40 citations · 69 across the 16 of their papers we have counts for
7 papers · 1 filter
On propagation of chaos for the Fisher-Rao gradient flow in entropic mean-field optimization
Petra Lazić, Linshan Liu, Mateusz B. Majka
We consider a class of optimization problems on the space of probability measures motivated by the mean-field approach to studying neural networks. Such problems can be solved by c…
Non-convex entropic mean-field optimization via Best Response flow
Razvan-Andrei Lascu, Mateusz B. Majka
We study the problem of minimizing non-convex functionals on the space of probability measures, regularized by the relative entropy (KL divergence) with respect to a fixed referenc…
Linear convergence of proximal descent schemes on the Wasserstein space
Razvan-Andrei Lascu, Mateusz B. Majka, David Šiška +1
We investigate proximal descent methods, inspired by the minimizing movement scheme introduced by Jordan, Kinderlehrer and Otto, for optimizing entropy-regularized functionals on t…
A Fisher-Rao gradient flow for entropic mean-field min-max games
Razvan-Andrei Lascu, Mateusz B. Majka, Łukasz Szpruch
Gradient flows play a substantial role in addressing many machine learning problems. We examine the convergence in continuous-time of a \textit{Fisher-Rao} (Mean-Field Birth-Death)…
Mirror Descent-Ascent for mean-field min-max problems
Razvan-Andrei Lascu, Mateusz B. Majka, Łukasz Szpruch
We study two variants of the mirror descent-ascent (MDA) algorithm for solving min-max problems on the space of measures: simultaneous and alternating. We work under assumptions of…
Entropic mean-field min-max problems via Best Response flow
Razvan-Andrei Lascu, Mateusz B. Majka, Łukasz Szpruch
We investigate the convergence properties of a continuous-time optimization method, the \textit{Mean-Field Best Response} flow, for solving convex-concave min-max games with entrop…
Polyak-Łojasiewicz inequality on the space of measures and convergence of mean-field birth-death processes
Linshan Liu, Mateusz B. Majka, Łukasz Szpruch
The Polyak-Lojasiewicz inequality (PLI) in is a natural condition for proving convergence of gradient descent algorithms. In the present paper, we study an analogue…