Convergence and Dynamical Behavior of the ADAM Algorithm for Non-Convex Stochastic Optimization

4 Oct 2018 Anas Barakat Pascal Bianchi

Adam is a popular variant of stochastic gradient descent for finding a local minimizer of a function. In the constant stepsize regime, assuming that the objective function is differentiable and non-convex, we establish the convergence in the long run of the iterates to a stationary point under a stability condition... (read more)

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