Convergence analysis of stochastic higher-order majorization-minimization algorithms

Majorization-minimization schemes are a broad class of iterative methods targeting general optimization problems, including nonconvex, nonsmooth and stochastic. These algorithms minimize successively a sequence of upper bounds of the objective function so that along the iterations the objective valu...

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Bibliographic Details

Published in:	Optimization methods & software Vol. 39; no. 2; pp. 384 - 413
Main Authors:	Lupu, Daniela, Necoara, Ion
Format:	Journal Article
Language:	English
Published:	Abingdon Taylor & Francis 03.03.2024 Taylor & Francis Ltd
Subjects:	Algorithms Approximation Convergence convergence rates Convexity Finite-sum optimization Iterative methods majorization-minimization minibatch Optimization stochastic higher-order algorithms Upper bounds
ISSN:	1055-6788, 1029-4937
Online Access:	Get full text
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