Learning data representations with sparse coding neural gas

ESANN 2008 Proceedings, 16th European Symposium on Artificial Neural Networks - Advances in Computational Intelligence and Learning

Volumn , Issue , 2008, Pages 233-238

  Labusch, Kai ^a   Barth, Erhardt ^a   Martinetz, Thomas ^a  

^a UNIVERSITY OF LÜBECK   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING DATA; LINEAR COMBINATIONS; NEURAL GAS ALGORITHMS; ORTHOGONAL MATCHING PURSUIT; OVER-COMPLETE; SPARSE CODES; SPARSE CODING; TRAINING SAMPLE;

NEURAL NETWORKS; SAMPLING;

ALGORITHMS;

EID: 58849101822     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (6)

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2. David L. Donoho, Michael Elad, and Vladimir N. Temlyakov. Stable recovery of sparse overcomplete representations in the presence of noise. IEEE Transactions on Information Theory, 52(1):6-18, 2006.
3. T. Martinetz and K. Schulten. A "Neural-Gas Network" Learns Topologies. Artificial Neural Networks, I:397-402, 1991.
4. E. Oja. A simplified neuron model as a principal component analyzer. J. Math. Biol., 15:267-273, 1982.
5. Y. Pati, R. Rezaiifar, and P. Krishnaprasad. Orthogonal matching pursuit: Recursive function approximation with applications to wavelet decomposition. Proceedings of the 27 th Annual Asilomar Conference on Signals, Systems, November 1993.
6. J. A. Tropp. Greed is good: algorithmic results for sparse approximation. IEEE Transactions on Information Theory, 50(10), 2004.