Search Results for author:
Found 6 papers, 4 papers with code
Compressive Recovery of Sparse Precision Matrices
We consider the problem of learning a graph modeling the statistical relations of the $d$ variables from a dataset with $n$ samples $X \in \mathbb{R}^{n \times d}$.
Implicit Differentiation for Hyperparameter Tuning the Weighted Graphical Lasso
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.
Fast Multiscale Diffusion on Graphs
Diffusing a graph signal at multiple scales requires computing the action of the exponential of several multiples of the Laplacian matrix.
Solving NMF with smoothness and sparsity constraints using PALM
Non-negative matrix factorization is a problem of dimensionality reduction and source separation of data that has been widely used in many fields since it was studied in depth in 1999 by Lee and Seung, including in compression of data, document clustering, processing of audio spectrograms and astronomy.
$L^γ$-PageRank for Semi-Supervised Learning
A procedure for the automated estimation of the optimal $\gamma$, from a unique observation of data, is devised and assessed.
Design of graph filters and filterbanks
The aim of this chapter is to review general concepts for the introduction of filters and representations of graph signals.
Signal Processing Information Theory Social and Information Networks Information Theory
