Inexact proximal \(\epsilon\)-subgradient methods for composite convex optimization problems
From MaRDI portal
Publication:2010107
DOI10.1007/s10898-019-00808-8zbMath1461.65176arXiv1805.10120OpenAlexW2964186284MaRDI QIDQ2010107
R. Díaz Millán, M. Pentón Machado
Publication date: 3 December 2019
Published in: Journal of Global Optimization (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1805.10120
Hilbert spacesplitting methodsoptimization probleminexact methods\(\epsilon\)-subdifferentialaccelerated methods
Numerical mathematical programming methods (65K05) Convex programming (90C25) Nonlinear programming (90C30) Methods involving semicontinuity and convergence; relaxation (49J45)
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A note on approximate accelerated forward-backward methods with absolute and relative errors, and possibly strongly convex objectives, Primal-dual \(\varepsilon\)-subgradient method for distributed optimization, Principled analyses and design of first-order methods with inexact proximal operators, On FISTA with a relative error rule, The proximal methods for solving absolute value equation, Optimization and learning with nonlocal calculus
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