An elementary approach to tight worst case complexity analysis of gradient based methods

This work presents a novel analysis that allows to achieve tight complexity bounds of gradient-based methods for convex optimization. We start by identifying some of the pitfalls rooted in the classical complexity analysis of the gradient descent method, and show how they can be remedied. Our method...

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Bibliographic Details
Published in:	Mathematical programming Vol. 201; no. 1-2; pp. 63 - 96
Main Authors:	Teboulle, Marc, Vaisbourd, Yakov
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2023 Springer
Subjects:	Calculus of Variations and Optimal Control; Optimization Combinatorics Full Length Paper Mathematical and Computational Physics Mathematical Methods in Physics Mathematics Mathematics and Statistics Mathematics of Computing Numerical Analysis Theoretical Convex minimization Gradient descent 68Q25 Performance estimation problem Proximal schemes 90C30 Composite minimization Global rate of convergence 90C25 90C60 Worst-case complexity analysis
ISSN:	0025-5610, 1436-4646
Online Access:	Get full text
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