3 papers
cs.LG2024
PASCO (PArallel Structured COarsening): an overlay to speed up graph clustering algorithms
Etienne Lasalle, Rémi Vaudaine, Titouan Vayer +4
Clustering the nodes of a graph is a cornerstone of graph analysis and has been extensively studied. However, some popular methods are not suitable for very large graphs: e.g., spe…
stat.ML2023
Compressive Recovery of Sparse Precision Matrices
Titouan Vayer, Etienne Lasalle, Rémi Gribonval +1
We consider the problem of learning a graph modeling the statistical relations of the variables from a dataset with samples . Standard approa…
cs.LG2023
Implicit Differentiation for Hyperparameter Tuning the Weighted Graphical Lasso
Can Pouliquen, Paulo Gonçalves, Mathurin Massias +1
We provide a framework and algorithm for tuning the hyperparameters of the Graphical Lasso via a bilevel optimization problem solved with a first-order method. In particular, we de…