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07/02/2022
Geometric Learning of Hidden Markov Models via a Method of Moments Algorithm
We present a novel algorithm for learning the parameters of hidden Marko...
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03/01/2022
Riemannian statistics meets random matrix theory: towards learning from high-dimensional covariance matrices
Riemannian Gaussian distributions were initially introduced as basic bui...
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02/15/2021
Online learning of Riemannian hidden Markov models in homogeneous Hadamard spaces
Hidden Markov models with observations in a Euclidean space play an impo...
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02/15/2021
On Riemannian Stochastic Approximation Schemes with Fixed Step-Size
This paper studies fixed step-size stochastic approximation (SA) schemes...
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02/15/2021
Gaussian distributions on Riemannian symmetric spaces in the large N limit
We consider Gaussian distributions on certain Riemannian symmetric space...
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01/26/2021
Statistical models and probabilistic methods on Riemannian manifolds
This entry contains the core material of my habilitation thesis, soon to...
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01/11/2021
Hidden Markov chains and fields with observations in Riemannian manifolds
Hidden Markov chain, or Markov field, models, with observations in a Euc...
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05/27/2020
Convergence Analysis of Riemannian Stochastic Approximation Schemes
This paper analyzes the convergence for a large class of Riemannian stoc...
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05/20/2020
Riemannian geometry for Compound Gaussian distributions: application to recursive change detection
A new Riemannian geometry for the Compound Gaussian distribution is prop...
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02/11/2019
The Riemannian barycentre as a proxy for global optimisation
Let M be a simply-connected compact Riemannian symmetric space, and U a ...
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05/17/2018
Fast, asymptotically efficient, recursive estimation in a Riemannian manifold
Stochastic optimisation in Riemannian manifolds, especially the Riemanni...
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05/17/2018