Gradient methods with regularization for constrained optimization problems and their complexity estimates

DOI10.1080/02331934.2017.1416612zbMath1401.90155arXiv1705.01396OpenAlexW2610358364MaRDI QIDQ4643688

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Publication date: 28 May 2018

Published in: Optimization (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1705.01396

zbMATH Keywords

strong convergenceconvex optimizationHilbert spacecomplexity estimatesconditional gradient methodgradient projection method

Mathematics Subject Classification ID

Convex programming (90C25) Abstract computational complexity for mathematical programming problems (90C60) Programming in abstract spaces (90C48)

Cites Work

• Convergence Rates for Conditional Gradient Sequences Generated by Implicit Step Length Rules
• The Method of Pairwise Variations with Tolerances for Linearly Constrained Optimization Problems
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