Papers with transductive auxiliary task
Transductive Auxiliary Task Self-Training for Neural Multi-Task Models (D19-61)
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| Challenge: | Multi-task learning and self-training are two common ways to improve a machine learning model’s performance in settings with limited training data. |
| Approach: | They propose a transductive auxiliary task self-training procedure that trains a model on auxiliary tasks and test instances with auxiliary labels generated by a single-task version of the model. |
| Outcome: | The proposed method improves accuracy by 9.56% over the pure multi-task model for dependency relation tagging and 13.03% for semantic taging. |