A zeroth order method for stochastic weakly convex optimization
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Publication:2057220
DOI10.1007/s10589-021-00313-3zbMath1481.90236arXiv2002.08083OpenAlexW3198503994MaRDI QIDQ2057220
Publication date: 8 December 2021
Published in: Computational Optimization and Applications (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2002.08083
Numerical mathematical programming methods (65K05) Derivative-free methods and methods using generalized derivatives (90C56) Stochastic programming (90C15)
Related Items (2)
A Zeroth-Order Proximal Stochastic Gradient Method for Weakly Convex Stochastic Optimization ⋮ Adaptive sampling quasi-Newton methods for zeroth-order stochastic optimization
Cites Work
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- Benchmarking Derivative-Free Optimization Algorithms
- Derivative-free optimization methods
- Proximally Guided Stochastic Subgradient Method for Nonsmooth, Nonconvex Problems
- Stochastic First- and Zeroth-Order Methods for Nonconvex Stochastic Programming
- Simulation optimization: a review of algorithms and applications
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