 3637 | 4932 | 1230 | 169 | 30 | 1 | 1 | 0 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | #ofbuckets(32bits) | 1 | 32 | 496 | 4960 | 35,960 | 201,376 | 906,192 | 3,365,856 | 10,518,300 | | #ofqueries(32bits)(237.8s) | 0 | 0 | 0 | 4 | 1710 | 4282 | 2691 | 1021 | 241 |
0
| | AU | AP | VP-25 | SF | | --- | --- | --- | --- | --- | | N=60 | 0.600 | 0.569 | 0.722 | 0.920 | | N=70 | 0.612 | 0.655 | 0.801 | 0.992 |
| N=80 | 0.645 | 0.657 | 0.814 | 0.989 | | --- | --- | --- | --- | --- | | N=90 | 0.642 | 0.678 | 0.816 | 0.986 | | N=100 | 0.663 | 0.685 | 0.823 | 0.983 |
1
| | AU | AP | VP-25 | SF | | --- | --- | --- | --- | --- | | N=60 | 0.600 | 0.569 | 0.722 | 0.920 | | N=70 | 0.612 | 0.655 | 0.801 | 0.992 |
| TSS | P1 | P2 | P3 | P4 | P5 | | --- | --- | --- | --- | --- | --- | | N/5 | 0.2174 | 0.2465 | 0.2515 | 0.2565 | 0.2631 | | 2N/5 | 0.2114 | 0.2468 | 0.2491 | 0.2557 | 0.2602 | | 3N/5 | 0.21 | 0.245 | 0.2482 | 0.2554 | 0.2587 | | 4N/5 | 0.2092 | 0.2449 | 0.2463 | 0.2539 | 0.2582 |
0
| | AU | AP | VP-25 | SF | | --- | --- | --- | --- | --- | | N=60 | 0.600 | 0.569 | 0.722 | 0.920 | | N=70 | 0.612 | 0.655 | 0.801 | 0.992 | | N=80 | 0.645 | 0.657 | 0.814 | 0.989 |
| N=90 | 0.642 | 0.678 | 0.816 | 0.986 | | --- | --- | --- | --- | --- | | N=100 | 0.663 | 0.685 | 0.823 | 0.983 |
1
| | AU | AP | VP-25 | SF | | --- | --- | --- | --- | --- | | N=60 | 0.600 | 0.569 | 0.722 | 0.920 | | N=70 | 0.612 | 0.655 | 0.801 | 0.992 | | N=80 | 0.645 | 0.657 | 0.814 | 0.989 |
| 3N/5 | 0.21 | 0.245 | 0.2482 | 0.2554 | 0.2587 | | --- | --- | --- | --- | --- | --- | | 4N/5 | 0.2092 | 0.2449 | 0.2463 | 0.2539 | 0.2582 |
0
| NetworkData | CAT | CRAB | FACE | MNIST | | --- | --- | --- | --- | --- | | CAT | 1.195 | 1.718 | 2.07 | 12.132 |
| CRAB | 2.621 | 0.854 | 3.158 | 10.881 | | --- | --- | --- | --- | --- | | FACE | 5.025 | 5.532 | 3.158 | 50.527 | | MNIST | 9.118 | 6.643 | 4.68 | 0.405 |
1
| NetworkData | CAT | CRAB | FACE | MNIST | | --- | --- | --- | --- | --- | | CAT | 1.195 | 1.718 | 2.07 | 12.132 |
| NetworkgroupID | N | minc | maxc | µ | On | | --- | --- | --- | --- | --- | --- | | N1 | 1000 | 10 | 50 | 0-0.5 | 100 | | N2 | 1000 | 20 | 100 | 0-0.5 | 100 | | N3 | 5000 | 10 | 50 | 0-0.5 | 500 | | N4 | 5000 | 20 | 100 | 0-0.5 | 500 | | N5 | 1000 | 10 | 50 | 0.1 | 0-500 | | N6 | 1000 | 20 | 100 | 0.1 | 0-500 | | N7 | 5000 | 10 | 50 | 0.1 | 0-2000 | | N8 | 5000 | 20 | 100 | 0.1 | 0-2000 |
0
| NetworkData | CAT | CRAB | FACE | MNIST | | --- | --- | --- | --- | --- | | CAT | 1.195 | 1.718 | 2.07 | 12.132 |
| CRAB | 2.621 | 0.854 | 3.158 | 10.881 | | --- | --- | --- | --- | --- | | FACE | 5.025 | 5.532 | 3.158 | 50.527 | | MNIST | 9.118 | 6.643 | 4.68 | 0.405 |
1
| NetworkData | CAT | CRAB | FACE | MNIST | | --- | --- | --- | --- | --- | | CAT | 1.195 | 1.718 | 2.07 | 12.132 |
| N7 | 5000 | 10 | 50 | 0.1 | 0-2000 | | --- | --- | --- | --- | --- | --- | | N8 | 5000 | 20 | 100 | 0.1 | 0-2000 |
0
| 3-objectdatasets | VINVisualLSTMVisualRNN | VINfromStateLSTMfromState | | --- | --- | --- | | Spring | 1.8313.2721.646 | 0.4261.844 | | Gravity | 1.2881.5721.194 | 0.1460.191 | | MagneticBilliards | 1.8782.9111.792 | 0.4541.863 | | Billiards | 1.6002.7521.391 | 0.9422.507 | | Drift | 2.9203.6632.474 | 0.00170.0052 |
| | | | | --- | --- | --- | | 6-objectdatasets | VINVisualLSTMVisualRNN | VINfromStateLSTMfromState | | Spring | 0.6080.8580.565 | 0.2350.324 | | Gravity | 0.4220.5970.416 | 0.0920.157 | | MagneticBilliards | 0.8361.3740.750 | 0.3490.791 | | Billiards | 1.0222.5820.918 | 0.8171.919 | | Drift | 0.8311.0830.749 | 0.00250.0069 |
1
| 3-objectdatasets | VINVisualLSTMVisualRNN | VINfromStateLSTMfromState | | --- | --- | --- | | Spring | 1.8313.2721.646 | 0.4261.844 | | Gravity | 1.2881.5721.194 | 0.1460.191 | | MagneticBilliards | 1.8782.9111.792 | 0.4541.863 | | Billiards | 1.6002.7521.391 | 0.9422.507 | | Drift | 2.9203.6632.474 | 0.00170.0052 |
| | OurModelVisualLSTMVisualRNN | OurPredictorLSTMPredictor | | --- | --- | --- | | Spring | 0.0460.2490.157 | 0.0630.324 | | Gravity | 0.0080.0480.043 | 0.0130.081 | | MagneticBilliards | 0.1110.3980.314 | 0.1790.332 | | Billiards | 0.1510.3910.308 | 0.1990.348 | | Euclideandeviationperobjectafterfullframewidthistravelled | | | | | OurModelVisualLSTMVisualRNN | OurPredictorLSTMPredictor | | Spring | 0.0690.3040.213 | 0.0910.360 | | Gravity | 0.0090.0380.038 | 0.0100.057 | | MagneticBilliards | 0.1180.4170.455 | 0.1650.354 | | Billiards | 0.1790.4700.395 | 0.2230.411 |
0
