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CVPR
2011
IEEE

Online Group-Structured Dictionary Learning

8 years 6 months ago
Online Group-Structured Dictionary Learning
We develop a dictionary learning method which is (i) online, (ii) enables overlapping group structures with (iii) non-convex sparsity-inducing regularization and (iv) handles the partially observable case. Structured sparsity and the related group norms have recently gained widespread attention in group-sparsity regularized problems in the case when the dictionary is assumed to be known and fixed. However, when the dictionary also needs to be learned, the problem is much more difficult. Only a few methods have been proposed to solve this problem, and they can handle two of these four desirable properties at most. To the best of our knowledge, our proposed method is the first one that possesses all of these properties. We investigate several interesting special cases of our framework, such as the online, structured, sparse non-negative matrix factorization, and demonstrate the efficiency of our algorithm with several numerical experiments.
Zoltan Szabo, Barnabas Poczos, Andras Lorincz
Added 09 Apr 2011
Updated 29 Apr 2011
Type Journal
Year 2011
Where CVPR
Authors Zoltan Szabo, Barnabas Poczos, Andras Lorincz
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