Share and Export
Share and Export
Potluru, Vamsi K., Le Roux, Jonathan, Pearlmutter, Barak A., Hershey, John R. and Brand, Matthew E. (2013) Coordinate Descent for Mixed-norm NMF. Technical Report. UNSPECIFIED.
Preview
BP-Coordinate-descent.pdf
Download (265kB) | Preview
Abstract
Nonnegative matrix factorization (NMF) is widely used in a variety of machine learning tasks
involving speech, documents and images. Being able to specify the structure of the matrix factors
is crucial in incorporating prior information. The factors correspond to the feature matrix and
the learnt representation. In particular, we allow an user-friendly specification of sparsity on the
groups of features using the L1/L2 measure. Also, we propose a pairwise coordinate descent
algorithm to minimize the objective. Experimental evidence of the efficacy of this approach is
provided on the ORL faces dataset.
| Item Type: | Monograph (Technical Report) |
|---|---|
| Additional Information: | This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All rights reserved. |
| Keywords: | Coordinate Descent; Mixed-norm NMF; Nonnegative matrix factorization; machine learning; |
| Academic Unit: | Faculty of Science and Engineering > Computer Science |
| Item ID: | 6553 |
| Identification Number: | TR2013-130 |
| Depositing User: | Barak Pearlmutter |
| Date Deposited: | 10 Nov 2015 16:43 |
| URI: | https://mural.maynoothuniversity.ie/id/eprint/6553 |
| Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
Repository Staff Only (login required)
- Item control page
Downloads
Downloads per month over past year
