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Volumn , Issue , 2009, Pages 601-608

Extended Grassmann kernels for subspace-based learning

Author keywords

[No Author keywords available]

Indexed keywords

DISCRIMINANT ANALYSIS; VECTORS;

EID: 84863338333     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (51)

References (18)
  • 4
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    • The em algorithm for mixtures of factor analyzers
    • Department of Computer Science, University of Toronto
    • Zoubin Ghahramani and Geoffrey E. Hinton. The EM algorithm for mixtures of factor analyzers. Technical Report CRG-TR-96-1, Department of Computer Science, University of Toronto, 21 1996.
    • (1996) Technical Report CRG-TR-96-1 , vol.21
    • Ghahramani, Z.1    Hinton, G.E.2
  • 5
    • 80053110323 scopus 로고    scopus 로고
    • Ph.D thesis in Electrical and Systems Engineering, University of Pennsylvania
    • Jihun Hamm. Subspace-based Learning with Grassmann Manifolds. Ph.D thesis in Electrical and Systems Engineering, University of Pennsylvania, 2008. Available at http://www.seas.upenn.edu/ jhham/Papers/thesis-jh.pdf.
    • (2008) Subspace-based Learning with Grassmann Manifolds
    • Hamm, J.1
  • 6
    • 56449127949 scopus 로고    scopus 로고
    • Grassmann discriminant analysis: A unifying view on subspace-based learning
    • Jihun Hamm and Daniel Lee. Grassmann discriminant analysis: a unifying view on subspace-based learning. In Int. Conf. Mach. Learning, 2008.
    • (2008) Int. Conf. Mach. Learning
    • Hamm, J.1    Lee, D.2
  • 7
    • 9444269199 scopus 로고    scopus 로고
    • Bhattacharyya expected likelihood kernels
    • Tony Jebara and Risi Imre Kondor. Bhattacharyya expected likelihood kernels. In COLT, pages 57-71, 2003.
    • (2003) COLT , pp. 57-71
    • Jebara, T.1    Kondor, R.I.2
  • 9
    • 0042441074 scopus 로고    scopus 로고
    • Analyzing appearance and contour based methods for object categorization
    • Bastian Leibe and Bernt Schiele. Analyzing appearance and contour based methods for object categorization. CVPR, 02:409, 2003.
    • (2003) CVPR , vol.2 , pp. 409
    • Leibe, B.1    Schiele, B.2
  • 13
    • 51949097477 scopus 로고    scopus 로고
    • Statistical analysis on Stiefel and Grassmann manifolds with applications in computer vision
    • Pavan Turaga, Ashok Veeraraghavan, and Rama Chellappa. Statistical analysis on Stiefel and Grassmann manifolds with applications in computer vision. In CVPR, 2008.
    • (2008) CVPR
    • Turaga, P.1    Veeraraghavan, A.2    Chellappa, R.3
  • 16
    • 29144498423 scopus 로고    scopus 로고
    • Subspace distance analysis with application to adaptive Bayesian algorithm for face recognition
    • DOI 10.1016/j.patcog.2005.08.015, PII S003132030500381X
    • LiweiWang, XiaoWang, and Jufu Feng. Subspace distance analysis with application to adaptive bayesian algorithm for face recognition. Pattern Recogn., 39(3):456-464, 2006. (Pubitemid 41808626)
    • (2006) Pattern Recognition , vol.39 , Issue.3 , pp. 456-464
    • Wang, L.1    Wang, X.2    Feng, J.3
  • 17
    • 4644322072 scopus 로고    scopus 로고
    • Learning over sets using kernel principal angles
    • Lior Wolf and Amnon Shashua. Learning over sets using kernel principal angles. J. Mach. Learn. Res., 4:913-931, 2003.
    • (2003) J. Mach. Learn. Res. , vol.4 , pp. 913-931
    • Wolf, L.1    Shashua, A.2
  • 18
    • 33645988196 scopus 로고    scopus 로고
    • From sample similarity to ensemble similarity: Probabilistic distance measures in Reproducing Kernel Hilbert Space
    • Shaohua Kevin Zhou and Rama Chellappa. From sample similarity to ensemble similarity: Probabilistic distance measures in Reproducing Kernel Hilbert Space. IEEE Trans. Pattern Anal. Mach. Intell., 28(6):917-929, 2006.
    • (2006) IEEE Trans. Pattern Anal. Mach. Intell. , vol.28 , Issue.6 , pp. 917-929
    • Zhou, S.K.1    Chellappa, R.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.