Hugo Lebeau

Postdoctoral Fellow, Inria (ENS Lyon)
OCKHAM Team

Office: M7 1H32
Mail: hugo.lebeau@inria.fr

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Research Topics

I am broadly interested in statistical and algorithmic aspects of machine learning from high-dimensional data, notably through the study of random matrix and tensor models. In particular, this includes,

spiked random matrix and tensor models,
random tensors and their low-rank approximations,
theoretical study of complex clustering tasks (multi-view, time-varying),
learning with memory constraints, compressive learning.

Publications

JMLR – A Random Matrix Approach to Low-Multilinear-Rank Tensor Approximation, Hugo Lebeau, Florent Chatelain, Romain Couillet [paper]
IEEE Signal Processing Letters – Asymptotic Gaussian Fluctuations of Eigenvectors in Spectral Clustering, Hugo Lebeau, Florent Chatelain, Romain Couillet [article][code]

ICLR 2024 – Performance Gaps in Multi-view Clustering under the Nested Matrix-Tensor Model, Hugo Lebeau, Mohamed El Amine Seddik, José Henrique de Morais Goulart [article][code]
GRETSI 2023 – HOSVD Tronquée : Analyse d'une Approximation Tensorielle Rapide, Hugo Lebeau, Romain Couillet, Florent Chatelain [article]
GRETSI 2022 – Une analyse par matrices aléatoires du clustering en ligne : comprendre l’impact des limitations en mémoire, Hugo Lebeau, Romain Couillet, Florent Chatelain [article]
ICML 2022 – A Random Matrix Analysis of Data Stream Clustering: Coping With Limited Memory Resources, Hugo Lebeau, Romain Couillet, Florent Chatelain [article][code][video]

Ph.D. Thesis

My Ph.D. manuscript is available here.

If you want to know what this is about, read the abstract on page 3.
If you want to know more, the introduction (16 pages) will give you a broad overview of the main challenges.
After that, feel free to dive into the chapters. Chapter 2 may be a prerequisite if you want to fully understand the following ones.

Teaching

I currently take part in the following courses as teaching assistant.

ENS Paris-Saclay, Master MVA — Random Matrix Theory and Machine Learning.
ENS Lyon, M1 — Statistics.

See my CV for a full list of my previous teachings.

I have written (in French) a short reflection on my first two years of teaching. It is available here.