8 citations · 8 across the 6 of their papers we have counts for
6 papers
Contrast-Free ICA and Causal Inference via Wasserstein Distances to the Gaussian
Félix Laplante, Christophe Ambroise, Pierre Humbert
We study the squared -Wasserstein distance to the standard Gaussian as a non-Gaussianity criterion and use it for linear Independent Component Analysis (ICA) and causal discover…
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…
Tensor Convolutional Sparse Coding with Low-Rank activations, an application to EEG analysis
Pierre Humbert, Laurent Oudre, Nivolas Vayatis +1
Recently, there has been growing interest in the analysis of spectrograms of ElectroEncephaloGram (EEG), particularly to study the neural correlates of (un)-consciousness during Ge…
Robust Kernel Density Estimation with Median-of-Means principle
Pierre Humbert, Batiste Le Bars, Ludovic Minvielle +1
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). This estima…
Learning the piece-wise constant graph structure of a varying Ising model
Batiste Le Bars, Pierre Humbert, Argyris Kalogeratos +1
This work focuses on the estimation of multiple change-points in a time-varying Ising model that evolves piece-wise constantly. The aim is to identify both the moments at which sig…
Multivariate Convolutional Sparse Coding with Low Rank Tensor
Pierre Humbert, Julien Audiffren, Laurent Oudre +1
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 activ…