Papers with AutoSeM
AutoSeM: Automatic Task Selection and Mixing in Multi-Task Learning (N19-1)
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| Challenge: | Multi-task learning is an inductive transfer mechanism that leverages information from related tasks to improve the primary model's generalization performance. |
| Approach: | They propose a multitask learning pipeline that finds relevant auxiliary tasks and learns their mixing ratio. |
| Outcome: | The proposed model can find relevant auxiliary tasks and learn their mixing ratio . the proposed model achieves significant performance boosts on several primary tasks . |