| 3-objectdatasets | VINVisualLSTMVisualRNN | VINfromStateLSTMfromState | | --- | --- | --- | | Spring | 1.8313.2721.646 | 0.4261.844 | | Gravity | 1.2881.5721.194 | 0.1460.191 | | MagneticBilliards | 1.8782.9111.792 | 0.4541.863 | | Billiards | 1.6002.7521.391 | 0.9422.507 |
| Drift | 2.9203.6632.474 | 0.00170.0052 | | --- | --- | --- | | | | | | 6-objectdatasets | VINVisualLSTMVisualRNN | VINfromStateLSTMfromState | | Spring | 0.6080.8580.565 | 0.2350.324 | | Gravity | 0.4220.5970.416 | 0.0920.157 | | MagneticBilliards | 0.8361.3740.750 | 0.3490.791 | | Billiards | 1.0222.5820.918 | 0.8171.919 | | Drift | 0.8311.0830.749 | 0.00250.0069 |
1
| 3-objectdatasets | VINVisualLSTMVisualRNN | VINfromStateLSTMfromState | | --- | --- | --- | | Spring | 1.8313.2721.646 | 0.4261.844 | | Gravity | 1.2881.5721.194 | 0.1460.191 | | MagneticBilliards | 1.8782.9111.792 | 0.4541.863 | | Billiards | 1.6002.7521.391 | 0.9422.507 |
| Euclideandeviationperobjectafterfullframewidthistravelled | | | | --- | --- | --- | | | OurModelVisualLSTMVisualRNN | OurPredictorLSTMPredictor | | Spring | 0.0690.3040.213 | 0.0910.360 | | Gravity | 0.0090.0380.038 | 0.0100.057 | | MagneticBilliards | 0.1180.4170.455 | 0.1650.354 | | Billiards | 0.1790.4700.395 | 0.2230.411 |
0
| | a1 | A2:K | 1<br>M | 2:K<br>M | B | | --- | --- | --- | --- | --- | --- | | K-means | 0.567 | 0.669 | 0.120 | 0.442 | - |
| VCA | 0.547 | 0.481 | 0.517 | 0.248 | - | | --- | --- | --- | --- | --- | --- | | NMF | 0.512 | 0.558 | 0.517 | 0.133 | - | | LMM | 0.437 | 0.473 | 0.349 | 0.148 | - | | SLMM | 0.359 | 0.495 | 0.009 | 0.128 | 0.259 |
1
| | a1 | A2:K | 1<br>M | 2:K<br>M | B | | --- | --- | --- | --- | --- | --- | | K-means | 0.567 | 0.669 | 0.120 | 0.442 | - |
| | a1 | A2:K | 1<br>M | 2:K<br>M | B | | --- | --- | --- | --- | --- | --- | | K-means(×10) | 0.043 | 0.225 | 0.015 | 6.136 | - | | VCA(×10) | 0.667 | 1.817 | 0.093 | 1.301 | - | | NMF(×10) | 0.010 | 0.381 | 0.448 | 1.486 | - | | LMM(×10) | 3.791 | 0.043 | 0.602 | 1.469 | - | | SLMM(×10) | 1.270 | 0.312 | 0.003 | 0.098 | 2.261 |
0
| | a1 | A2:K | 1<br>M | 2:K<br>M | B | | --- | --- | --- | --- | --- | --- | | K-means | 0.567 | 0.669 | 0.120 | 0.442 | - |
| VCA | 0.547 | 0.481 | 0.517 | 0.248 | - | | --- | --- | --- | --- | --- | --- | | NMF | 0.512 | 0.558 | 0.517 | 0.133 | - | | LMM | 0.437 | 0.473 | 0.349 | 0.148 | - | | SLMM | 0.359 | 0.495 | 0.009 | 0.128 | 0.259 |
1
| | a1 | A2:K | 1<br>M | 2:K<br>M | B | | --- | --- | --- | --- | --- | --- | | K-means | 0.567 | 0.669 | 0.120 | 0.442 | - |
| VCA(×10) | 0.667 | 1.817 | 0.093 | 1.301 | - | | --- | --- | --- | --- | --- | --- | | NMF(×10) | 0.010 | 0.381 | 0.448 | 1.486 | - | | LMM(×10) | 3.791 | 0.043 | 0.602 | 1.469 | - | | SLMM(×10) | 1.270 | 0.312 | 0.003 | 0.098 | 2.261 |
0
| No. | ptsnum | BeltramiEquation | GeneralizedLaplace | | --- | --- | --- | --- | | collocation | EFG | collocation | EFG |
| 1 | 24<br>2<br>32<br>2<br>48<br>2<br>64 | 0.183<br>0.432<br>1.141<br>1.902 | 6.444<br>15.987<br>35.707<br>68.326 | 0.590<br>0.666<br>1.610<br>2.737 | 4.917<br>8.616<br>19.381<br>35.241 | | --- | --- | --- | --- | --- | --- | | 2 | 24<br>2<br>32<br>2<br>48<br>2<br>64 | 0.186<br>0.399<br>0.931<br>1.823 | 7.554<br>23.040<br>31.314<br>60.240 | 0.360<br>0.528<br>1.335<br>2.138 | 4.237<br>7.330<br>16.399<br>28.158 | | 3 | 1047<br>1807<br>4132<br>7185 | 0.317<br>0.744<br>1.847<br>3.236 | 13.788<br>22.611<br>61.306<br>112.171 | 0.573<br>0.987<br>2.206<br>4.042 | 7.135<br>12.436<br>29.526<br>50.446 |
1
| No. | ptsnum | BeltramiEquation | GeneralizedLaplace | | --- | --- | --- | --- | | collocation | EFG | collocation | EFG |
| No. | ptsnum | BeltramiEquation | GeneralizedLaplace | | | | --- | --- | --- | --- | --- | --- | | collocation | EFG | collocation | EFG | | | | 1 | 24<br>2<br>32<br>2<br>48<br>2<br>64 | 4.477E-05<br>2.384E-05<br>1.015E-05<br>7.254E-06 | 9.434E-04<br>5.332E-04<br>1.454E-04<br>1.087E-04 | 6.906E-04<br>3.839E-04<br>1.686E-04<br>9.599E-05 | 1.610E-01<br>1.287E-01<br>6.291E-02<br>4.055E-02 | | 2 | 24<br>2<br>32<br>2<br>48<br>2<br>64 | 2.980E-04<br>1.664E-04<br>4.348E-05<br>1.703E-05 | 3.665E-03<br>2.732E-03<br>1.241E-03<br>1.053E-03 | 1.660E-03<br>1.458E-03<br>3.923E-04<br>2.593E-04 | 4.188E-01<br>4.190E-01<br>3.992E-01<br>3.977E-01 | | 3 | 1047<br>1807<br>4132<br>7185 | 9.719E-05<br>7.198E-05<br>5.201E-05<br>3.491E-05 | 9.882E-05<br>5.451E-05<br>2.922E-05<br>2.005E-05 | 1.907E-05<br>1.007E-05<br>4.797E-06<br>2.813E-06 | 1.934E+00<br>1.691E+00<br>2.028E+00<br>1.840E+00 |
0
| No. | ptsnum | BeltramiEquation | GeneralizedLaplace | | | | --- | --- | --- | --- | --- | --- | | collocation | EFG | collocation | EFG | | | | 1 | 24<br>2<br>32<br>2<br>48<br>2<br>64 | 0.183<br>0.432<br>1.141<br>1.902 | 6.444<br>15.987<br>35.707<br>68.326 | 0.590<br>0.666<br>1.610<br>2.737 | 4.917<br>8.616<br>19.381<br>35.241 |
