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[PDF] Adam: A Method for Stochastic Optimization | Semantic Scholar
This work introduces Adam, an algorithm for first-order gradient-based optimization of stochastic objective functions, based on adaptive estimates of lower-order moments, and provides a regret bound on the convergence rate that is comparable to the best known results under the online convex optimization framework. We introduce Adam, an ...
Dec 22, 2014
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