Gradient Projection and Conditional Gradient Methods for Constrained Nonconvex Minimization

DOI10.1080/01630563.2019.1704780zbMath1437.49024arXiv1906.11580OpenAlexW3000303000WikidataQ126397729 ScholiaQ126397729MaRDI QIDQ5222248

A. A. Tremba, Maxim V. Balashov, Boris T. Polyak

Publication date: 1 April 2020

Published in: Numerical Functional Analysis and Optimization (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1906.11580

zbMATH Keywords

nonconvex optimizationFrank-Wolfe methodgradient projection methodsmooth functionsstrongly convex setproximally smooth setminimization on a sphereLežanski-Polyak-Lojasiewicz condition

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26) Numerical optimization and variational techniques (65K10) Set-valued and variational analysis (49J53) Methods involving semicontinuity and convergence; relaxation (49J45) Applications of functional analysis in optimization, convex analysis, mathematical programming, economics (46N10) Methods of reduced gradient type (90C52)

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