| 2 | 24<br>2<br>32<br>2<br>48<br>2<br>64 | 0.186<br>0.399<br>0.931<br>1.823 | 7.554<br>23.040<br>31.314<br>60.240 | 0.360<br>0.528<br>1.335<br>2.138 | 4.237<br>7.330<br>16.399<br>28.158 | | --- | --- | --- | --- | --- | --- | | 3 | 1047<br>1807<br>4132<br>7185 | 0.317<br>0.744<br>1.847<br>3.236 | 13.788<br>22.611<br>61.306<br>112.171 | 0.573<br>0.987<br>2.206<br>4.042 | 7.135<br>12.436<br>29.526<br>50.446 |
1
| No. | ptsnum | BeltramiEquation | GeneralizedLaplace | | | | --- | --- | --- | --- | --- | --- | | collocation | EFG | collocation | EFG | | | | 1 | 24<br>2<br>32<br>2<br>48<br>2<br>64 | 0.183<br>0.432<br>1.141<br>1.902 | 6.444<br>15.987<br>35.707<br>68.326 | 0.590<br>0.666<br>1.610<br>2.737 | 4.917<br>8.616<br>19.381<br>35.241 |
| 1 | 24<br>2<br>32<br>2<br>48<br>2<br>64 | 4.477E-05<br>2.384E-05<br>1.015E-05<br>7.254E-06 | 9.434E-04<br>5.332E-04<br>1.454E-04<br>1.087E-04 | 6.906E-04<br>3.839E-04<br>1.686E-04<br>9.599E-05 | 1.610E-01<br>1.287E-01<br>6.291E-02<br>4.055E-02 | | --- | --- | --- | --- | --- | --- | | 2 | 24<br>2<br>32<br>2<br>48<br>2<br>64 | 2.980E-04<br>1.664E-04<br>4.348E-05<br>1.703E-05 | 3.665E-03<br>2.732E-03<br>1.241E-03<br>1.053E-03 | 1.660E-03<br>1.458E-03<br>3.923E-04<br>2.593E-04 | 4.188E-01<br>4.190E-01<br>3.992E-01<br>3.977E-01 | | 3 | 1047<br>1807<br>4132<br>7185 | 9.719E-05<br>7.198E-05<br>5.201E-05<br>3.491E-05 | 9.882E-05<br>5.451E-05<br>2.922E-05<br>2.005E-05 | 1.907E-05<br>1.007E-05<br>4.797E-06<br>2.813E-06 | 1.934E+00<br>1.691E+00<br>2.028E+00<br>1.840E+00 |
0
| n=50 | n=100 | n=200 | | | | | | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | nopre-proc. | pre-proc. | nopre-proc. | pre-proc. | nopre-proc. | pre-proc. | max. | | | | | | | | | h | avg. | max. | avg. | max. | avg. | max. | avg. | max. | avg. | max. | avg. | max. | states | | 1 | 0 | 0.01 | 0 | 0.01 | 0 | 0.02 | 0 | 0.01 | 0 | 0.02 | 0 | 0.02 | 2 | | 2 | 0 | 0.01 | 0 | 0 | 0 | 0.04 | 0 | 0.02 | 0 | 0.05 | 0 | 0.03 | 6 | | 3 | 0 | 0.01 | 0 | 0 | 0.01 | 0.01 | 0 | 0.02 | 0.01 | 0.02 | 0.01 | 0.06 | 24 | | 4 | 0.02 | 0.04 | 0.01 | 0.01 | 0.04 | 0.06 | 0.02 | 0.03 | 0.08 | 0.11 | 0.04 | 0.06 | 112 | | 5 | 0.12 | 0.18 | 0.05 | 0.08 | 0.27 | 0.33 | 0.12 | 0.18 | 0.51 | 0.65 | 0.27 | 0.4 | 568 | | 6 | 0.76 | 1.09 | 0.26 | 0.42 | 1.72 | 2.52 | 0.78 | 1.23 | 3.56 | 4.84 | 1.78 | 2.73 | 3032 |
| 7 | 4.67 | 8.13 | 1.32 | 3.38 | 12.18 | 16.27 | 4.93 | 7.17 | 25.71 | 27.89 | 13.45 | 15.06 | 16768 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 8 | 42.18 | 72.01 | 7.66 | 19.74 | 114.11 | 136.28 | 50.78 | 69.6 | 242.49 | 269.56 | 116.55 | 131.73 | 95200 |
1
| n=50 | n=100 | n=200 | | | | | | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | nopre-proc. | pre-proc. | nopre-proc. | pre-proc. | nopre-proc. | pre-proc. | max. | | | | | | | | | h | avg. | max. | avg. | max. | avg. | max. | avg. | max. | avg. | max. | avg. | max. | states | | 1 | 0 | 0.01 | 0 | 0.01 | 0 | 0.02 | 0 | 0.01 | 0 | 0.02 | 0 | 0.02 | 2 | | 2 | 0 | 0.01 | 0 | 0 | 0 | 0.04 | 0 | 0.02 | 0 | 0.05 | 0 | 0.03 | 6 | | 3 | 0 | 0.01 | 0 | 0 | 0.01 | 0.01 | 0 | 0.02 | 0.01 | 0.02 | 0.01 | 0.06 | 24 | | 4 | 0.02 | 0.04 | 0.01 | 0.01 | 0.04 | 0.06 | 0.02 | 0.03 | 0.08 | 0.11 | 0.04 | 0.06 | 112 | | 5 | 0.12 | 0.18 | 0.05 | 0.08 | 0.27 | 0.33 | 0.12 | 0.18 | 0.51 | 0.65 | 0.27 | 0.4 | 568 | | 6 | 0.76 | 1.09 | 0.26 | 0.42 | 1.72 | 2.52 | 0.78 | 1.23 | 3.56 | 4.84 | 1.78 | 2.73 | 3032 |
| n=50 | n=100 | n=200 | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | | h | avg. | max. | avg. | max. | avg. | max. | max.states | | 1 | 0 | 0.01 | 0 | 0.01 | 0 | 0.01 | 2 | | 2 | 0 | 0.01 | 0 | 0.01 | 0 | 0.01 | 5 | | 3 | 0 | 0.01 | 0 | 0.01 | 0.01 | 0.01 | 15 | | 4 | 0 | 0.01 | 0.01 | 0.01 | 0.02 | 0.03 | 51 | | 5 | 0.01 | 0.02 | 0.04 | 0.06 | 0.09 | 0.12 | 188 | | 6 | 0.03 | 0.05 | 0.15 | 0.21 | 0.36 | 0.5 | 731 | | 7 | 0.11 | 0.19 | 0.58 | 0.98 | 1.55 | 2.35 | 2950 | | 8 | 0.36 | 0.57 | 2.3 | 3.9 | 7.16 | 8.03 | 12235 | | 9 | 1.2 | 2.4 | 10.74 | 13.8 | 33.97 | 55.2 | 51822 | | 10 | 4,46 | 14.05 | 49.63 | 87.13 | - | - | 222616 | | 11 | 16,92 | 52.41 | - | - | - | - | 771128 |
0
