Posts by Collection

portfolio

Portfolio item number 1

Portfolio item number 2

publications

A Probabilistic Framework to Node-level Anomaly Detection in Communication Networks

B. Le Bars and A. Kalogeratos. INFOCOM 2019.

Learning laplacian matrix from bandlimited graph signals

B. Le Bars, P. Humbert, L. Oudre and A. Kalogeratos. ICASSP 2019.

Learning the piece-wise constant graph structure of a varying Ising model

B. Le Bars, P. Humbert, A. Kalogeratos and N. Vayatis. ICML 2020.

Event detection and structure inference for graph vectors

B. Le Bars. 2021.

Learning Laplacian Matrix from Graph Signals with Sparse Spectral Representation

P. Humbert*, B. Le Bars*, L. Oudre, A. Kalogeratos and N. Vayatis. Journal of Machine Learning Research 22 (2021).

Robust Kernel Density Estimation with Median-of-Means principle

P. Humbert*, B. Le Bars* and L. Minvielle. ICML 2022.

Refined Convergence and Topology Learning for Decentralized SGD with Heterogeneous Data

B. Le Bars, A. Bellet, M. Tommasi, E. Lavoie and A-M. Kermarrec . AISTATS 2023.

One-Shot Federated Conformal Prediction

P. Humbert, B. Le Bars, A. Bellet, and S. Arlot. ICML 2023.

Minimax Excess Risk of First-Order Methods for Statistical Learning with Data-Dependent Oracles

K. Scaman, M. Even, B. Le Bars and L. Massoulié. AISTATS 2024.

Marginal and Training-Conditional Guarantees in One-Shot Federated Conformal Prediction

P. Humbert, B. Le Bars, A. Bellet, and S. Arlot. May 2024

Improved Stability and Generalization Guarantees of the Decentralized SGD Algorithm

B. Le Bars, A. Bellet, M. Tommasi, K. Scaman, G. Neglia. ICML 2024.

talks

Machine learning techniques for geolocating Sigfox devices

Node-level anomaly detection in communication networks

Node-level anomaly detection in communication networks

Learning Laplacian Matrix from Bandlimited Graph Signals

A Probabilistic framework to Node-level Anomaly Detection in Communication Networks.

Change-point detection in a time-varying Ising model

Learning the piece-wise constant graph structure of a varying Ising model

Event detection and structure inference for graph vectors

Contributions to graph learning and change point detection

Refined Convergence and Topology Learning for Decentralized Optimization with Heterogeneous Data

Robust Kernel Density Estimation with Median-of-Means principle

teaching

Data analysis in Python

Introduction to Statistical Learning