output
20102026
most citedNon-parametric Models for Non-negative Functions

12 citations

researchers with a paper here
collaborating institutions

44 papers

cs.LG2026

Regularized Variational and Spectral Log-Density-Ratio Estimation in the Gaussian Location Model

Francis Bach

We study ridge-regularized log-density-ratio estimation in the Gaussian location model with a common covariance matrix. By affine invariance, the model is written as q N(0,…

cs.AI2026

Minimax Optimal Variance-Aware Regret Bounds for Multinomial Logistic MDPs

Pierre Boudart, Pierre Gaillard, Alessandro Rudi

We study reinforcement learning for episodic Markov Decision Processes (MDPs) whose transitions are modelled by a multinomial logistic (MNL) model. Existing algorithms for MNL mixt…

cs.LG2026

A Spectral Framework for Closed-Form Relative Density Estimation

Francis Bach

We propose a closed-form spectral framework for relative log-density estimation in linearly parameterized probabilistic models, including unnormalized and conditional models. This…

math.ST2026

Adjusted Scores for Discrete Langevin Algorithms

Armand Gissler, Saeed Saremi, Francis Bach

Sampling from discrete distributions is a ubiquitous task in machine learning, recently revisited by the emergence of discrete diffusion models. While Langevin algorithms constitut…

math.OC2026

High-Dimensional Analysis of Gradient Flow for Extensive-Width Quadratic Neural Networks

Simon Martin, Giulio Biroli, Francis Bach

We study the high-dimensional training dynamics of a shallow neural network with quadratic activation in a teacher-student setup. We focus on the extensive-width regime, where the…

cs.LG2025

A Convex Loss Function for Set Prediction with Optimal Trade-offs Between Size and Conditional Coverage

Francis Bach

We consider supervised learning problems in which set predictions provide explicit uncertainty estimates. Using Choquet integrals (a.k.a. Lov{á}sz extensions), we propose a convex…