| n=50 | n=100 | n=200 | | | | | | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | nopre-proc. | pre-proc. | nopre-proc. | pre-proc. | nopre-proc. | pre-proc. | max. | | | | | | | | | h | avg. | max. | avg. | max. | avg. | max. | avg. | max. | avg. | max. | avg. | max. | states | | 1 | 0 | 0.01 | 0 | 0.01 | 0 | 0.02 | 0 | 0.01 | 0 | 0.02 | 0 | 0.02 | 2 | | 2 | 0 | 0.01 | 0 | 0 | 0 | 0.04 | 0 | 0.02 | 0 | 0.05 | 0 | 0.03 | 6 | | 3 | 0 | 0.01 | 0 | 0 | 0.01 | 0.01 | 0 | 0.02 | 0.01 | 0.02 | 0.01 | 0.06 | 24 | | 4 | 0.02 | 0.04 | 0.01 | 0.01 | 0.04 | 0.06 | 0.02 | 0.03 | 0.08 | 0.11 | 0.04 | 0.06 | 112 | | 5 | 0.12 | 0.18 | 0.05 | 0.08 | 0.27 | 0.33 | 0.12 | 0.18 | 0.51 | 0.65 | 0.27 | 0.4 | 568 |
| 6 | 0.76 | 1.09 | 0.26 | 0.42 | 1.72 | 2.52 | 0.78 | 1.23 | 3.56 | 4.84 | 1.78 | 2.73 | 3032 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 7 | 4.67 | 8.13 | 1.32 | 3.38 | 12.18 | 16.27 | 4.93 | 7.17 | 25.71 | 27.89 | 13.45 | 15.06 | 16768 | | 8 | 42.18 | 72.01 | 7.66 | 19.74 | 114.11 | 136.28 | 50.78 | 69.6 | 242.49 | 269.56 | 116.55 | 131.73 | 95200 |
1
| n=50 | n=100 | n=200 | | | | | | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | nopre-proc. | pre-proc. | nopre-proc. | pre-proc. | nopre-proc. | pre-proc. | max. | | | | | | | | | h | avg. | max. | avg. | max. | avg. | max. | avg. | max. | avg. | max. | avg. | max. | states | | 1 | 0 | 0.01 | 0 | 0.01 | 0 | 0.02 | 0 | 0.01 | 0 | 0.02 | 0 | 0.02 | 2 | | 2 | 0 | 0.01 | 0 | 0 | 0 | 0.04 | 0 | 0.02 | 0 | 0.05 | 0 | 0.03 | 6 | | 3 | 0 | 0.01 | 0 | 0 | 0.01 | 0.01 | 0 | 0.02 | 0.01 | 0.02 | 0.01 | 0.06 | 24 | | 4 | 0.02 | 0.04 | 0.01 | 0.01 | 0.04 | 0.06 | 0.02 | 0.03 | 0.08 | 0.11 | 0.04 | 0.06 | 112 | | 5 | 0.12 | 0.18 | 0.05 | 0.08 | 0.27 | 0.33 | 0.12 | 0.18 | 0.51 | 0.65 | 0.27 | 0.4 | 568 |
| 10 | 4,46 | 14.05 | 49.63 | 87.13 | - | - | 222616 | | --- | --- | --- | --- | --- | --- | --- | --- | | 11 | 16,92 | 52.41 | - | - | - | - | 771128 |
0
| Senoneset | Architecture | devsetWER | testWER | | --- | --- | --- | --- | | 9k | BLSTM<br>ResNet<br>LACE<br>CNN-BLSTM<br>BLSTM+ResNet+LACE<br>BLSTM+ResNet+LACE+CNN-BLSTM | 11.5<br>10.0<br>11.2<br>11.3<br>9.8<br>9.6 | 8.3<br>8.2<br>8.1<br>8.4<br>7.2<br>7.2 |
| 9kpuhpum | BLSTM<br>ResNet<br>LACE<br>CNN-BLSTM<br>BLSTM+ResNet+LACE<br>BLSTM+ResNet+LACE+CNN-BLSTM | 11.3<br>11.2<br>11.1<br>11.6<br>9.7<br>9.7 | 8.1<br>8.4<br>8.3<br>8.4<br>7.4<br>7.3 | | --- | --- | --- | --- | | 27k | BLSTM<br>ResNet<br>LACE<br>BLSTM+ResNet+LACE | 11.4<br>11.5<br>11.3<br>10.0 | 8.0<br>8.8<br>8.8<br>7.5 | | 27kpuhpum | BLSTM<br>ResNet<br>LACE<br>BLSTM+ResNet+LACE | 11.3<br>11.2<br>11.0<br>9.8 | 8.0<br>8.0<br>8.4<br>7.3 |
1
| Senoneset | Architecture | devsetWER | testWER | | --- | --- | --- | --- | | 9k | BLSTM<br>ResNet<br>LACE<br>CNN-BLSTM<br>BLSTM+ResNet+LACE<br>BLSTM+ResNet+LACE+CNN-BLSTM | 11.5<br>10.0<br>11.2<br>11.3<br>9.8<br>9.6 | 8.3<br>8.2<br>8.1<br>8.4<br>7.2<br>7.2 |
| Category | Code | Method | n4 | s4 | n3 | s3 | n | s | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | Centrality | OR1R<br>OR2<br>OR2R<br>OR3R<br>OR4 | leastsimilartocentroid<br>highestlexrank<br>smallestlexrank<br>smallcluster<br>tfidf | 308<br>302<br>317<br>468<br>474 | -2.73<br>1.39<br>-0.61<br>-4.40<br>-4.93 | 453<br>457<br>450<br>581<br>596 | -2.14<br>1.11<br>-0.58<br>-3.94<br>-4.36 | 846<br>846<br>846<br>848<br>850 | -1.26<br>0.59<br>-0.29<br>-2.85<br>-3.24 | | NewYorker | NY1<br>NY2<br>NY3 | officialwinner<br>officialrunnerup<br>officialthirdplace | 314<br>330<br>276 | 3.57<br>3.24<br>2.29 | 466<br>463<br>435 | 2.96<br>2.60<br>1.57 | 847<br>845<br>842 | 1.78<br>1.54<br>0.89 | | General | GE1<br>GE2<br>GE3R | syntacticallycomplex<br>concrete<br>wellformatted | 268<br>259<br>296 | -0.10<br>-0.33<br>0.81 | 406<br>427<br>446 | -0.14<br>-0.41<br>0.61 | 846<br>844<br>846 | -0.70<br>-0.26<br>0.31 | | Content | CU1<br>CU2<br>CU2R<br>CU3 | freebase<br>positivesentiment<br>negativesentiment<br>people | 290<br>268<br>298<br>276 | 0.26<br>1.21<br>1.69<br>1.45 | 424<br>396<br>445<br>409 | 0.17<br>0.83<br>1.30<br>1.24 | 840<br>836<br>826<br>834 | 0.07<br>0.46<br>0.70<br>0.68 | | Control | CO2 | antijoke | 259 | 0.27 | 394 | -0.04 | 822 | -0.09 |
0
| Senoneset | Architecture | devsetWER | testWER | | --- | --- | --- | --- | | 9k | BLSTM<br>ResNet<br>LACE<br>CNN-BLSTM<br>BLSTM+ResNet+LACE<br>BLSTM+ResNet+LACE+CNN-BLSTM | 11.5<br>10.0<br>11.2<br>11.3<br>9.8<br>9.6 | 8.3<br>8.2<br>8.1<br>8.4<br>7.2<br>7.2 | | 9kpuhpum | BLSTM<br>ResNet<br>LACE<br>CNN-BLSTM<br>BLSTM+ResNet+LACE<br>BLSTM+ResNet+LACE+CNN-BLSTM | 11.3<br>11.2<br>11.1<br>11.6<br>9.7<br>9.7 | 8.1<br>8.4<br>8.3<br>8.4<br>7.4<br>7.3 |
| 27k | BLSTM<br>ResNet<br>LACE<br>BLSTM+ResNet+LACE | 11.4<br>11.5<br>11.3<br>10.0 | 8.0<br>8.8<br>8.8<br>7.5 | | --- | --- | --- | --- | | 27kpuhpum | BLSTM<br>ResNet<br>LACE<br>BLSTM+ResNet+LACE | 11.3<br>11.2<br>11.0<br>9.8 | 8.0<br>8.0<br>8.4<br>7.3 |
1
