Mirror Prox algorithm for multi-term composite minimization and semi-separable problems

DOI10.1007/s10589-014-9723-3zbMath1321.65105arXiv1311.1098OpenAlexW2154319048WikidataQ57392873 ScholiaQ57392873MaRDI QIDQ2350862

Niao He, Arkadi Nemirovski, Anatoli B. Juditsky

Publication date: 25 June 2015

Published in: Computational Optimization and Applications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1311.1098

zbMATH Keywords

algorithmsminimization problemsvariational problemscomplexity boundmonotone variational inequalitiesnuclear norm regularizationproximal methodscomposite optimizationalternating directions methodconvex-concave saddle point problemslasso-type problemmulti-term penalty

Mathematics Subject Classification ID

Convex programming (90C25) Large-scale problems in mathematical programming (90C06) Minimax problems in mathematical programming (90C47) Variational inequalities (49J40) Complexity and performance of numerical algorithms (65Y20) Numerical methods for variational inequalities and related problems (65K15)

Related Items

Optimal Algorithms for Non-Smooth Distributed Optimization in Networks, On iteration complexity of a first-order primal-dual method for nonlinear convex cone programming, A fast dual proximal-gradient method for separable convex optimization with linear coupled constraints, Accelerated gradient sliding for structured convex optimization, A stochastic variance-reduced accelerated primal-dual method for finite-sum saddle-point problems, Primal-dual proximal splitting and generalized conjugation in non-smooth non-convex optimization, Proximal primal-dual best approximation algorithm with memory, Point process estimation with Mirror Prox algorithms, A Distributed ADMM-like Method for Resource Sharing over Time-Varying Networks, Optimal subgradient methods: computational properties for large-scale linear inverse problems, A Primal-Dual Algorithm with Line Search for General Convex-Concave Saddle Point Problems

Uses Software

• CVX
• Mosek
• NESTA

Cites Work

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