The backtrack Hölder gradient method with application to min-max and min-min problems

We present a new algorithm to solve min-max or min-min problems out of the convex world. We use rigidity assumptions, ubiquitous in learning, making our method – the backtrack Hölder algorithm applicable to many optimization problems. Our approach takes advantage of hidden regularity properties and...

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Bibliographic Details
Main Authors: Bolte, Jérôme, Glaudin, Lilian, Pauwels, Edouard, Serrurier, Mathieu
Format: Article
Language:English
Published: Université de Montpellier 2023-12-01
Series:Open Journal of Mathematical Optimization
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Online Access:https://ojmo.centre-mersenne.org/articles/10.5802/ojmo.24/
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