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Nishimori meets Bethe: a spectral method for node classification in sparse weighted graphs


Mar 05, 2021
Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay


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Two-way kernel matrix puncturing: towards resource-efficient PCA and spectral clustering


Feb 25, 2021
Romain Couillet, Florent Chatelain, Nicolas Le Bihan

* 24 pages (10 for the core paper, 14 for the proofs in supplementary materials) , 8 figures 

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Concentration of measure and generalized product of random vectors with an application to Hanson-Wright-like inequalities


Feb 19, 2021
Cosme Louart, Romain Couillet

* 48 pages 

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Concentration of measure and generalized product ofrandom vectors with an application to Hanson-Wright-like inequalities


Feb 16, 2021
Cosme Louart, Romain Couillet

* 48 pages 

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Concentration of solutions to random equations with concentration of measure hypotheses


Oct 19, 2020
Cosme Louart, Romain Couillet


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Sparse Quantized Spectral Clustering


Oct 03, 2020
Zhenyu Liao, Romain Couillet, Michael W. Mahoney


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Large Dimensional Analysis and Improvement of Multi Task Learning


Sep 03, 2020
Malik Tiomoko, Romain Couillet, Hafiz Tiomoko


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A Concentration of Measure and Random Matrix Approach to Large Dimensional Robust Statistics


Jun 17, 2020
Cosme Louart, Romain Couillet

* 28 pages, 1 figure 

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Consistent Semi-Supervised Graph Regularization for High Dimensional Data


Jun 13, 2020
Xiaoyi Mai, Romain Couillet


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


Jun 09, 2020
Zhenyu Liao, Romain Couillet, Michael W. Mahoney


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


Jun 03, 2020
Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay


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A unified framework for spectral clustering in sparse graphs


Mar 20, 2020
Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay


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


Jan 21, 2020
Mohamed El Amine Seddik, Cosme Louart, Mohamed Tamaazousti, Romain Couillet


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Optimal Laplacian regularization for sparse spectral community detection


Dec 03, 2019
Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay

* Submitted to ICASSP 2020, under review 

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Inner-product Kernels are Asymptotically Equivalent to Binary Discrete Kernels


Sep 15, 2019
Zhenyu Liao, Romain Couillet


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Random Matrix-Improved Estimation of the Wasserstein Distance between two Centered Gaussian Distributions


Mar 08, 2019
Malik Tiomoko, Romain Couillet

* Submitted to European Signal Processing Conference (EUSIPCO'19) 

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Random Matrix Improved Covariance Estimation for a Large Class of Metrics


Feb 07, 2019
Malik Tiomoko, Florent Bouchard, Guillaume Ginholac, Romain Couillet


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Optimized Deformed Laplacian for Spectrum-based Community Detection in Sparse Heterogeneous Graphs


Jan 25, 2019
Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay


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A Geometric Approach of Gradient Descent Algorithms in Neural Networks


Nov 08, 2018
Yacine Chitour, Zhenyu Liao, Romain Couillet

* Preprint. Work in progress 

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Random matrix-improved estimation of covariance matrix distances


Oct 10, 2018
Romain Couillet, Malik Tiomoko, Steeve Zozor, Eric Moisan


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On the Spectrum of Random Features Maps of High Dimensional Data


Jul 20, 2018
Zhenyu Liao, Romain Couillet

* 13 pages (with Supplementary Material), 10 figure, ICML 2018 

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The Dynamics of Learning: A Random Matrix Approach


Jul 20, 2018
Zhenyu Liao, Romain Couillet

* 14 pages (with Supplementary Material), 7 figures, ICML 2018 

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Latent heterogeneous multilayer community detection


Jun 16, 2018
Hafiz Tiomoko Ali, Sijia Liu, Yasin Yilmaz, Alfred Hero, Romain Couillet, Indika Rajapakse


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A Large Dimensional Study of Regularized Discriminant Analysis Classifiers


Feb 18, 2018
Khalil Elkhalil, Abla Kammoun, Romain Couillet, Tareq Y. Al-Naffouri, Mohamed-Slim Alouini


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A random matrix analysis and improvement of semi-supervised learning for large dimensional data


Nov 09, 2017
Xiaoyi Mai, Romain Couillet


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A Random Matrix Approach to Neural Networks


Jun 29, 2017
Cosme Louart, Zhenyu Liao, Romain Couillet


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A Large Dimensional Analysis of Least Squares Support Vector Machines


Jan 11, 2017
Zhenyu Liao, Romain Couillet

* 26 pages, 10 figures, 1 table, partially presented at ICASSP 2017 

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Spectral community detection in heterogeneous large networks


Nov 03, 2016
Hafiz Tiomoko Ali, Romain Couillet


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Random matrices meet machine learning: a large dimensional analysis of LS-SVM


Sep 08, 2016
Zhenyu Liao, Romain Couillet

* wrong article submitted 

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