Regression on E2006-log1p (test)
19.5CPU TimeAPG+
Evaluation Results
| Method | Links | ||||
|---|---|---|---|---|---|
| APG+Sparsity level (s)=0.01m2022.11 | 19.5 | 40 | 49 | 0.141 | |
| APG-LL+Sparsity level (s)=0.01m2022.11 | 41.2 | 142 | 38 | 0.142 | |
| APG+Sparsity level (s)=0.05m2022.11 | 105.6 | 222 | 124 | 0.132 | |
| APG-LL+Sparsity level (s)=0.05m2022.11 | 107.5 | 326 | 100 | 0.138 | |
| APGSparsity level (s)=0.01m2022.11 | 270.6 | 669 | 0 | 0.136 | |
| APGSparsity level (s)=0.05m2022.11 | 811.8 | 1,757 | 0 | 0.133 | |
| APG-LL+Sparsity level (s)=1.5m2022.11 | 1,362.7 | 1,744 | 94 | 0.313 | |
| APG-LL+Sparsity level (s)=2m2022.11 | 1,672.1 | 2,057 | 101 | 0.299 | |
| APG+Sparsity level (s)=1.5m2022.11 | 1,697.5 | 2,104 | 118 | 0.279 | |
| APG+Sparsity level (s)=2m2022.11 | 2,098.5 | 2,496 | 108 | 0.28 | |
| PG-LLSparsity level (s)=1.5m2022.11 | 2,398.6 | 3,002 | 0 | 0.231 | |
| PG-LLSparsity level (s)=2m2022.11 | 2,460.1 | 2,946 | 0 | 0.225 | |
| PG-LLSparsity level (s)=0.05m2022.11 | 2,696 | 7,086 | 0 | 0.132 | |
| PGSparsity level (s)=0.01m, Max iterations reached=true2022.11 | 2,998.6 | 10,000 | 0 | 0.167 | |
| PGSparsity level (s)=0.05m, Max iterations reached=true2022.11 | 3,644.1 | 10,000 | 0 | 0.161 | |
| APGSparsity level (s)=1.5m2022.11 | 5,686.2 | 6,781 | 0 | 0.209 | |
| PG-LLSparsity level (s)=0.01m, Max iterations reached=true2022.11 | 6,049.8 | 20,000 | 0 | 0.132 | |
| APGSparsity level (s)=2m2022.11 | 6,375.8 | 7,300 | 0 | 0.201 | |
| PGSparsity level (s)=1.5m2022.11 | 7,617.3 | 10,000 | 0 | 0.154 | |
| PGSparsity level (s)=2m2022.11 | 8,003 | 10,000 | 0 | 0.154 |