output
20122026
most citedDeep neural networks algorithms for stochastic control problems on finite horizon: convergence analysis

97 citations

541 papers

math.OC2026

Polyak-Łojasiewicz inequality is essentially no more general than strong convexity for functions

Aziz Ben Nejma

The Polyak-Łojasiewicz (PŁ) inequality extends the favorable optimization properties of strongly convex functions to a broader class of functions. In this paper, we prove a theorem…

cond-mat.stat-mech2025

Strong zero modes in integrable spin-S chains

Fabian H. L. Essler, Paul Fendley, Eric Vernier

We derive exact strong zero mode (ESZM) operators for integrable spin-S chains with open boundary conditions and a boundary field. Their locality properties are generally weaker th…

math.AP2025

Quantitative rigidity of the Wasserstein contraction under convolution

Max Fathi, Michael Goldman, Daniel Tsodyks

The aim of this paper is to investigate the contraction properties of -Wasserstein distances with respect to convolution in Euclidean spaces both qualitatively and quantitativel…

stat.ML2025

Fairness Meets Privacy: Integrating Differential Privacy and Demographic Parity in Multi-class Classification

Lilian Say, Christophe Denis, Rafael Pinot

The increasing use of machine learning in sensitive applications demands algorithms that simultaneously preserve data privacy and ensure fairness across potentially sensitive sub-p…

stat.ML2025

Maxitive Donsker-Varadhan Formulation for Possibilistic Variational Inference

Jasraj Singh, Shelvia Wongso, Jeremie Houssineau +1

Variational inference (VI) is a cornerstone of modern Bayesian learning, enabling approximate inference in complex models. However, its formulation depends on expectations and dive…

math-ph2025

Harmonic functions on Tutte embeddings and linearized Monge-Ampère equation

Mikhail Basok, Dmitry Chelkak, Benoît Laslier +1

We prove convergence of solutions of Dirichlet problems and Green's functions on Tutte harmonic embeddings to those of the linearized Monge--Ampère equation . Mor…