Technical Results on the Convergence of Quasi-Newton Methods for Nonsmooth Optimization

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Authors: Bennet Gebken
Cited by: 0
References: 30

Abstract

Abstract It is well-known by now that the BFGS method is an effective method for minimizing nonsmooth functions. However, despite its popularity, theoretical convergence results are almost non-existent. One of the difficulties when analyzing the nonsmooth case is the fact that the secant equation forces certain eigenvalues of the quasi-Newton matrix to vanish in the limit, which is a behavior that has not yet been fully analyzed. In this article, we show what kind of behavior of the eigenvalues would be sufficient to be able to prove the convergence for piecewise differentiable functions. More precisely, we derive assumptions on the behavior from numerical experiments and then prove criticality of the limit under these assumptions. Furthermore, we show how quasi-Newton methods are able to explore the piecewise structure. While we do not prove that the observed behavior of the eigenvalues always occurs, we believe that these results still give insight, and a certain intuition, for the convergence for nonsmooth functions.

Fields of Study & Subjects

Iterative Methods for Nonlinear Equations Advanced Optimization Algorithms Research Matrix Theory and Algorithms

Publication details

Journal / source
Journal of Optimization Theory and Applications
Publisher
Springer Science and Business Media LLC
Volume
209
Issue
2
Publication date
1 May 2026
Language
EN