ICLR Optimization papers II

Critical Learning Periods in Deep Neural Networks


Measuring and regularizing networks in function space


On the Convergence of a Class of Adam-Type Algorithms for Non-Convex Optimization


Toward Understanding the Impact of Staleness in Distributed Machine Learning




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