| Senoneset | Architecture | devsetWER | testWER | | --- | --- | --- | --- | | 9k | BLSTM<br>ResNet<br>LACE<br>CNN-BLSTM<br>BLSTM+ResNet+LACE<br>BLSTM+ResNet+LACE+CNN-BLSTM | 11.5<br>10.0<br>11.2<br>11.3<br>9.8<br>9.6 | 8.3<br>8.2<br>8.1<br>8.4<br>7.2<br>7.2 | | 9kpuhpum | BLSTM<br>ResNet<br>LACE<br>CNN-BLSTM<br>BLSTM+ResNet+LACE<br>BLSTM+ResNet+LACE+CNN-BLSTM | 11.3<br>11.2<br>11.1<br>11.6<br>9.7<br>9.7 | 8.1<br>8.4<br>8.3<br>8.4<br>7.4<br>7.3 |
| General | GE1<br>GE2<br>GE3R | syntacticallycomplex<br>concrete<br>wellformatted | 268<br>259<br>296 | -0.10<br>-0.33<br>0.81 | 406<br>427<br>446 | -0.14<br>-0.41<br>0.61 | 846<br>844<br>846 | -0.70<br>-0.26<br>0.31 | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | Content | CU1<br>CU2<br>CU2R<br>CU3 | freebase<br>positivesentiment<br>negativesentiment<br>people | 290<br>268<br>298<br>276 | 0.26<br>1.21<br>1.69<br>1.45 | 424<br>396<br>445<br>409 | 0.17<br>0.83<br>1.30<br>1.24 | 840<br>836<br>826<br>834 | 0.07<br>0.46<br>0.70<br>0.68 | | Control | CO2 | antijoke | 259 | 0.27 | 394 | -0.04 | 822 | -0.09 |
0
| Pr.No. | Median | Median | Median | LLEvals | | --- | --- | --- | --- | --- | | ULAccuracy | LLAccuracy | LLCalls | | | | SMD1 | 0.000247 | 0.000143 | 4686 | 995.52 | | SMD2 | 0.000146 | 0.000169 | 3866 | 921.23 | | SMD3 | 0.000442 | 0.000155 | 4494 | 1110.03 |
| SMD4 | 0.000526 | 0.000171 | 3250 | 749.48 | | --- | --- | --- | --- | --- | | SMD5 | 0.000011 | 0.000013 | 7404 | 1206.62 | | SMD6 | 0.000745 | 0.000351 | 6874 | 1199.66 |
1
| Pr.No. | Median | Median | Median | LLEvals | | --- | --- | --- | --- | --- | | ULAccuracy | LLAccuracy | LLCalls | | | | SMD1 | 0.000247 | 0.000143 | 4686 | 995.52 | | SMD2 | 0.000146 | 0.000169 | 3866 | 921.23 | | SMD3 | 0.000442 | 0.000155 | 4494 | 1110.03 |
| Pr.No. | Median | Median | Median | LLEvals | | --- | --- | --- | --- | --- | | ULAccuracy | LLAccuracy | LLCalls | | | | SMD1 | 0.000036 | 0.000015 | 2639 | 641.39 | | SMD2 | 0.000006 | 0.000005 | 2387 | 652.39 | | SMD3 | 0.000064 | 0.000023 | 2390 | 617.64 | | SMD4 | 0.000028 | 0.000027 | 1687 | 672.60 | | SMD5 | 0.000004 | 0.000003 | 2966 | 681.37 | | SMD6 | 0.000157 | 0.000081 | 3301 | 746.07 |
0
| Pr.No. | Median | Median | Median | LLEvals | | --- | --- | --- | --- | --- | | ULAccuracy | LLAccuracy | LLCalls | | | | SMD1 | 0.000247 | 0.000143 | 4686 | 995.52 |
| SMD2 | 0.000146 | 0.000169 | 3866 | 921.23 | | --- | --- | --- | --- | --- | | SMD3 | 0.000442 | 0.000155 | 4494 | 1110.03 | | SMD4 | 0.000526 | 0.000171 | 3250 | 749.48 | | SMD5 | 0.000011 | 0.000013 | 7404 | 1206.62 | | SMD6 | 0.000745 | 0.000351 | 6874 | 1199.66 |
1
| Pr.No. | Median | Median | Median | LLEvals | | --- | --- | --- | --- | --- | | ULAccuracy | LLAccuracy | LLCalls | | | | SMD1 | 0.000247 | 0.000143 | 4686 | 995.52 |
| SMD2 | 0.000006 | 0.000005 | 2387 | 652.39 | | --- | --- | --- | --- | --- | | SMD3 | 0.000064 | 0.000023 | 2390 | 617.64 | | SMD4 | 0.000028 | 0.000027 | 1687 | 672.60 | | SMD5 | 0.000004 | 0.000003 | 2966 | 681.37 | | SMD6 | 0.000157 | 0.000081 | 3301 | 746.07 |
0
| dataset | algorithms | indexsize | | | | --- | --- | --- | --- | --- | | tree(hashtable) | graph | all | | | | SIFT1M | flann(16-tree) | 997.5MB | 0 | 997.5MB | | Efanna(16-tree,10-NN) | 283.3MB | 60.5MB | 343.8MB | | | GNNS(10-NN) | 0 | 60.5MB | 60.5MB | | | kGraph(10-NN) | 0 | 60.5MB | 60.5MB | | | IEH-LSH(32bit,10-NN) | 82.7MB | 60.5MB | 143.2MB | | | IEH-ITQ(32bit,10-NN) | 82.7MB | 60.5MB | 143.2MB | | | GIST1 | flann(16-tree) | 998.4MB | 0 | 998.4MB | | Efanna(16-tree,10-NN) | 287.7MB | 60.5MB | 348.2MB | | | GNNS(10-NN) | 0 | 60.5MB | 60.5MB | | | kGraph(10-NN) | 0 | 60.5MB | 60.5MB | |
| IEH-LSH(32bit,10-NN) | 82.7MB | 60.5MB | 143.2MB | | --- | --- | --- | --- | | IEH-ITQ(32bit,10-NN) | 82.7MB | 60.5MB | 143.2MB | | Theindexsizehereisthesizeinthememory,notthesizeonthedisk. | | | |
1
| dataset | algorithms | indexsize | | | | --- | --- | --- | --- | --- | | tree(hashtable) | graph | all | | | | SIFT1M | flann(16-tree) | 997.5MB | 0 | 997.5MB | | Efanna(16-tree,10-NN) | 283.3MB | 60.5MB | 343.8MB | | | GNNS(10-NN) | 0 | 60.5MB | 60.5MB | | | kGraph(10-NN) | 0 | 60.5MB | 60.5MB | | | IEH-LSH(32bit,10-NN) | 82.7MB | 60.5MB | 143.2MB | | | IEH-ITQ(32bit,10-NN) | 82.7MB | 60.5MB | 143.2MB | | | GIST1 | flann(16-tree) | 998.4MB | 0 | 998.4MB | | Efanna(16-tree,10-NN) | 287.7MB | 60.5MB | 348.2MB | | | GNNS(10-NN) | 0 | 60.5MB | 60.5MB | | | kGraph(10-NN) | 0 | 60.5MB | 60.5MB | |
