Model-Protected Multi-Task Learning

Multi-task learning (MTL) refers to the paradigm of learning multiple related tasks together. In contrast, in single-task learning (STL) each individual task is learned independently. MTL often leads to better-trained models because they can leverage the commonalities among related tasks. However, because MTL algorithms can ``leak" inform...More