3 papers
stat.ML2020
Riemannian geometry for Compound Gaussian distributions: application to recursive change detection
Florent Bouchard, Ammar Mian, Jialun Zhou +3
A new Riemannian geometry for the Compound Gaussian distribution is proposed. In particular, the Fisher information metric is obtained, along with corresponding geodesics and dista…
math.DG2020
A Riemannian Framework for Low-Rank Structured Elliptical Models
Florent Bouchard, Arnaud Breloy, Guillaume Ginolhac +2
This paper proposes an original Riemmanian geometry for low-rank structured elliptical models, i.e., when samples are elliptically distributed with a covariance matrix that has a l…
stat.ML2019
Random Matrix Improved Covariance Estimation for a Large Class of Metrics
Malik Tiomoko, Florent Bouchard, Guillaume Ginholac +1
Relying on recent advances in statistical estimation of covariance distances based on random matrix theory, this article proposes an improved covariance and precision matrix estima…