| dataset | algorithms | indexsize | | | | --- | --- | --- | --- | --- | | tree(hashtable) | graph | all | | | | SIFT1M | flann(4-tree) | 261.2MB | 0 | 261.2MB | | Efanna(4-tree,40-NN) | 76.6MB | 182.8MB | 259.4MB | | | GNNS(60-NN) | 0 | 266.7MB | 266.7MB | | | IEH-ITQ(32bit,40-NN) | 82.7MB | 182.8MB | 265.5MB | | | GIST1 | flann(4-tree) | 261.2MB | 0 | 261.2MB | | Efanna(4-tree,40-NN) | 76.6MB | 182.8MB | 259.4MB | | | GNNS(60-NN) | 0 | 266.7MB | 266.7MB | | | IEH-ITQ(32bit,40-NN) | 82.7MB | 182.8MB | 265.5MB | | | Theindexsizehereisthesizeinthememory,notthesizeonthedisk. | | | | |
0
| dataset | algorithms | indexsize | | | | --- | --- | --- | --- | --- | | tree(hashtable) | graph | all | | | | SIFT1M | flann(16-tree) | 997.5MB | 0 | 997.5MB | | Efanna(16-tree,10-NN) | 283.3MB | 60.5MB | 343.8MB | | | GNNS(10-NN) | 0 | 60.5MB | 60.5MB | | | kGraph(10-NN) | 0 | 60.5MB | 60.5MB | | | IEH-LSH(32bit,10-NN) | 82.7MB | 60.5MB | 143.2MB | | | IEH-ITQ(32bit,10-NN) | 82.7MB | 60.5MB | 143.2MB | | | GIST1 | flann(16-tree) | 998.4MB | 0 | 998.4MB | | Efanna(16-tree,10-NN) | 287.7MB | 60.5MB | 348.2MB | | | GNNS(10-NN) | 0 | 60.5MB | 60.5MB | | | kGraph(10-NN) | 0 | 60.5MB | 60.5MB | | | IEH-LSH(32bit,10-NN) | 82.7MB | 60.5MB | 143.2MB | |
| IEH-ITQ(32bit,10-NN) | 82.7MB | 60.5MB | 143.2MB | | --- | --- | --- | --- | | Theindexsizehereisthesizeinthememory,notthesizeonthedisk. | | | |
1
| dataset | algorithms | indexsize | | | | --- | --- | --- | --- | --- | | tree(hashtable) | graph | all | | | | SIFT1M | flann(16-tree) | 997.5MB | 0 | 997.5MB | | Efanna(16-tree,10-NN) | 283.3MB | 60.5MB | 343.8MB | | | GNNS(10-NN) | 0 | 60.5MB | 60.5MB | | | kGraph(10-NN) | 0 | 60.5MB | 60.5MB | | | IEH-LSH(32bit,10-NN) | 82.7MB | 60.5MB | 143.2MB | | | IEH-ITQ(32bit,10-NN) | 82.7MB | 60.5MB | 143.2MB | | | GIST1 | flann(16-tree) | 998.4MB | 0 | 998.4MB | | Efanna(16-tree,10-NN) | 287.7MB | 60.5MB | 348.2MB | | | GNNS(10-NN) | 0 | 60.5MB | 60.5MB | | | kGraph(10-NN) | 0 | 60.5MB | 60.5MB | | | IEH-LSH(32bit,10-NN) | 82.7MB | 60.5MB | 143.2MB | |
| SIFT1M | flann(4-tree) | 261.2MB | 0 | 261.2MB | | --- | --- | --- | --- | --- | | Efanna(4-tree,40-NN) | 76.6MB | 182.8MB | 259.4MB | | | GNNS(60-NN) | 0 | 266.7MB | 266.7MB | | | IEH-ITQ(32bit,40-NN) | 82.7MB | 182.8MB | 265.5MB | | | GIST1 | flann(4-tree) | 261.2MB | 0 | 261.2MB | | Efanna(4-tree,40-NN) | 76.6MB | 182.8MB | 259.4MB | | | GNNS(60-NN) | 0 | 266.7MB | 266.7MB | | | IEH-ITQ(32bit,40-NN) | 82.7MB | 182.8MB | 265.5MB | | | Theindexsizehereisthesizeinthememory,notthesizeonthedisk. | | | | |
0
| Sensor | WiredKLJNKeyExchange | WirelessKeyExchange | | --- | --- | --- | | A | A={B,D}kljn | A={C,E,F,G,H,I,J}wireless | | B | B={A,E}kljn | B={C,D,F,G,H,I,J}wireless |
| C | C={D}kljn | C={A,B,E,F,G,H,I,J}wireless | | --- | --- | --- | | D | D={A,C,E}kljn | D={B,F,G,H,I,J}wireless | | E | E={B,D}kljn | E={A,C,F,G,H,I,J}wireless | | F | F={G}kljn | F={A,B,C,D,E,H,I,J}wireless | | G | G={F}kljn | G={A,B,C,D,E,H,I,J}wireless | | H | H=∅kljn | H={A,B,C,D,E,F,G,I,J}wireless | | I | I=∅kljn | I={A,B,C,D,E,F,G,H,J}wireless | | J | J=∅kljn | J={A,B,C,D,E,F,G,H,I}wireless |
1
| Sensor | WiredKLJNKeyExchange | WirelessKeyExchange | | --- | --- | --- | | A | A={B,D}kljn | A={C,E,F,G,H,I,J}wireless | | B | B={A,E}kljn | B={C,D,F,G,H,I,J}wireless |
| Timestep | Analogdata | Quantizeddata<br>M=5 | Quantizeddata<br>M=2 | | --- | --- | --- | --- | | t=1MI | Sensor2,7 | Sensor2,7 | Sensor2,7 | | t=1FI | Sensor2,7 | Sensor2,7 | Sensor2,7 | | t=3MI | Sensor8 | Sensor8 | Sensor2,7,14 | | t=3FI | Sensor8 | Sensor8 | Sensor2,7,9 | | t=8MI | Sensor16 | Sensor16 | Sensor10,16,21 | | t=8FI | Sensor15 | Sensor15 | Sensor10,16 |
0
| Sensor | WiredKLJNKeyExchange | WirelessKeyExchange | | --- | --- | --- | | A | A={B,D}kljn | A={C,E,F,G,H,I,J}wireless | | B | B={A,E}kljn | B={C,D,F,G,H,I,J}wireless | | C | C={D}kljn | C={A,B,E,F,G,H,I,J}wireless | | D | D={A,C,E}kljn | D={B,F,G,H,I,J}wireless | | E | E={B,D}kljn | E={A,C,F,G,H,I,J}wireless | | F | F={G}kljn | F={A,B,C,D,E,H,I,J}wireless | | G | G={F}kljn | G={A,B,C,D,E,H,I,J}wireless |
| H | H=∅kljn | H={A,B,C,D,E,F,G,I,J}wireless | | --- | --- | --- | | I | I=∅kljn | I={A,B,C,D,E,F,G,H,J}wireless | | J | J=∅kljn | J={A,B,C,D,E,F,G,H,I}wireless |
1
| Sensor | WiredKLJNKeyExchange | WirelessKeyExchange | | --- | --- | --- | | A | A={B,D}kljn | A={C,E,F,G,H,I,J}wireless | | B | B={A,E}kljn | B={C,D,F,G,H,I,J}wireless | | C | C={D}kljn | C={A,B,E,F,G,H,I,J}wireless | | D | D={A,C,E}kljn | D={B,F,G,H,I,J}wireless | | E | E={B,D}kljn | E={A,C,F,G,H,I,J}wireless | | F | F={G}kljn | F={A,B,C,D,E,H,I,J}wireless | | G | G={F}kljn | G={A,B,C,D,E,H,I,J}wireless |
