Adaptive coordinate sampling for stochastic primal–dual optimization

DOI10.1111/itor.13011OpenAlexW3171848598MaRDI QIDQ6092496

Anthony Man-Cho So, Huikang Liu, Xiaolu Wang

Publication date: 23 November 2023

Published in: International Transactions in Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/itor.13011

zbMATH Keywords

machine learningadaptive importance samplingprimal-dual methodsstochastic optimization algorithms

Mathematics Subject Classification ID

Operations research, mathematical programming (90-XX)

Cites Work

• Unnamed Item
• Unnamed Item
• On optimal probabilities in stochastic coordinate descent methods
• On the complexity analysis of randomized block-coordinate descent methods
• A first-order primal-dual algorithm for convex problems with applications to imaging
• Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function
• Efficiency of Coordinate Descent Methods on Huge-Scale Optimization Problems
• A General Framework for a Class of First Order Primal-Dual Algorithms for Convex Optimization in Imaging Science
• Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization
• Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization

This page was built for publication: Adaptive coordinate sampling for stochastic primal–dual optimization