Szabo, Z;
Póczos, B;
Lőrincz, A;
(2011)
Online Group-Structured Dictionary Learning.
In:
2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
(pp. 2865 - 2872).
IEEE
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Abstract
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.
| Type: | Proceedings paper |
|---|---|
| Title: | Online Group-Structured Dictionary Learning |
| Event: | IEEE Computer Vision and Pattern Recognition (CVPR) |
| Location: | Providence, RI, USA |
| Dates: | 2011-06-20 - 2011-06-25 |
| ISBN-13: | 978-1-4577-0394-2 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/CVPR.2011.5995712 |
| Publisher version: | http://dx.doi.org/10.1109/CVPR.2011.5995712 |
| Language: | English |
| Additional information: | © 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1433155 |
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