
Tight convex relaxations for sparse matrix factorization
Based on a new atomic norm, we propose a new convex formulation for spar...
07/19/2014 ∙ by Emile Richard, et al. ∙ 0 ∙ shareread it

Convex Relaxation for Combinatorial Penalties
In this paper, we propose an unifying view of several recently proposed ...
05/06/2012 ∙ by Guillaume Obozinski, et al. ∙ 0 ∙ shareread it

On the Equivalence between Herding and Conditional Gradient Algorithms
We show that the herding procedure of Welling (2009) takes exactly the f...
03/20/2012 ∙ by Francis Bach, et al. ∙ 0 ∙ shareread it

Group Lasso with Overlaps: the Latent Group Lasso approach
We study a norm for structured sparsity which leads to sparse linear pre...
10/03/2011 ∙ by Guillaume Obozinski, et al. ∙ 0 ∙ shareread it

Structured sparsity through convex optimization
Sparse estimation methods are aimed at using or obtaining parsimonious r...
09/12/2011 ∙ by Francis Bach, et al. ∙ 0 ∙ shareread it

Trace Lasso: a trace norm regularization for correlated designs
Using the ℓ_1norm to regularize the estimation of the parameter vector ...
09/09/2011 ∙ by Edouard Grave, et al. ∙ 0 ∙ shareread it

Optimization with SparsityInducing Penalties
Sparse estimation methods are aimed at using or obtaining parsimonious r...
08/03/2011 ∙ by Francis Bach, et al. ∙ 0 ∙ shareread it

Multiscale Mining of fMRI data with Hierarchical Structured Sparsity
Inverse inference, or "brain reading", is a recent paradigm for analyzin...
05/02/2011 ∙ by Rodolphe Jenatton, et al. ∙ 0 ∙ shareread it

Convex and Network Flow Optimization for Structured Sparsity
We consider a class of learning problems regularized by a structured spa...
04/11/2011 ∙ by Julien Mairal, et al. ∙ 0 ∙ shareread it

Proximal Methods for Hierarchical Sparse Coding
Sparse coding consists in representing signals as sparse linear combinat...
09/11/2010 ∙ by Rodolphe Jenatton, et al. ∙ 0 ∙ shareread it

Network Flow Algorithms for Structured Sparsity
We consider a class of learning problems that involve a structured spars...
08/31/2010 ∙ by Julien Mairal, et al. ∙ 0 ∙ shareread it

Structured Sparse Principal Component Analysis
We present an extension of sparse PCA, or sparse dictionary learning, wh...
09/08/2009 ∙ by Rodolphe Jenatton, et al. ∙ 0 ∙ shareread it

Support union recovery in highdimensional multivariate regression
In multivariate regression, a Kdimensional response vector is regressed...
08/05/2008 ∙ by Guillaume Obozinski, et al. ∙ 0 ∙ shareread it

Canonical Tensor Decomposition for Knowledge Base Completion
The problem of Knowledge Base Completion can be framed as a 3rdorder bi...
06/19/2018 ∙ by Timothée Lacroix, et al. ∙ 0 ∙ shareread it

Learning the effect of latent variables in Gaussian Graphical models with unobserved variables
The edge structure of the graph defining an undirected graphical model d...
07/20/2018 ∙ by Marina Vinyes, et al. ∙ 0 ∙ shareread it

A direct approach to detection and attribution of climate change
We present here a novel statistical learning approach for detection and ...
10/08/2019 ∙ by Eniko Székely, et al. ∙ 0 ∙ shareread it