1 code implementation • 21 May 2024 • Pierre Humbert, Batiste Le Bars, Aurélien Bellet, Sylvain Arlot
Our experiments confirm that our algorithms return prediction sets with coverage and length similar to those obtained in a centralized setting.
1 code implementation • 13 Feb 2023 • Pierre Humbert, Batiste Le Bars, Aurélien Bellet, Sylvain Arlot
In this paper, we introduce a conformal prediction method to construct prediction sets in a oneshot federated learning setting.
1 code implementation • 6 Jul 2020 • Pierre Humbert, Laurent Oudre, Nivolas Vayatis, Julien Audiffren
Recently, there has been growing interest in the analysis of spectrograms of ElectroEncephaloGram (EEG), particularly to study the neural correlates of (un)-consciousness during General Anesthesia (GA).
1 code implementation • 30 Jun 2020 • Pierre Humbert, Batiste Le Bars, Ludovic Minvielle, Nicolas Vayatis
In this paper, we introduce a robust nonparametric density estimator combining the popular Kernel Density Estimation method and the Median-of-Means principle (MoM-KDE).
no code implementations • ICML 2020 • Batiste Le Bars, Pierre Humbert, Argyris Kalogeratos, Nicolas Vayatis
This work focuses on the estimation of multiple change-points in a time-varying Ising model that evolves piece-wise constantly.
no code implementations • 9 Aug 2019 • Pierre Humbert, Julien Audiffren, Laurent Oudre, Nicolas Vayatis
This paper introduces a new multivariate convolutional sparse coding based on tensor algebra with a general model enforcing both element-wise sparsity and low-rankness of the activations tensors.