Romain Couillet

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 126

Top Venues

CoRR

ICASSP

IEEE Trans. Signal Process.

CAMSAP

University of Paris-Sud, Orsay, France (PHD)

Education History

University of Paris-Sud, Orsay, France

PHD

Publications

Hugo Lebeau, Florent Chatelain, Romain Couillet
A Random Matrix Approach to Low-Multilinear-Rank Tensor Approximation. CoRR (2024)
Minh-Toan Nguyen, Romain Couillet
Asymptotic Bayes risk of semi-supervised multitask learning on Gaussian mixture. CoRR (2023)
Minh-Toan Nguyen, Romain Couillet
Asymptotic Bayes risk of semi-supervised multitask learning on Gaussian mixture. AISTATS (2023)
Malik Tiomoko, Romain Couillet, Frédéric Pascal
PCA-based Multi-Task Learning: a Random Matrix Approach. ICML (2023)
Cyprien Doz, Chengfang Ren, Jean Philippe Ovarlez, Romain Couillet
Large Dimensional Analysis of LS-SVM Transfer Learning: Application to Polsar Classification. ICASSP (2023)
José Henrique de Morais Goulart, Romain Couillet, Pierre Comon
A Random Matrix Perspective on Random Tensors. J. Mach. Learn. Res. 23 (2022)
Romain Couillet, Denis Trystram, Thierry Ménissier
The Submerged Part of the AI-Ceberg [Perspectives]. IEEE Signal Process. Mag. 39 (5) (2022)
Hafiz Tiomoko Ali, Zhenyu Liao, Romain Couillet
Random matrices in service of ML footprint: ternary random features with no performance loss. ICLR (2022)
Hugo Lebeau, Romain Couillet, Florent Chatelain
A Random Matrix Analysis of Data Stream Clustering: Coping With Limited Memory Resources. ICML (2022)
Mohamed El Amine Seddik, Cosme Louart, Romain Couillet, Mohamed Tamaazousti
The Unexpected Deterministic and Universal Behavior of Large Softmax Classifiers. AISTATS (2021)
Romain Couillet, Florent Chatelain, Nicolas Le Bihan
Two-way kernel matrix puncturing: towards resource-efficient PCA and spectral clustering. CoRR (2021)
Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay
Nishimori meets Bethe: a spectral method for node classification in sparse weighted graphs. CoRR (2021)
Hafiz Tiomoko Ali, Zhenyu Liao, Romain Couillet
Random matrices in service of ML footprint: ternary random features with no performance loss. CoRR (2021)
Malik Tiomoko, Romain Couillet, Frédéric Pascal
PCA-based Multi Task Learning: a Random Matrix Approach. CoRR (2021)
José Henrique de Morais Goulart, Romain Couillet, Pierre Comon
A Random Matrix Perspective on Random Tensors. CoRR (2021)
Romain Couillet, Florent Chatelain, Nicolas Le Bihan
Two-way kernel matrix puncturing: towards resource-efficient PCA and spectral clustering. ICML (2021)
Sami Fakhry, Romain Couillet, Malik Tiomoko
Multi-task learning on the edge: cost-efficiency and theoretical optimality. CoRR (2021)
Malik Tiomoko, Hafiz Tiomoko Ali, Romain Couillet
Deciphering and Optimizing Multi-Task Learning: a Random Matrix Approach. ICLR (2021)
Xiaoyi Mai, Romain Couillet
Consistent Semi-Supervised Graph Regularization for High Dimensional Data. J. Mach. Learn. Res. 22 (2021)
Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay
A Unified Framework for Spectral Clustering in Sparse Graphs. J. Mach. Learn. Res. 22 (2021)
Charles Séjourné, Romain Couillet, Pierre Comon
A Large-Dimensional Analysis of Symmetric SNE. ICASSP (2021)
Zhenyu Liao, Romain Couillet, Michael W. Mahoney
Sparse Quantized Spectral Clustering. ICLR (2021)
Zhenyu Liao, Romain Couillet, Michael W. Mahoney
A random matrix analysis of random Fourier features: beyond the Gaussian kernel, a precise phase transition, and the corresponding double descent. CoRR (2020)
Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay
Community detection in sparse time-evolving graphs with a dynamical Bethe-Hessian. NeurIPS (2020)
Romain Couillet, Yagmur Gizem Cinar, Éric Gaussier, Muhammad Imran
Word Representations Concentrate and This is Good News! CoNLL (2020)
Zhenyu Liao, Romain Couillet, Michael W. Mahoney
Sparse Quantized Spectral Clustering. CoRR (2020)
Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay
A unified framework for spectral clustering in sparse graphs. CoRR (2020)
Xiaoyi Mai, Romain Couillet
Consistent Semi-Supervised Graph Regularization for High Dimensional Data. CoRR (2020)
Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay
Optimal Laplacian Regularization for Sparse Spectral Community Detection. ICASSP (2020)
Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay
Community detection in sparse time-evolving graphs with a dynamical Bethe-Hessian. CoRR (2020)
Mohamed El Amine Seddik, Cosme Louart, Mohamed Tamaazousti, Romain Couillet
Random Matrix Theory Proves that Deep Learning Representations of GAN-data Behave as Gaussian Mixtures. CoRR (2020)
Malik Tiomoko, Cosme Louart, Romain Couillet
Large Dimensional Asymptotics of Multi-Task Learning. ICASSP (2020)
Mohamed El Amine Seddik, Cosme Louart, Mohamed Tamaazousti, Romain Couillet
Random Matrix Theory Proves that Deep Learning Representations of GAN-data Behave as Gaussian Mixtures. ICML (2020)
Malik Tiomoko Ali, Romain Couillet, Hafiz Tiomoko
Large Dimensional Analysis and Improvement of Multi Task Learning. CoRR (2020)
Tayeb Zarrouk, Romain Couillet, Florent Chatelain, Nicolas Le Bihan
Performance-Complexity Trade-Off in Large Dimensional Statistics. MLSP (2020)
Khalil Elkhalil, Abla Kammoun, Romain Couillet, Tareq Y. Al-Naffouri, Mohamed-Slim Alouini
A Large Dimensional Study of Regularized Discriminant Analysis. IEEE Trans. Signal Process. 68 (2020)
Zhenyu Liao, Romain Couillet, Michael W. Mahoney
A random matrix analysis of random Fourier features: beyond the Gaussian kernel, a precise phase transition, and the corresponding double descent. NeurIPS (2020)
Malik Tiomoko, Romain Couillet
Random Matrix-Improved Estimation of the Wasserstein Distance between two Centered Gaussian Distributions. EUSIPCO (2019)
Malik Tiomoko, Romain Couillet, Florent Bouchard, Guillaume Ginolhac
Random Matrix Improved Covariance Estimation for a Large Class of Metrics. ICML (2019)
Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay
Optimized Deformed Laplacian for Spectrum-based Community Detection in Sparse Heterogeneous Graphs. CoRR (2019)
Malik Tiomoko, Romain Couillet
Estimation of Covariance Matrix Distances in the High Dimension Low Sample Size Regime. CAMSAP (2019)
Malik Tiomoko, Romain Couillet
Random Matrix-Improved Estimation of the Wasserstein Distance between two Centered Gaussian Distributions. CoRR (2019)
Malik Tiomoko, Florent Bouchard, Guillaume Ginolhac, Romain Couillet
Random Matrix Improved Covariance Estimation for a Large Class of Metrics. CoRR (2019)
Arun Kadavankandy, Romain Couillet
Asymptotic Gaussian Fluctuations of Spectral Clustering Eigenvectors. CAMSAP (2019)
Romain Couillet, Malik Tiomoko, Steeve Zozor, Eric Moisan
Random matrix-improved estimation of covariance matrix distances. J. Multivar. Anal. 174 (2019)
Zhenyu Liao, Romain Couillet
On Inner-Product Kernels of High Dimensional Data. CAMSAP (2019)
Mohamed El Amine Seddik, Mohamed Tamaazousti, Romain Couillet
Kernel Random Matrices of Large Concentrated Data: the Example of GAN-Generated Images. ICASSP (2019)
Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay
Optimal Laplacian regularization for sparse spectral community detection. CoRR (2019)
Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay
Revisiting the Bethe-Hessian: Improved Community Detection in Sparse Heterogeneous Graphs. NeurIPS (2019)
Xiaoyi Mai, Zhenyu Liao, Romain Couillet
A Large Scale Analysis of Logistic Regression: Asymptotic Performance and New Insights. ICASSP (2019)
Malik Tiomoko, Romain Couillet, Eric Moisan, Steeve Zozor
Improved Estimation of the Distance between Covariance Matrices. ICASSP (2019)
Hafiz Tiomoko Ali, Sijia Liu, Yasin Yilmaz, Romain Couillet, Indika Rajapakse, Alfred O. Hero III
Latent Heterogeneous Multilayer Community Detection. ICASSP (2019)
Lorenzo Dall'Amico, Romain Couillet
Community Detection in Sparse Realistic Graphs: Improving the Bethe Hessian. ICASSP (2019)
Romain Couillet
High Dimensional Robust Classification: A Random Matrix Analysis. CAMSAP (2019)
Zhenyu Liao, Romain Couillet
A Large Dimensional Analysis of Least Squares Support Vector Machines. IEEE Trans. Signal Process. 67 (4) (2019)
Romain Couillet
A Random Matrix Analysis and Optimization Framework to Large Dimensional Transfer Learning. CAMSAP (2019)
Zhenyu Liao, Romain Couillet
Inner-product Kernels are Asymptotically Equivalent to Binary Discrete Kernels. CoRR (2019)
Cosme Louart, Romain Couillet
A Concentration of Measure Perspective to Robust Statistics. CAMSAP (2019)
Xiaoyi Mai, Romain Couillet
Revisiting and Improving Semi-supervised Learning: A Large Dimensional Approach. ICASSP (2019)
Mohamed El Amine Seddik, Mohamed Tamaazousti, Romain Couillet
A Kernel Random Matrix-Based Approach for Sparse PCA. ICLR (Poster) (2019)
Apostolos Karadimitrakis, Aris L. Moustakas, Romain Couillet
Gallager Bound for MIMO Channels: Large- $N$ Asymptotics. IEEE Trans. Wirel. Commun. 17 (2) (2018)
Abla Kammoun, Romain Couillet, Frédéric Pascal, Mohamed-Slim Alouini
Optimal Design of the Adaptive Normalized Matched Filter Detector Using Regularized Tyler Estimators. IEEE Trans. Aerosp. Electron. Syst. 54 (2) (2018)
Xiaoyi Mai, Romain Couillet
Semi-Supervised Spectral Clustering. ACSSC (2018)
Nicolas Auguin, David Morales-Jiménez, Matthew R. McKay, Romain Couillet
Large-Dimensional Behavior of Regularized Maronna's M-Estimators of Covariance Matrices. IEEE Trans. Signal Process. 66 (13) (2018)
Zhenyu Liao, Romain Couillet
On the Spectrum of Random Features Maps of High Dimensional Data. ICML (2018)
Zhenyu Liao, Romain Couillet
On the Spectrum of Random Features Maps of High Dimensional Data. CoRR (2018)
Hafiz Tiomoko Ali, Abla Kammoun, Romain Couillet
Random Matrix Asymptotics of Inner Product Kernel Spectral Clustering. ICASSP (2018)
Hafiz Tiomoko Ali, Sijia Liu, Yasin Yilmaz, Alfred O. Hero III, Romain Couillet, Indika Rajapakse
Latent heterogeneous multilayer community detection. CoRR (2018)
Cosme Louart, Romain Couillet
A Random Matrix and Concentration Inequalities Framework for Neural Networks Analysis. ICASSP (2018)
Liusha Yang, Matthew R. McKay, Romain Couillet
Random Matrix-Optimized High-Dimensional MVDR Beamforming. SSP (2018)
Zhenyu Liao, Romain Couillet
The Dynamics of Learning: A Random Matrix Approach. ICML (2018)
Romain Couillet, Malik Tiomoko, Steeve Zozor, Eric Moisan
Random matrix-improved estimation of covariance matrix distances. CoRR (2018)
Zhenyu Liao, Romain Couillet
The Dynamics of Learning: A Random Matrix Approach. CoRR (2018)
Liusha Yang, Matthew R. McKay, Romain Couillet
High-Dimensional MVDR Beamforming: Optimized Solutions Based on Spiked Random Matrix Models. IEEE Trans. Signal Process. 66 (7) (2018)
Yacine Chitour, Zhenyu Liao, Romain Couillet
