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Volumn , Issue , 2010, Pages 1-6

Efficient online learning of a non-negative sparse autoencoder

Author keywords

[No Author keywords available]

Indexed keywords

BATCH ALGORITHMS; BENCHMARK DATASETS; NON NEGATIVES; NON-NEGATIVE SPARSE CODING; NONNEGATIVE MATRIX FACTORIZATION; ONLINE LEARNING; RECONSTRUCTION ERROR; SPARSENESS CONSTRAINTS;

EID: 84863864196     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (18)

References (14)
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    • M. Spratling. Learning Image Components for Object Recognition. Mach. Learn., 2006.
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    • Spratling, M.1
  • 2
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    • D. D. Lee, and H. S. Seung. Learning the parts of objects by nonnegative matrix factorization. Nature, pp. 788-791, 1999.
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    • Lee, D.D.1    Seung, H.S.2
  • 4
    • 84900510076 scopus 로고    scopus 로고
    • Non-negative Matrix Factorization with Sparseness Constraints
    • P. O. Hoyer. Non-negative Matrix Factorization with Sparseness Constraints. Journal of Machine Learning Research, pp. 1457-1469, 2004.
    • (2004) Journal of Machine Learning Research , pp. 1457-1469
    • Hoyer, P.O.1
  • 5
    • 70049094447 scopus 로고    scopus 로고
    • Sparse Feature Learning for Deep Belief Networks
    • Y-lan Boureau and Y. Lecun. Sparse Feature Learning for Deep Belief Networks. NIPS, pp. 1-8, 2007.
    • (2007) NIPS , pp. 1-8
    • Boureau, Y.-L.1    Lecun, Y.2
  • 7
    • 1242331294 scopus 로고    scopus 로고
    • A "nonnegative PCA" algorithm for independent component analysis
    • M. D. Plumbley and O. Erkki. A "nonnegative PCA" algorithm for independent component analysis. Neural Networks, pp. 66-76, 2004.
    • (2004) Neural Networks , pp. 66-76
    • Plumbley, M.D.1    Erkki, O.2
  • 8
    • 33646185004 scopus 로고    scopus 로고
    • A Gradient Rule for the Plasticity of a Neuron's Intrinsic Excitability
    • J. Triesch. A Gradient Rule for the Plasticity of a Neuron's Intrinsic Excitability. Neural Computation, pp. 65-70, 2005.
    • (2005) Neural Computation , pp. 65-70
    • Triesch, J.1
  • 10
    • 33745805403 scopus 로고    scopus 로고
    • A fast learning algorithm for deep belief nets
    • G. E. Hinton and S. Osindero. A fast learning algorithm for deep belief nets. Neural Computation, pp. 1527-54, 2006.
    • (2006) Neural Computation , pp. 1527-1554
    • Hinton, G.E.1    Osindero, S.2
  • 11
    • 56449089103 scopus 로고    scopus 로고
    • Extracting and composing robust features with denoising autoencoders
    • P. Vincent and H. Larochelle and Y. Bengio. Extracting and composing robust features with denoising autoencoders ICML'08, pp. 1096-1103, 2008.
    • (2008) ICML'08 , pp. 1096-1103
    • Vincent, P.1    Larochelle, H.2    Bengio, Y.3
  • 12
    • 10944225085 scopus 로고    scopus 로고
    • Backpropagation-Decorrelation: Online recurrent learning with O(N) complexity
    • J. J. Steil. Backpropagation-Decorrelation: online recurrent learning with O(N) complexity Proc. IJCNN, pp. 843-848, 2004.
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    • Steil, J.J.1
  • 13
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    • Synergies Between Intrinsic and Synaptic Plasticity Mechanisms
    • J. Triesch. Synergies Between Intrinsic and Synaptic Plasticity Mechanisms. Neural Computation, pp. 885-909, 2007.
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  • 14
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    • The MNIST database of handwritten digits
    • Y. Lecun and C. Cortes. The MNIST database of handwritten digits. http://yann.lecun.com/exdb/mnist.
    • Lecun, Y.1    Cortes, C.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.