FullyUnconstrainedOnlineLearning

Neural Information Processing Systems 

We provide a technique for online convex optimization that obtains regret G w Tlog( w G T)+ w 2 +G2 on G-Lipschitz losses for any comparison pointw without knowing eitherG or w .

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