Papers with Multi-task auxiliary learning

1 papers
Efficient Multi-Task Auxiliary Learning: Selecting Auxiliary Data by Feature Similarity (2021.emnlp-main)

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Challenge: Multi-task auxiliary learning uses a set of relevant auxiliary tasks to improve performance of a primary task.
Approach: They propose a time-efficient sampling method to select the most beneficial sub-datasets from the auxiliary tasks to achieve efficient multi-task auxiliary learning.
Outcome: The proposed method significantly outperforms random sampling and ST-DNN on three benchmark datasets.

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