| t=3MI | Sensor8 | Sensor8 | Sensor2,7,14 | | --- | --- | --- | --- | | t=3FI | Sensor8 | Sensor8 | Sensor2,7,9 | | t=8MI | Sensor16 | Sensor16 | Sensor10,16,21 | | t=8FI | Sensor15 | Sensor15 | Sensor10,16 |
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| UniqueActors | ExecutionTime(msec) | | | | | --- | --- | --- | --- | --- | | | Step-8 | Step-9 | | | | | MySQL | Neo4j | MySQL | Neo4j |
| 150 | 225 | 9616 | 1907 | 2403 | | --- | --- | --- | --- | --- | | 158 | 372 | 11700 | 2844 | 2925 | | 220 | 713 | 14655 | 6292 | 3664 | | 229 | 903 | 29520 | 6703 | 7380 | | 242 | 1403 | 48891 | 8453 | 12223 |
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| UniqueActors | ExecutionTime(msec) | | | | | --- | --- | --- | --- | --- | | | Step-8 | Step-9 | | | | | MySQL | Neo4j | MySQL | Neo4j |
| Entity | Ni | Vi | Mi | StructureType | | --- | --- | --- | --- | --- | | Account | 11446187 | 11446187 | 1 | Vestigial | | CPUHours | 11446187 | 11446187 | 2752964 | Identity | | DefaultDepartment | 11446187 | 11446187 | 1 | Vestigial | | JobName | 11446187 | 11446187 | 90491 | Organization | | JobNumber | 11446187 | 11446187 | 485212 | Identity | | MemoryUsage | 11446187 | 11446187 | 5241559 | Identity | | Priority | 11446187 | 11446187 | 1 | Vestigial | | TaskNumber | 11446187 | 11446187 | 7491889 | Identity | | UserName | 11446187 | 11446187 | 8388 | Organization |
0
| UniqueActors | ExecutionTime(msec) | | | | | --- | --- | --- | --- | --- | | | Step-8 | Step-9 | | | | | MySQL | Neo4j | MySQL | Neo4j | | 150 | 225 | 9616 | 1907 | 2403 | | 158 | 372 | 11700 | 2844 | 2925 | | 220 | 713 | 14655 | 6292 | 3664 |
| 229 | 903 | 29520 | 6703 | 7380 | | --- | --- | --- | --- | --- | | 242 | 1403 | 48891 | 8453 | 12223 |
1
| UniqueActors | ExecutionTime(msec) | | | | | --- | --- | --- | --- | --- | | | Step-8 | Step-9 | | | | | MySQL | Neo4j | MySQL | Neo4j | | 150 | 225 | 9616 | 1907 | 2403 | | 158 | 372 | 11700 | 2844 | 2925 | | 220 | 713 | 14655 | 6292 | 3664 |
| JobNumber | 11446187 | 11446187 | 485212 | Identity | | --- | --- | --- | --- | --- | | MemoryUsage | 11446187 | 11446187 | 5241559 | Identity | | Priority | 11446187 | 11446187 | 1 | Vestigial | | TaskNumber | 11446187 | 11446187 | 7491889 | Identity | | UserName | 11446187 | 11446187 | 8388 | Organization |
0
| HPE | Sleeve | Neckline | Pattern | Total | | --- | --- | --- | --- | --- | | Andrilukaetal.+K-Means | 24.1 | 26.6 | 34.2 | 28.3 |
| Sappetal.+K-Means | 22.9 | 27.9 | 40.5 | 30.4 | | --- | --- | --- | --- | --- | | YangandRamanan+K-Means | 38.3 | 25.7 | 22.6 | 28.9 | | Groundtruth+K-Means | 34.7 | 36.1 | 39.5 | 36.8 | | OurApproach | 55.6 | 68.8 | 80.8 | 68.4 |
1
| HPE | Sleeve | Neckline | Pattern | Total | | --- | --- | --- | --- | --- | | Andrilukaetal.+K-Means | 24.1 | 26.6 | 34.2 | 28.3 |
| HPE | Sleeve | Neckline | Pattern | Total | | --- | --- | --- | --- | --- | | Andrilukaetal.+K-Means | 27.5 | 31.7 | 27.6 | 28.9 | | Sappetal.+K-Means | 34.9 | 30.5 | 23.8 | 29.7 | | YangandRamanan+K-Means | 43.2 | 28.6 | 35.8 | 35.9 | | Groundtruth+K-Means | 31 | 29.8 | 26.1 | 28.9 | | OurApproach | 57.2 | 60.3 | 74.7 | 64.1 |
0
| HPE | Sleeve | Neckline | Pattern | Total | | --- | --- | --- | --- | --- | | Andrilukaetal.+K-Means | 24.1 | 26.6 | 34.2 | 28.3 | | Sappetal.+K-Means | 22.9 | 27.9 | 40.5 | 30.4 | | YangandRamanan+K-Means | 38.3 | 25.7 | 22.6 | 28.9 |
| Groundtruth+K-Means | 34.7 | 36.1 | 39.5 | 36.8 | | --- | --- | --- | --- | --- | | OurApproach | 55.6 | 68.8 | 80.8 | 68.4 |
1
| HPE | Sleeve | Neckline | Pattern | Total | | --- | --- | --- | --- | --- | | Andrilukaetal.+K-Means | 24.1 | 26.6 | 34.2 | 28.3 | | Sappetal.+K-Means | 22.9 | 27.9 | 40.5 | 30.4 | | YangandRamanan+K-Means | 38.3 | 25.7 | 22.6 | 28.9 |
| Sappetal.+K-Means | 34.9 | 30.5 | 23.8 | 29.7 | | --- | --- | --- | --- | --- | | YangandRamanan+K-Means | 43.2 | 28.6 | 35.8 | 35.9 | | Groundtruth+K-Means | 31 | 29.8 | 26.1 | 28.9 | | OurApproach | 57.2 | 60.3 | 74.7 | 64.1 |
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| | MusicalEnsembleGroup | NoMusicalEnsembleGroup | | | | | | --- | --- | --- | --- | --- | --- | --- | | | Human-like | Harmony | Melody | Human-like | Harmony | Melody |
| OdetoJoy<br>-Layered<br>HMM | 3.125 | 3.250 | 3.125 | 3.8 | 4.0 | 3.8 | | --- | --- | --- | --- | --- | --- | --- | | WeThree<br>Kings-<br>Layered<br>HMM | 3.500 | 3.125 | 3.125 | 2.4 | 1.8 | 2.2 | | Pachelbel’s<br>Canon-<br>TVAR(11) | 3.438 | 3.375 | 3.063 | 3.5 | 3.6 | 3.2 |
1
| | MusicalEnsembleGroup | NoMusicalEnsembleGroup | | | | | | --- | --- | --- | --- | --- | --- | --- | | | Human-like | Harmony | Melody | Human-like | Harmony | Melody |
