On constrained sparse matrix factorization

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2007, Pages

  Zheng, Wei Shi ^a   Li, Stan Z ^b   Lai, J H ^a   Liao, Shengcai ^b  

^a SUN YAT SEN UNIVERSITY   (China)

^b INSTITUTE OF AUTOMATION   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER NETWORKS; COMPUTER VISION; FACTORIZATION; IMAGE PROCESSING; LIGHT MEASUREMENT; ONLINE SEARCHING;

INTERNATIONAL CONFERENCES; SPARSE MATRIX FACTORIZATION;

FEATURE EXTRACTION;

EID: 50649093063     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2007.4408911     Document Type: Conference Paper

References (15)

1. D. D. Lee and H. S. Seung. Learning the parts of objects by non-negative matrix factorization. Nature, 401: 788-791, 1999.
2. R. Zass and A. Shashua. Nonnegative Sparse PCA. NIPS 2006.
3. D. D. Lee and H. S. Seung. Algorithms for non-negative matrix factorization. NIPS, 2000.
4. P. S. Penev and J. J. Atick. Local feature analysis: a general statistical theory for object representation. Network: Computation in Neural Systems, 7(3): 477-500, 1996.
5. MIT Center for Biological and Computation Learning, CBCL Face Database #1, http://www.ai.mit.edu/projects/cbcl.
6. M. D. Plumbley. Algorithms for non-negative independent component analysis. IEEE TNN, 14(3): 534-543, 2003.
7. th Workshop on Text Mining, SDM 2006.
8. P.O. Hoyer. Non-negative matrix factorization with sparseness constraints. JMLR, 5: 1457-1469, 2004.
9. P.O. Hoyer. Nonnegative Sparse Coding. Proc. IEEE Workshop Neural Networks for Signal Processing, 2002.
10. Hyvärinen, J. Karhunen, and E. Oja. Independent Component Analysis. John Wiley and Sons, 2001.
11. S. Z. Li, X. Hou, H. Zhang, and Q. Cheng. Learning spatially localized parts-based representations. CVPR, 2001.
12. D. Donoho and V. Stodden. When does non-negative matrix factorization give a correct decomposition into parts? NIPS, 2003.
13. A. Pascual-Montano, J. M. Carazo, K. Kochi, D. Lehmann, and R. D. Pascual-Marqui. Nonsmooth non-negative matrix factorization (nsNMF). IEEE TPAMI, 28(3): 403-415, 2006.
14. H. Zou, T. Hastie, and R. Tibshirani, "Sparse principal component analysis," Technical Report, Statistics Department, Stanford University, 2004.
15. M. Kirby and L. Sirovich. Application of the karhunenloeve procedure for the characterization of human faces. IEEE TPAMI, 12(1): 103-108, 1990.