The Marginal Value of Adaptive Gradient Methods in Machine Learning

NeurIPS 2017 Ashia C. WilsonRebecca RoelofsMitchell SternNathan SrebroBenjamin Recht

Adaptive optimization methods, which perform local optimization with a metric constructed from the history of iterates, are becoming increasingly popular for training deep neural networks. Examples include AdaGrad, RMSProp, and Adam... (read more)

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