A Zeroth-Order Proximal Stochastic Gradient Method for Weakly Convex Stochastic Optimization
Author:
Affiliation:
1. School of Science and Engineering, University of Dundee, Dundee, Scotland DD1 4HR, UK.
2. Department of Electrical Engineering, Yale University, New Haven, CT 06511 USA ().
Publisher
Society for Industrial & Applied Mathematics (SIAM)
Subject
Applied Mathematics,Computational Mathematics
Reference45 articles.
1. Pattern Search Methods for User-Provided Points: Application to Molecular Geometry Problems
2. Finding Optimal Algorithmic Parameters Using Derivative‐Free Optimization
3. Convergence of a random optimization method for constrained optimization problems
4. Zeroth-Order Nonconvex Stochastic Optimization: Handling Constraints, High Dimensionality, and Saddle Points
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