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20232026
most citedEntropic mean-field min-max problems via Best Response flow

1 citations · 1 across the 6 of their papers we have counts for

collaborators

7 papers

math.OC2026

Wasserstein Saddle-Free Newton: Saddle Escape and Local Spectral Convergence

Razvan-Andrei Lascu, Taiji Suzuki

Extending saddle-free Newton methods to Wasserstein space requires controlling Hessian dependent operators along nonlinear transport trajectories and accounting for a Hessian spect…

cs.LG2025

PPO in the Fisher-Rao geometry

Razvan-Andrei Lascu, David Šiška, Łukasz Szpruch

Proximal Policy Optimization (PPO) is widely used in reinforcement learning due to its strong empirical performance, yet it lacks formal guarantees for policy improvement and conve…

math.OC2025

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…

math.OC2024

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…

math.OC2024

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)…

math.OC2024

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…

math.OC2023★ 1 cited

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…