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math.OC2020
SGD for Structured Nonconvex Functions: Learning Rates, Minibatching and Interpolation
Robert M. Gower, Othmane Sebbouh, Nicolas Loizou
Stochastic Gradient Descent (SGD) is being used routinely for optimizing non-convex functions. Yet, the standard convergence theory for SGD in the smooth non-convex setting gives a…
math.OC2019
Nesterov's acceleration and Polyak's heavy ball method in continuous time: convergence rate analysis under geometric conditions and perturbations
Othmane Sebbouh, Charles Dossal, Aude Rondepierre
In this article a family of second order ODEs associated to inertial gradient descend is studied. These ODEs are widely used to build trajectories converging to a minimizer o…