4f87658ef0de194413056248a00ce009-AuthorFeedback.pdf

However,lowering training loss may cause overfitting, especially when training data isscarce.9 In contrast, ARML is guaranteed to find a good prior so that the least data is required to find the parameter which10 generalizesthebest(i.e. Ideally, ARML can discard a harmful task by lowering its29 weightto0. Our37 true objective is to find the optimal task weightsα?