Graphical Convergence of Subgradients in Nonconvex Optimization and Learning

17 Oct 2018Damek DavisDmitriy Drusvyatskiy

We investigate the stochastic optimization problem of minimizing population risk, where the loss defining the risk is assumed to be weakly convex. Compositions of Lipschitz convex functions with smooth maps are the primary examples of such losses... (read more)

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