Adaptive Subgradient Methods for Online Learning and ...
tion, which significantly simplifies setting a learning rate and results in regret guarantees that are provably as good as the best proximal function that can be chosen in hindsight. We give several efficient algorithms for empirical risk minimization probl ems with common and important regu-larization functions and domain constraints.
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