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Proximal Methods for Sparse Hierarchical Dictionary Learning

Proximal Methods for Sparse Hierarchical Dictionary Learning,Rodolphe Jenatton,Julien Mairal,Guillaume Obozinski,Francis Bach

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Proximal Methods for Sparse Hierarchical Dictionary Learning   (Citations: 17)
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We propose to combine two approaches for mod- eling data admitting sparse representations: on the one hand, dictionary learning has proven ef- fective for various signal processing tasks. On the other hand, recent work on structured spar- sity provides a natural framework for modeling dependencies between dictionary elements. We thus consider a tree-structured sparse regulariza- tion to learn dictionaries embedded in a hierar- chy. The involved proximal operator is com- putable exactly via a primal-dual method, allow- ing the use of accelerated gradient techniques. Experiments show that for natural image patches, learned dictionary elements organize themselves in such a hierarchical structure, leading to an im- proved performance for restoration tasks. When applied to text documents, our method learns hi- erarchies of topics, thus providing a competitive alternative to probabilistic topic models.
Conference: International Conference on Machine Learning - ICML , pp. 487-494, 2010
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