15 citations · 15 across the 2 of their papers we have counts for
3 papers
math.OC2020
Ubiquitous algorithms in convex optimization generate self-contracted sequences
Axel Böhm, Aris Daniilidis
In this work we show that various algorithms, ubiquitous in convex optimization (e.g. proximal-gradient, alternating projections and averaged projections) generate self-contracted…
math.OC2020★ 15 cited
Variable Smoothing for Weakly Convex Composite Functions
Axel Böhm, Stephen J. Wright
We study minimization of a structured objective function, being the sum of a smooth function and a composition of a weakly convex function with a linear operator. Applications incl…
math.OC2019
Variable smoothing for convex optimization problems using stochastic gradients
Radu Ioan Bot, Axel Böhm
We aim to solve a structured convex optimization problem, where a nonsmooth function is composed with a linear operator. When opting for full splitting schemes, usually, primal-dua…