| Piece | Thirds | Fourths/Fifths | Dissonant | | --- | --- | --- | --- | | Beethoven’sOdetoJoy | 0.0769 | 0.3427 | 0.1119 | | Beethoven’sOdetoJoy-LayeredHMM | 0.1266 | 0.2848 | 0.1709 | | WeThreeKings | 0.0757 | 0.2919 | 0.4324 | | WeThreeKings-LayeredHMM | 0.2054 | 0.2865 | 0.1784 | | Pachelbel’sCanon | 0.1497 | 0.2389 | 0.5191 | | Pachelbel’sCanon-TVAR(11) | 0.625 | 0.275 | 0.3000 |
0
| | MusicalEnsembleGroup | NoMusicalEnsembleGroup | | | | | | --- | --- | --- | --- | --- | --- | --- | | | Human-like | Harmony | Melody | Human-like | Harmony | Melody | | OdetoJoy<br>-Layered<br>HMM | 3.125 | 3.250 | 3.125 | 3.8 | 4.0 | 3.8 |
| WeThree<br>Kings-<br>Layered<br>HMM | 3.500 | 3.125 | 3.125 | 2.4 | 1.8 | 2.2 | | --- | --- | --- | --- | --- | --- | --- | | Pachelbel’s<br>Canon-<br>TVAR(11) | 3.438 | 3.375 | 3.063 | 3.5 | 3.6 | 3.2 |
1
| | MusicalEnsembleGroup | NoMusicalEnsembleGroup | | | | | | --- | --- | --- | --- | --- | --- | --- | | | Human-like | Harmony | Melody | Human-like | Harmony | Melody | | OdetoJoy<br>-Layered<br>HMM | 3.125 | 3.250 | 3.125 | 3.8 | 4.0 | 3.8 |
| WeThreeKings | 0.0757 | 0.2919 | 0.4324 | | --- | --- | --- | --- | | WeThreeKings-LayeredHMM | 0.2054 | 0.2865 | 0.1784 | | Pachelbel’sCanon | 0.1497 | 0.2389 | 0.5191 | | Pachelbel’sCanon-TVAR(11) | 0.625 | 0.275 | 0.3000 |
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| Shuttle | ImageObject | | --- | --- | | K=15,L=50 | K=15,L=50 | | k=5 | k=5 | | k=5 | k=5 | | k=5 | k=5 | | k=k=5reachcomp<br>λ=0.2 | k=k=5reachcomp<br>λ=0.2 | | k=5 | k=5 | | k=5 | k=5 | | k=k=5minmax<br>Banwidth=5,scale=0.2<br>GaussianKernel | k=k=5minmax<br>Banwidth=5,scale=0.2<br>GaussianKernel |
| k=5 | k=5 | | --- | --- | | h=1,c=0.1<br>GaussianKernel | h=1,c=0.1<br>GaussianKernel | | k=5,m=0.5 | k=5,m=0.5 | | k=5,\|S1\|=320,\|S2\|=2 | k=5,\|S1\|=320,\|S2\|=2 |
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| Shuttle | ImageObject | | --- | --- | | K=15,L=50 | K=15,L=50 | | k=5 | k=5 | | k=5 | k=5 | | k=5 | k=5 | | k=k=5reachcomp<br>λ=0.2 | k=k=5reachcomp<br>λ=0.2 | | k=5 | k=5 | | k=5 | k=5 | | k=k=5minmax<br>Banwidth=5,scale=0.2<br>GaussianKernel | k=k=5minmax<br>Banwidth=5,scale=0.2<br>GaussianKernel |
| Image | KernelSize,<br>Connectivity | Time | Upper-bound<br>SDBCMPLP-CP-v2 | Lower-bound<br>SDBCMPLP-CP-v2 | | --- | --- | --- | --- | --- | | “1234” | 3×3,23 | 20min<br>1hr<br>24hr | −601.31−601.31<br>−601.31−601.31<br>−601.31−601.31 | −601.42−601.31<br>−601.32−601.31<br>−601.31−601.31 | | “1234” | 5×5,70 | 20min<br>1hr<br>24hr | −550.99−550.81<br>−551.02−550.95<br>−551.02−551.02 | −551.84−551.87<br>−551.26−551.30<br>−551.02−551.06 | | “1234” | 7×7,136 | 20min<br>1hr<br>24hr | −478.07−474.19<br>−478.15−477.47<br>−478.16−477.84 | −479.82−500.90<br>−478.74−487.26<br>−478.16−480.46 | | “ABCD” | 3×3,23 | 20min<br>1hr<br>24hr | −524.60−524.60<br>−524.60−524.60<br>−524.60−524.60 | −524.74−524.60<br>−524.63−524.60<br>−524.60−524.60 | | “ABCD” | 5×5,70 | 20min<br>1hr<br>24hr | −452.60−452.33<br>−452.64−452.48<br>−452.64−452.64 | −453.63−456.18<br>−452.99−453.60<br>−452.64−452.69 | | “ABCD” | 7×7,136 | 20min<br>1hr<br>24hr | −416.63−410.82<br>−416.74−414.77<br>−416.77−416.29 | −418.73−452.00<br>−417.75−432.34<br>−416.78−422.12 |
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| Shuttle | ImageObject | | --- | --- | | K=15,L=50 | K=15,L=50 | | k=5 | k=5 | | k=5 | k=5 | | k=5 | k=5 | | k=k=5reachcomp<br>λ=0.2 | k=k=5reachcomp<br>λ=0.2 | | k=5 | k=5 | | k=5 | k=5 | | k=k=5minmax<br>Banwidth=5,scale=0.2<br>GaussianKernel | k=k=5minmax<br>Banwidth=5,scale=0.2<br>GaussianKernel | | k=5 | k=5 |
| h=1,c=0.1<br>GaussianKernel | h=1,c=0.1<br>GaussianKernel | | --- | --- | | k=5,m=0.5 | k=5,m=0.5 | | k=5,\|S1\|=320,\|S2\|=2 | k=5,\|S1\|=320,\|S2\|=2 |
1
| Shuttle | ImageObject | | --- | --- | | K=15,L=50 | K=15,L=50 | | k=5 | k=5 | | k=5 | k=5 | | k=5 | k=5 | | k=k=5reachcomp<br>λ=0.2 | k=k=5reachcomp<br>λ=0.2 | | k=5 | k=5 | | k=5 | k=5 | | k=k=5minmax<br>Banwidth=5,scale=0.2<br>GaussianKernel | k=k=5minmax<br>Banwidth=5,scale=0.2<br>GaussianKernel | | k=5 | k=5 |
| “ABCD” | 3×3,23 | 20min<br>1hr<br>24hr | −524.60−524.60<br>−524.60−524.60<br>−524.60−524.60 | −524.74−524.60<br>−524.63−524.60<br>−524.60−524.60 | | --- | --- | --- | --- | --- | | “ABCD” | 5×5,70 | 20min<br>1hr<br>24hr | −452.60−452.33<br>−452.64−452.48<br>−452.64−452.64 | −453.63−456.18<br>−452.99−453.60<br>−452.64−452.69 | | “ABCD” | 7×7,136 | 20min<br>1hr<br>24hr | −416.63−410.82<br>−416.74−414.77<br>−416.77−416.29 | −418.73−452.00<br>−417.75−432.34<br>−416.78−422.12 |
0