On Modification of an Adaptive Stochastic Mirror Descent Algorithm for Convex Optimization Problems with Functional Constraints

DOI10.1007/978-981-15-8498-5_3zbMath1486.90142arXiv1904.09513OpenAlexW2939708579MaRDI QIDQ5860603

Mohammad S. Alkousa

Publication date: 22 November 2021

Published in: Forum for Interdisciplinary Mathematics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1904.09513

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Convex programming (90C25) Stochastic programming (90C15) Stochastic approximation (62L20)

Cites Work

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• OSGA: a fast subgradient algorithm with optimal complexity
• A weighted mirror descent algorithm for nonsmooth convex optimization problem
• The CoMirror algorithm for solving nonsmooth constrained convex problems
• Lectures on convex optimization
• New method of stochastic approximation type
• Mirror descent and nonlinear projected subgradient methods for convex optimization.
• Mirror descent and constrained online optimization problems
• Algorithms for stochastic optimization with function or expectation constraints
• Mirror descent and convex optimization problems with non-smooth inequality constraints
• Lectures on Modern Convex Optimization
• Robust Stochastic Approximation Approach to Stochastic Programming
• Acceleration of Stochastic Approximation by Averaging
• Bregman Monotone Optimization Algorithms
• A Stochastic Approximation Method

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