Optimality of the final model found via Stochastic Gradient Descent

22 Oct 2018Andrea Schioppa

We study convergence properties of Stochastic Gradient Descent (SGD) for convex objectives without assumptions on smoothness or strict convexity. We consider the question of establishing that with high probability the objective evaluated at the candidate minimizer returned by SGD is close to the minimal value of the objective... (read more)

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