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Published in 2017 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2016.2527053
Abstract: In online convex optimization, adaptive algorithms, which can utilize the second-order information of the loss function’s (sub)gradient, have shown improvements over standard gradient methods. This paper presents a framework Follow the Bregman Divergence Leader that…
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Keywords:
note unification;
adaptive online;
online learning;
online ... See more keywords