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Volumn , Issue , 2012, Pages 2278-2281

STPCA: Sparse tensor Principal Component Analysis for feature extraction

Author keywords

[No Author keywords available]

Indexed keywords

EIGEN DECOMPOSITION; GEORGIA; MULTILINEAR PRINCIPAL COMPONENT ANALYSIS (MPCA); OCCLUSION PROBLEMS; PROJECTION MATRIX; REGRESSION PROBLEM; SEMANTIC INTERPRETATION; SPARSE TENSORS; TENSOR SUBSPACE ANALYSIS;

EID: 84874580875     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (22)

References (7)
  • 1
    • 68649096448 scopus 로고    scopus 로고
    • Tensor decompositions and applications
    • T. Kolda and B. Bader. Tensor decompositions and applications. SIAM review, 51(3):455-500, 2009.
    • (2009) SIAM Review , vol.51 , Issue.3 , pp. 455-500
    • Kolda, T.1    Bader, B.2
  • 6
    • 78149311430 scopus 로고    scopus 로고
    • Two-dimensional sparse principal component analysis: A new technique for feature extraction
    • IEEE
    • C. Xiao and Z. Wang. Two-dimensional sparse principal component analysis: A new technique for feature extraction. In Natural Computation (ICNC), 2010 Sixth International Conference on, volume 2, pages 976-980. IEEE.
    • Natural Computation (ICNC), 2010 Sixth International Conference on , vol.2 , pp. 976-980
    • Xiao, C.1    Wang, Z.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.