451 citations · 1.8k across the 39 of their papers we have counts for
5 papers · 1 filter
Learning Hierarchical and Topographic Dictionaries with Structured Sparsity
Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski +1
Recent work in signal processing and statistics have focused on defining new regularization functions, which not only induce sparsity of the solution, but also take into account th…
Structured sparsity through convex optimization
Francis Bach, Rodolphe Jenatton, Julien Mairal +1
Sparse estimation methods are aimed at using or obtaining parsimonious representations of data or models. While naturally cast as a combinatorial optimization problem, variable or…
Optimization with Sparsity-Inducing Penalties
Francis Bach, Rodolphe Jenatton, Julien Mairal +1
Sparse estimation methods are aimed at using or obtaining parsimonious representations of data or models. They were first dedicated to linear variable selection but numerous extens…
Multi-scale Mining of fMRI data with Hierarchical Structured Sparsity
Rodolphe Jenatton, Alexandre Gramfort, Vincent Michel +4
Inverse inference, or "brain reading", is a recent paradigm for analyzing functional magnetic resonance imaging (fMRI) data, based on pattern recognition and statistical learning.…
Convex and Network Flow Optimization for Structured Sparsity
Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski +1
We consider a class of learning problems regularized by a structured sparsity-inducing norm defined as the sum of l_2- or l_infinity-norms over groups of variables. Whereas much ef…