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Applied Math Seminar: Michael Murray (UCLA)
Applied Math Seminar: Michael Murray (UCLA)
Title: Towards Understanding the Success of First Order Methods in Training Mildly Overparameterized Networks Abstract: For most problems of interest the loss landscape of a neural network is non-convex and contains a plethora of spurious critical points. Despite this first order methods such as SGD and Adam are in practice remarkably successful at finding optimal, […]