Sparse coding and NMF

IEEE International Conference on Neural Networks - Conference Proceedings

Volumn 4, Issue , 2004, Pages 2529-2533

  Eggert, Julian ^a   Körner, Edgar ^a  

^a HONDA RESEARCH INSTITUTE EUROPE GMBH   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATIVE RECONSTRUCTION; LOCAL MINIMUM; NON-NEGATIVE MATRIX FACTORIZATION (NMF); SPARSE CODING;

ALGORITHMS; COMPUTER SIMULATION; COSTS; IMAGE RECONSTRUCTION; LEARNING SYSTEMS; MATRIX ALGEBRA; STATISTICS; VECTOR QUANTIZATION; VECTORS;

IMAGE CODING;

EID: 10944227316     PISSN: 10987576     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2004.1381036     Document Type: Conference Paper

References (6)

1. P. O. Hoyer. Modeling receptive fields with non-negative sparse coding. In Tenth Annual Computational Neuroscience Meeting (CNS), Chicago, Illinois, 2002. Conference proceedings paper.
2. P. O. Hoyer. Non-negative sparse coding. In NNSP 2002 conference proceedings, 2002. Conference proceedings paper.
3. D. D. Lee and H. S. Seung. Learning the parts of objects with nonnegative matrix factorization. Nature, 401:788-791, 1999.
4. D. D. Lee and H. S. Seung. Algorithms for non-negative matrix factorization. In Todd K. Leen, Thomas G. Dietterich, and Volker Tresp, editors. Advances in Neural Information Processing Systems 13, pages 556-562. MIT Press, 2001.
5. B. A. Olshausen. Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature, pages 607-609, 1996.
6. H. Wersing, J. Eggert, and E. Körner. Sparse coding with invariance constraints. In ICANN/ICONIP 2003 conference proceedings, 2003. Conference proceedings paper.