Image Classification on Caltech-256 (Efficiency Metrics)
3.16SpeedupInductive-SUBSELNET
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| Inductive-SUBSELNETRAR Target=20%2024.09 | 3.16 | 7,406.23 | |
| Transductive-SUBSELNETRAR Target=20%2024.09 | 3.12 | 7,747.82 | |
| Inductive-SUBSELNETRAR Target=10%2024.09 | 2.43 | 9,597.22 | |
| Bottom-b-loss+gumbelRAR Target=20%2024.09 | 2.36 | 9,510.12 | |
| Transductive-SUBSELNETRAR Target=10%2024.09 | 2.33 | 9,983.86 | |
| GradMatchRAR Target=20%2024.09 | 2.07 | 12,507.9 | |
| GLISTERRAR Target=20%2024.09 | 1.76 | 13,921.4 | |
| GradMatchRAR Target=10%2024.09 | 1.45 | 16,499.3 | |
| GLISTERRAR Target=10%2024.09 | 1.31 | 16,904.5 |