Multi-Task Learning on Ridership
16.79Total LossOptimal
Evaluation results
| Method | Links | |
|---|---|---|
| Optimal#Groups=4, |Gtrain|=102026.02 | 16.79 | |
| Optimal#Groups=3, |Gtrain|=102026.02 | 16.9 | |
| Optimal#Groups=2, |Gtrain|=102026.02 | 17.03 | |
| TAG#Groups=2, |Gtrain|=102026.02 | 17.5 | |
| ETAP#Groups=4, |Gtrain|=102026.02 | 17.59 | |
| ETAPTask-group splits=42026.02 | 17.59 | |
| ETAP#Groups=2, |Gtrain|=102026.02 | 17.77 | |
| ETAPTask-group splits=22026.02 | 17.77 | |
| ETAP#Groups=3, |Gtrain|=102026.02 | 17.83 | |
| ETAPTask-group splits=32026.02 | 17.83 | |
| MTGNet#Groups=2, |Gtrain|=102026.02 | 17.86 | |
| GRAD-TAE#Groups=3, |Gtrain|=102026.02 | 17.94 | |
| MTGNet#Groups=4, |Gtrain|=102026.02 | 18.06 | |
| MTGNet#Groups=3, |Gtrain|=102026.02 | 18.12 | |
| TAG#Groups=4, |Gtrain|=102026.02 | 18.25 | |
| TAG#Groups=3, |Gtrain|=102026.02 | 18.31 | |
| GRAD-TAE#Groups=4, |Gtrain|=102026.02 | 18.45 | |
| GRAD-TAE#Groups=2, |Gtrain|=102026.02 | 18.48 | |
| PCGrad2026.02 | 18.84 | |
| Naive MTL2026.02 | 18.95 |