Arnaud Breloy

Sparse PCA with False Discovery Rate Controlled Variable Selection

Sparse principal component analysis (PCA) aims at mapping large dimensional data to a linear subspace of lower dimension. By imposing loading vectors to be sparse, it performs the double duty of...

The Fisher-Rao geometry of CES distributions

When dealing with a parametric statistical model, a Riemannian manifold can naturally appear by endowing the parameter space with the Fisher information metric. The geometry induced on the...

Learning Graphical Factor Models with Riemannian Optimization

Graphical models and factor analysis are well-established tools in multivariate statistics. While these models can be both linked to structures exhibited by covariance and precision matrices, they...

Riemannian optimization for non-centered mixture of scaled Gaussian distributions

This paper studies the statistical model of the non-centered mixture of scaled Gaussian distributions (NC-MSG). Using the Fisher-Rao information geometry associated to this distribution, we derive...

Entropic Wasserstein Component Analysis

Dimension reduction (DR) methods provide systematic approaches for analyzing high-dimensional data. A key requirement for DR is to incorporate global dependencies among original and embedded...

Robust Geometric Metric Learning

This paper proposes new algorithms for the metric learning problem. We start by noticing that several classical metric learning formulations from the literature can be viewed as modified...

Entropic Wasserstein Component Analysis

A robust signal subspace estimator

Computationally Efficient Text-to-Video Editing for Autonomous Driving Data Augmentation

Deep Unrolling of Robust PCA and Convolutional Sparse Coding for Stationary Target Localization in Through Wall Radar Imaging

Robust Geometric Metric Learning

Signal subspace change detection in structured covariance matrices

Block majorization-minimization algorithms for low-rank clutter subspace estimation

On the Recursions of Robust COMET Algorithm for Convexly Structured Shape Matrix

Leveraging Standardization in Graph Learning

Robust Subspace Clustering for Radar Detection

Bayesian Robust Signal Subspace Estimation in Non-Gaussian Environment

Efficient Estimation of Kronecker Product of Linear Structured Scatter Matrices under t-distribution