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Volumn 3889 LNCS, Issue , 2006, Pages 295-302

Riemannian optimization method on the flag manifold for independent subspace analysis

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING ALGORITHMS; MATHEMATICAL MODELS; OPTIMIZATION; PROBLEM SOLVING; STATE SPACE METHODS;

EID: 33745697492     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11679363_37     Document Type: Conference Paper
Times cited : (39)

References (10)
  • 1
    • 1442336159 scopus 로고    scopus 로고
    • Riemannian geometry of Grassmann manifolds with a view on algorithmic computation
    • P-A. Absil, R. Mahony, and R. Sepulchre, Riemannian geometry of Grassmann manifolds with a view on algorithmic computation, Acta Applicandae Mathematicae, 80(2), pp. 199-220, 2004.
    • (2004) Acta Applicandae Mathematicae , vol.80 , Issue.2 , pp. 199-220
    • Absil, P.-A.1    Mahony, R.2    Sepulchre, R.3
  • 2
    • 0000396062 scopus 로고    scopus 로고
    • Natural gradient works efficiently in learning
    • S. Amari, Natural gradient works efficiently in Learning, Neural Computation, 10, pp.251-276, 1998.
    • (1998) Neural Computation , vol.10 , pp. 251-276
    • Amari, S.1
  • 4
    • 21844443579 scopus 로고    scopus 로고
    • Quasi-geodesic neural learning algorithms over the orthogonal group: A tutorial
    • S. Fiori, Quasi-Geodesic Neural Learning Algorithms over the Orthogonal Group: A Tutorial, Journal of Machine Learning Research, 6, pp.743-781, 2005.
    • (2005) Journal of Machine Learning Research , vol.6 , pp. 743-781
    • Fiori, S.1
  • 7
    • 0034222304 scopus 로고    scopus 로고
    • Emergence of phase and shift invariant features by decomposition of natural images into independent feature subspaces
    • A. Hyvärinen and P.O. Hoyer, Emergence of phase and shift invariant features by decomposition of natural images into independent feature subspaces. Neural Computation, 12(7), pp.1705-1720, 2000.
    • (2000) Neural Computation , vol.12 , Issue.7 , pp. 1705-1720
    • Hyvärinen, A.1    Hoyer, P.O.2
  • 9
    • 21744442796 scopus 로고    scopus 로고
    • Learning algorithms utilizing quasi-geodesic flows on the stiefel manifold
    • Y. Nishimori and S. Akaho, Learning Algorithms Utilizing Quasi-Geodesic Flows on the Stiefel Manifold, Neurocomputing, 67 pp.106-135, 2005.
    • (2005) Neurocomputing , vol.67 , pp. 106-135
    • Nishimori, Y.1    Akaho, S.2
  • 10
    • 0038460232 scopus 로고    scopus 로고
    • Algorithms for non-negative independent component analysis
    • M. D. Plumbley, Algorithms for non-negative independent component analysis. IEEE Transactions on Neural Networks, 14(3), pp.534-543, 2003.
    • (2003) IEEE Transactions on Neural Networks , vol.14 , Issue.3 , pp. 534-543
    • Plumbley, M.D.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.