Sparse Logistic Regression on Synthetic Logistic regression
0Gap (%)OKGLM
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| OKGLMp=16K2026.05 | 0 | 7,790 | 3,821 | |
| GPU-Parallel BnBp=16K2026.05 | 0 | 100.8 | 3,865 | |
| GPU-Parallel BnBp=8K2026.05 | 0 | 93.5 | 12,939 | |
| OKGLMp=4K2026.05 | 0 | 10,361 | 25,477 | |
| GPU-Parallel BnBp=4K2026.05 | 0 | 80.4 | 26,861 | |
| GPU-Parallel BnBp=2K2026.05 | 0 | 160.7 | 122,299 | |
| GPU-Parallel BnBp=1K2026.05 | 0 | 473.5 | 742,719 | |
| GPU-Parallel BnBp=5002026.05 | 0 | 4,348 | 3,763,479 | |
| MOSEKp=5002026.05 | 6.74 | — | 228,302 | |
| MOSEKp=1K2026.05 | 9.42 | — | 38,517 | |
| MOSEKp=2K2026.05 | 10.31 | — | 4,824 | |
| MOSEKp=4K2026.05 | 10.63 | — | 1,057 | |
| OKGLMp=8K2026.05 | 23.63 | — | 10,885 | |
| Gurobip=5002026.05 | 27.54 | — | 821,898 | |
| Gurobip=16K2026.05 | 32.52 | — | 55,063 | |
| Gurobip=8K2026.05 | 38.81 | — | 160,008 | |
| Gurobip=1K2026.05 | 41.93 | — | 521,731 | |
| Gurobip=2K2026.05 | 48.42 | — | 518,798 | |
| Gurobip=4K2026.05 | 50.05 | — | 552,994 | |
| OKGLMp=2K2026.05 | 55.49 | — | 29,691 | |
| OKGLMp=5002026.05 | 69.6 | — | 45,117 | |
| OKGLMp=1K2026.05 | 70.07 | — | 38,610 |