EF1 – Extracting dynamical Laws from Complex Data

Project

EF1-23

On a Frank-Wolfe Approach for Abs-Smooth Optimization

Project Heads

Sebastian Pokutta, Andrea Walther, Zev Woodstock

Project Members

N.N.

Project Duration

01.01.2023 − 31.12.2025

Located at

HU Berlin

Description

Motivated by nonsmooth problems in machine learning, we solve the problem of minimizing an abs-smooth function subject to closed convex constraints. New theory and algorithms are developed using linear minimization oracles to enforce constraints and abs-linearization methods to handle nonsmoothness.

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