10 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Centre Inria de l'Université de LilleFR1 paper
- Centre National de la Recherche ScientifiqueFR1 paper
- Département d'InformatiqueFR1 paper
- École Normale Supérieure - PSLFR1 paper
- École PolytechniqueFR1 paper
- Frantsevich Institute for Problems in Materials ScienceUA1 paper
- Institute of PhysicsPL1 paper
- Institut national de recherche en sciences et technologies du numériqueFR1 paper
- Laboratoire de Mathématiques Blaise PascalFR1 paper
- Laboratoire de Mathématiques d'OrsayFR1 paper
- Laboratoire Traitement et Communication de l’InformationFR1 paper
- LamsadeFR1 paper
8 papers
Accurate, private, secure, federated U-statistics with higher degree
Quentin Sinh, Jan Ramon
We study the problem of computing a U-statistic with a kernel function f of degree k 2, i.e., the average of some function f over all k-tuples of instances, in a federated le…
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…
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…
The origin of the ferroelectric-like orthorhombic phase in oxygen-deficient HfO2-y nanoparticles
Eugene A. Eliseev, Iryna V. Kondakova, Yuri O. Zagorodniy +6
In this work we established the relationship between the crystalline structure symmetry, point defects and possible appearance of the ferroelectric-like polarization in HfO2-y nano…
Optimal Classification under Performative Distribution Shift
Edwige Cyffers, Muni Sreenivas Pydi, Jamal Atif +1
Performative learning addresses the increasingly pervasive situations in which algorithmic decisions may induce changes in the data distribution as a consequence of their public de…
Central Limit Theorem for Bayesian Neural Network trained with Variational Inference
Arnaud Descours, Tom Huix, Arnaud Guillin +3
In this paper, we rigorously derive Central Limit Theorems (CLT) for Bayesian two-layerneural networks in the infinite-width limit and trained by variational inference on a regress…
One-Shot Federated Conformal Prediction
Pierre Humbert, Batiste Le Bars, Aurélien Bellet +1
In this paper, we introduce a conformal prediction method to construct prediction sets in a oneshot federated learning setting. More specifically, we define a quantile-of-quantiles…
Extending Gossip Algorithms to Distributed Estimation of U-Statistics
Igor Colin, Aurélien Bellet, Joseph Salmon +1
Efficient and robust algorithms for decentralized estimation in networks are essential to many distributed systems. Whereas distributed estimation of sample mean statistics has bee…