Rusu, Cristian and Dumitrescu, Bogdan Block Orthonormal Overcomplete Dictionary Learning. In: 21st European Signal Processing Conference (EUSIPCO), September 9th-13th, 2013, Marrakesh, Marocco pp. 1-5. (Unpublished) (2013)
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Abstract
In the field of sparse representations, the overcomplete dictionary learning problem is of crucial importance and has a growing application pool where it is used. In this paper we present an iterative dictionary learning algorithm based on the singular value decomposition that efficiently construct unions of orthonormal bases. The important innovation described in this paper, that affects positively the running time of the learning procedures, is the way in which the sparse representations are computed - data are reconstructed in a single orthonormal base, avoiding slow sparse approximation algorithms - how the bases in the union are used and updated individually and how the union itself is expanded by looking at the worst reconstructed data items. The numerical experiments show conclusively the speedup induced by our method when compared to previous works, for the same target representation error.
| Item Type: | Conference or Workshop Item (Paper) |
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| Additional Information: | This work was supported by the Romanian National Authority for Scientific Research, CNCS - UEFISCDI, project number PN-II-ID-PCE-2011-3-0400. |
| Uncontrolled Keywords: | Sparse representations, orthogonal blocks, overcomplete dictionary learning |
| Subjects: | P Language and Literature > P Philology. Linguistics Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Research Area: | Computer Science and Applications |
| Depositing User: | Ms T. Iannizzi |
| Date Deposited: | 05 Nov 2013 11:14 |
| Last Modified: | 05 Nov 2013 11:14 |
| URI: | http://eprints.imtlucca.it/id/eprint/1856 |
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