Rate of convergence of the bundle method

DOI10.1007/s10957-017-1108-1zbMath1373.90102arXiv1609.00842OpenAlexW2963646419MaRDI QIDQ2412838

Yu Du, Ruszczyński, Andrzej

Publication date: 27 October 2017

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

Full work available at URL: https://arxiv.org/abs/1609.00842

zbMATH Keywords

nonsmooth optimizationbundle method

Mathematics Subject Classification ID

Convex programming (90C25)

Related Items (7)

Survey Descent: A Multipoint Generalization of Gradient Descent for Nonsmooth Optimization ⋮ A Unified Analysis of Descent Sequences in Weakly Convex Optimization, Including Convergence Rates for Bundle Methods ⋮ Revisiting Spectral Bundle Methods: Primal-Dual (Sub)linear Convergence Rates ⋮ Optimal Convergence Rates for the Proximal Bundle Method ⋮ General Hölder smooth convergence rates follow from specialized rates assuming growth bounds ⋮ Selective linearization for multi-block statistical learning ⋮ A Proximal Bundle Variant with Optimal Iteration-Complexity for a Large Range of Prox Stepsizes

Uses Software

• PLCP

Cites Work

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• Proximal level bundle methods for convex nondifferentiable optimization, saddle-point problems and variational inequalities
• New variants of bundle methods
• Methods of descent for nondifferentiable optimization
• Bundle-level type methods uniformly optimal for smooth and nonsmooth convex optimization
• An aggregate subgradient method for nonsmooth convex minimization
• A modification and an extension of Lemarechal’s algorithm for nonsmooth minimization
• Monotone Operators and the Proximal Point Algorithm
• Numerical optimization. Theoretical and practical aspects. Transl. from the French

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