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CORR
2012
Springer
232views Education» more  CORR 2012»
12 years 1 days ago
Smoothing Proximal Gradient Method for General Structured Sparse Learning
We study the problem of learning high dimensional regression models regularized by a structured-sparsity-inducing penalty that encodes prior structural information on either input...
Xi Chen, Qihang Lin, Seyoung Kim, Jaime G. Carbone...
ICDM
2009
IEEE
149views Data Mining» more  ICDM 2009»
13 years 11 months ago
Accelerated Gradient Method for Multi-task Sparse Learning Problem
—Many real world learning problems can be recast as multi-task learning problems which utilize correlations among different tasks to obtain better generalization performance than...
Xi Chen, Weike Pan, James T. Kwok, Jaime G. Carbon...
ICML
2010
IEEE
13 years 5 months ago
Proximal Methods for Sparse Hierarchical Dictionary Learning
We propose to combine two approaches for modeling data admitting sparse representations: on the one hand, dictionary learning has proven effective for various signal processing ta...
Rodolphe Jenatton, Julien Mairal, Guillaume Obozin...
MOR
2010
120views more  MOR 2010»
13 years 2 months ago
Proximal Alternating Minimization and Projection Methods for Nonconvex Problems: An Approach Based on the Kurdyka-Lojasiewicz In
We study the convergence properties of an alternating proximal minimization algorithm for nonconvex structured functions of the type: L(x, y) = f(x)+Q(x, y)+g(y), where f : Rn → ...
Hedy Attouch, Jérôme Bolte, Patrick R...
CORR
2011
Springer
261views Education» more  CORR 2011»
12 years 11 months ago
Convex and Network Flow Optimization for Structured Sparsity
We consider a class of learning problems regularized by a structured sparsity-inducing norm defined as the sum of 2- or ∞-norms over groups of variables. Whereas much effort ha...
Julien Mairal, Rodolphe Jenatton, Guillaume Obozin...