598 citations · 1.6k across the 66 of their papers we have counts for
8 papers · 1 filter
Sparse Quantized Spectral Clustering
Zhenyu Liao, Romain Couillet, Michael W. Mahoney
Given a large data matrix, sparsifying, quantizing, and/or performing other entry-wise nonlinear operations can have numerous benefits, ranging from speeding up iterative algorithm…
Large Dimensional Analysis and Improvement of Multi Task Learning
Malik Tiomoko, Romain Couillet, Hafiz Tiomoko
Multi Task Learning (MTL) efficiently leverages useful information contained in multiple related tasks to help improve the generalization performance of all tasks. This article con…
Consistent Semi-Supervised Graph Regularization for High Dimensional Data
Xiaoyi Mai, Romain Couillet
Semi-supervised Laplacian regularization, a standard graph-based approach for learning from both labelled and unlabelled data, was recently demonstrated to have an insignificant hi…
A Concentration of Measure and Random Matrix Approach to Large Dimensional Robust Statistics
Cosme Louart, Romain Couillet
This article studies the \emph{robust covariance matrix estimation} of a data collection with , where is a \te…
A Random Matrix Analysis of Random Fourier Features: Beyond the Gaussian Kernel, a Precise Phase Transition, and the Corresponding Double Descent
Zhenyu Liao, Romain Couillet, Michael W. Mahoney
This article characterizes the exact asymptotics of random Fourier feature (RFF) regression, in the realistic setting where the number of data samples , their dimension , and…
Community detection in sparse time-evolving graphs with a dynamical Bethe-Hessian
Lorenzo Dall'Amico, Romain Couillet, Nicolas Tremblay
This article considers the problem of community detection in sparse dynamical graphs in which the community structure evolves over time. A fast spectral algorithm based on an exten…