Romain COUILLET

Professor

L2S, CentraleSupélec
Bât. Breguet A5.16
3 rue Joliot Curie
91190 Gif-sur-Yvette, France

+33 (0)1 69 85 14 36

Publications

Journal articles

2020

Random matrix improved covariance estimation for a large class of metrics

Tiomoko, Bouchard, Ginolhac, Couillet
J. stat. mech., 2020 (12), IOP Publishing, p. 124011, 2020
2019

Random matrix-improved estimation of covariance matrix distances

Couillet, Tiomoko, Zozor, Moisan
Journal of Multivariate Analysis, 174, p. 104531, 2019

A Large Dimensional Analysis of Least Squares Support Vector Machines

LIAO, Couillet
IEEE Transactions on Signal Processing, 67 (4), p. 1065-1074, 2019
2018

Large-Dimensional Behavior of Regularized Maronna’s M-Estimators of Covariance Matrices

Auguin, Morales-Jimenez, Mckay, Couillet
IEEE Transactions on Signal Processing, 66 (13), p. 3529-3542, 2018

High-Dimensional MVDR Beamforming: Optimized Solutions Based on Spiked Random Matrix Models

Yang, Mckay, Couillet
IEEE Transactions on Signal Processing, 66 (7), p. 1933-1947, 2018

Optimal Design of the Adaptive Normalized Matched Filter Detector

Kammoun, Couillet, Pascal, Alouini
IEEE Transactions on Aerospace and Electronic Systems, 54 (2), p. 755–769, 2018

Gallager Bound for MIMO Channels: Large- $N$ Asymptotics

Karadimitrakis, Moustakas, Couillet
IEEE Transactions on Wireless Communications, 17 (2), p. 1323-1330, 2018

A RANDOM MATRIX APPROACH TO NEURAL NETWORKS

Louart, Liao, Couillet
Ann. Appl. Probab., 28 (2), Institute of Mathematical Statistics (IMS), p. 1190-1248, 2021

Improved spectral community detection in large heterogeneous networks

Tiomoko Ali, Couillet
JMLR, 18 (10), Microtome Publishing, p. 1-49, 2021
2017

Large System Analysis of Power Normalization Techniques in Massive MIMO

Sadeghi, Sanguinetti, Couillet, Yuen
IEEE Trans. Veh. Technol., 66 (10), Institute of Electrical and Electronics Engineers, p. 9005 – 9017, 2017

Conference papers

2021

DECIPHERING AND OPTIMIZING MULTI-TASK LEARNING: A RANDOM MATRIX APPROACH

Tiomoko, Tiomoko, Couillet
International Conference on Learning Representations 2021, Vienna, Autriche, 2021

Sparse Quantized Spectral Clustering

LIAO, Couillet, Mahoney
ICLR 2021 – 9th International Conference on Learning Representations, Virtual Only, France, 2021
2020

Community detection in sparse time-evolving graphs with a dynamical Bethe-Hessian

Dall’Amico, Couillet, Tremblay
NeurIPS 2020 – 34th Conference on Neural Information Processing Systems, Vancouver (virtual), Canada, 2020

A random matrix analysis of random Fourier features: beyond the Gaussian kernel, a precise phase transition, and the corresponding double descent

LIAO, Couillet, Mahoney
NeurIPS 2020 – 34th Conference on Neural Information Processing Systems, Vancouver (virtual), Canada, 2020

Performance-Complexity Trade-Off in Large Dimensional Statistics

Zarrouk, Couillet, Chatelain, Le Bihan
MLSP 2020 – IEEE 30th International Workshop on Machine Learning for Signal Processing, Espoo (virtual), Finlande, 2020

A Random Matrix Analysis of Learning with α-Dropout

Seddik, Couillet, Tamaazousti
ICML 2020 Workshop Artemiss – 1st Workshop on the Art of Learning with Missing Values, Virtual, France, 2020

Large Dimensional Asymptotics of Multi-Task Learning

Tiomoko, Louart, Couillet
ICASSP 2020 – IEEE International Conference on Acoustics, Speech and Signal Processing, Barcelone (virtual), Espagne, 2020

Optimal Laplacian Regularization for Sparse Spectral Community Detection

Dall’Amico, Couillet, Tremblay
ICASSP 2020 – IEEE International Conference on Acoustics, Speech and Signal Processing, Barcelone (virtual), Espagne, 2021

Random Matrix Theory Proves that Deep Learning Representations of GAN-data Behave as Gaussian Mixtures

Seddik, Louart, Tamaazousti, Couillet
ICML 2020 : Thirty-seventh International Conference on Machine Learning, Online, France, 2021
2019

Estimation of Covariance Matrix Distances in the High Dimension Low Sample Size Regime

Tiomoko, Couillet
CAMSAP 2019 – 8th IEEE workshop on Computational Advances in Multi-Sensor Adaptive Processing, Le Gosier, Guadeloupe, France, 2019

Books

2017
Chapitres d’ouvrages scientifiques

Random matrix theory

Couillet, Debbah
in Random matrix theory, pp. 245-293, CRC Press, 2021
2011
Ouvrages scientifiques

Random Matrix Methods for Wireless Communications

Couillet, Debbah
Cambridge University Press, 2011

Radio Engineering: From Software Radio to Cognitive Radio

Palicot, Moy, Gul, Debbah, Couillet, Tembine, Seguier, Le Guennec, Jouini, Tourneur, Louët, Nafkha, Leray, Loison, Gillard
Wiley-ISTE, 2011
Autres ouvrages scientifiques
2010
Ouvrages scientifiques

De la radio logicielle à la radio intelligente

Palicot, Moy, Debbah, Couillet, Tembine, Séguier, Le Guennec, Jouini, Tourneur, Louët, Nafkha, Leray, Loison, Gillard
Lavoisier-Hermès, 2010
Chapitres d’ouvrages scientifiques

Fundamentals of OFDMA Synchronization

Couillet, Debbah
in Orthogonal Frequency Division Multiple Access (OFDMA), pp. Chapitre 13, Auerbach Publications, CRC Press, Taylor & Francis, 2021

Patents and software

2008

These/HDR

2010
Thèses

Application of random matrix theory to future wireless flexible networks

Couillet
Université Paris Sud – Paris XI, 2010