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math.OC2022
Convergence of First-Order Methods for Constrained Nonconvex Optimization with Dependent Data
Ahmet Alacaoglu, Hanbaek Lyu
We focus on analyzing the classical stochastic projected gradient methods under a general dependent data sampling scheme for constrained smooth nonconvex optimization. We show the…
math.OC2022★ 1 cited
Stochastic regularized majorization-minimization with weakly convex and multi-convex surrogates
Hanbaek Lyu
Stochastic majorization-minimization (SMM) is a class of stochastic optimization algorithms that proceed by sampling new data points and minimizing a recursive average of surrogate…