A Geometric Approach of Gradient Descent Algorithms in Neural Networks. CoRR (2018)
Romain Couillet, Zhenyu Liao, Xiaoyi Mai
Classification Asymptotics in the Random Matrix Regime. EUSIPCO (2018)
Hafiz Tiomoko Ali, Abla Kammoun, Romain Couillet
Random Matrix-Improved Kernels For Large Dimensional Spectral Clustering. SSP (2018)
Hafiz Tiomoko Ali, Romain Couillet
Improved spectral community detection in large heterogeneous networks. J. Mach. Learn. Res. 18 (2017)
Meysam Sadeghi, Luca Sanguinetti, Romain Couillet, Chau Yuen
Large System Analysis of Power Normalization Techniques in Massive MIMO. CoRR (2017)
Meysam Sadeghi, Luca Sanguinetti, Romain Couillet, Chau Yuen
Reducing the Computational Complexity of Multicasting in Large-Scale Antenna Systems. CoRR (2017)
Meysam Sadeghi, Luca Sanguinetti, Romain Couillet, Chau Yuen
Reducing the Computational Complexity of Multicasting in Large-Scale Antenna Systems. IEEE Trans. Wirel. Commun. 16 (5) (2017)
Apostolos Karadimitrakis, Romain Couillet, Aris L. Moustakas, Luca Sanguinetti
The Gallager Bound in Fiber Optical MIMO. WSA (2017)
Cosme Louart, Zhenyu Liao, Romain Couillet
A Random Matrix Approach to Neural Networks. CoRR (2017)
Khalil Elkhalil, Abla Kammoun, Romain Couillet, Tareq Y. Al-Naffouri, Mohamed-Slim Alouini
Asymptotic performance of regularized quadratic discriminant analysis based classifiers. MLSP (2017)
Cosme Louart, Romain Couillet
Harnessing neural networks: A random matrix approach. ICASSP (2017)
Meysam Sadeghi, Luca Sanguinetti, Romain Couillet, Chau Yuen
Large System Analysis of Power Normalization Techniques in Massive MIMO. IEEE Trans. Veh. Technol. 66 (10) (2017)
Xiaoyi Mai, Romain Couillet
A random matrix analysis and improvement of semi-supervised learning for large dimensional data. CoRR (2017)
Xiaoyi Mai, Romain Couillet
The counterintuitive mechanism of graph-based semi-supervised learning in the big data regime. ICASSP (2017)
Apostolos Karadimitrakis, Aris L. Moustakas, Romain Couillet
Gallager Bound for MIMO Channels: Large-N Asymptotics. CoRR (2017)
Zhenyu Liao, Romain Couillet
Random matrices meet machine learning: A large dimensional analysis of LS-SVM. ICASSP (2017)
Azary Abboud, Franck Iutzeler, Romain Couillet, Mérouane Debbah, Houria Siguerdidjane
Distributed Production-Sharing Optimization and Application to Power Grid Networks. IEEE Trans. Signal Inf. Process. over Networks 2 (1) (2016)
Romain Couillet
Introduction. Traitement du Signal 33 (2-3) (2016)
Nicolas Auguin, David Morales-Jiménez, Matthew R. McKay, Romain Couillet
Robust shrinkage M-estimators of large covariance matrices. SSP (2016)
Hafiz Tiomoko Ali, Romain Couillet
Performance analysis of spectral community detection in realistic graph models. ICASSP (2016)
Luca Sanguinetti, Romain Couillet, Mérouane Debbah
Large System Analysis of Base Station Cooperation for Power Minimization. IEEE Trans. Wirel. Commun. 15 (8) (2016)
Romain Couillet
Estimation robuste et matrices aléatoires. Traitement du Signal 33 (2-3) (2016)
Romain Couillet, Gilles Wainrib, Harry Sevi, Hafiz Tiomoko Ali
Training performance of echo state neural networks. SSP (2016)
Romain Couillet, Abla Kammoun, Frédéric Pascal
Second order statistics of robust estimators of scatter. Application to GLRT detection for elliptical signals. J. Multivar. Anal. 143 (2016)
Abla Kammoun, Romain Couillet, Frédéric Pascal, Mohamed-Slim Alouini
Convergence and Fluctuations of Regularized Tyler Estimators. IEEE Trans. Signal Process. 64 (4) (2016)
Romain Couillet, Abla Kammoun
Random matrix improved subspace clustering. ACSSC (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Romain Couillet