A proximal-Newton method for unconstrained convex optimization in Hilbert spaces

DOI10.1080/02331934.2017.1389942zbMath1398.90120OpenAlexW2766232439MaRDI QIDQ4639119

Unnamed Author, Benar Fux Svaiter

Publication date: 3 May 2018

Published in: Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331934.2017.1389942

zbMATH Keywords

complexitysmooth convex optimizationproximal point methodsproximal-Newton method

Mathematics Subject Classification ID

Convex programming (90C25) Methods of quasi-Newton type (90C53) Programming in abstract spaces (90C48)

Related Items

Parallel proximal method of solving split system of fixed point set constraint minimization problems

Cites Work

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• A hybrid approximate extragradient-proximal point algorithm using the enlargement of a maximal monotone operator
• Cubic regularization of Newton method and its global performance
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• An Accelerated Hybrid Proximal Extragradient Method for Convex Optimization and Its Implications to Second-Order Methods
• On the Complexity of the Hybrid Proximal Extragradient Method for the Iterates and the Ergodic Mean
• Complexity of Variants of Tseng's Modified F-B Splitting and Korpelevich's Methods for Hemivariational Inequalities with Applications to Saddle-point and Convex Optimization Problems
• Monotone Operators and the Proximal Point Algorithm
• Iteration-Complexity of a Newton Proximal Extragradient Method for Monotone Variational Inequalities and Inclusion Problems

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