8 citations · 10 across the 9 of their papers we have counts for
9 papers
Dangerous Liaisons of Convex Learning and Non-Affine Aggregation
Thomas Boudou, Batiste Le Bars, Nirupam Gupta +1
Last-iterate convergence and generalization guarantees in first-order convex learning hinge on the monotonicity of the update operator. While linear averaging preserves the monoton…
Adaptive Personalized Federated Learning via Multi-task Averaging of Kernel Mean Embeddings
Jean-Baptiste Fermanian, Batiste Le Bars, Aurélien Bellet
Personalized Federated Learning (PFL) enables a collection of agents to collaboratively learn individual models without sharing raw data. We propose a new PFL approach in which eac…
Metric space valued Fréchet regression
László Györfi, Pierre Humbert, Batiste Le Bars
We consider the problem of estimating the Fréchet and conditional Fréchet mean from data taking values in separable metric spaces. Unlike Euclidean spaces, where well-established m…
Adaptive collaboration for online personalized distributed learning with heterogeneous clients
Constantin Philippenko, Batiste Le Bars, Kevin Scaman +1
We study the problem of online personalized decentralized learning with statistically heterogeneous clients collaborating to accelerate local training. An important challenge i…
TAMIS: Tailored Membership Inference Attacks on Synthetic Data
Paul Andrey, Batiste Le Bars, Marc Tommasi
Membership Inference Attacks (MIA) enable to empirically assess the privacy of a machine learning algorithm. In this paper, we propose TAMIS, a novel MIA against differentially-pri…
On Volume Minimization in Conformal Regression
Batiste Le Bars, Pierre Humbert
We study the question of volume optimality in split conformal regression, a topic still poorly understood in comparison to coverage control. Using the fact that the calibration ste…