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Volumn , Issue , 2009, Pages 609-616

Kernel change-point analysis

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; ESTIMATION; STATISTICAL TESTS;

EID: 84858765869     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (180)

References (24)
  • 2
    • 0142192295 scopus 로고    scopus 로고
    • Conditional random fields: Probabilistic models for segmenting and labeling sequence data
    • J. Lafferty, A. McCallum, and F. Pereira. Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In Proc. ICML, 2001.
    • (2001) Proc. ICML
    • Lafferty, J.1    McCallum, A.2    Pereira, F.3
  • 7
    • 0346405517 scopus 로고    scopus 로고
    • Sequential analysis: Some classical problems and new challenges
    • T. L. Lai. Sequential analysis: some classical problems and new challenges. Statistica Sinica, 11, 2001.
    • (2001) Statistica Sinica , vol.11
    • Lai, T.L.1
  • 9
    • 85162067877 scopus 로고    scopus 로고
    • Testing for homogeneity with kernel Fisher discriminant analysis
    • Z. Harchaoui, F. Bach, and E. Moulines. Testing for homogeneity with kernel Fisher discriminant analysis. In Adv. NIPS, 2007.
    • (2007) Adv. NIPS
    • Harchaoui, Z.1    Bach, F.2    Moulines, E.3
  • 10
    • 33847676413 scopus 로고    scopus 로고
    • Statistical properties of kernel principal component analysis
    • G. Blanchard, O. Bousquet, and L. Zwald. Statistical properties of kernel principal component analysis. Machine Learning, 66, 2007.
    • (2007) Machine Learning , vol.66
    • Blanchard, G.1    Bousquet, O.2    Zwald, L.3
  • 11
    • 33847186281 scopus 로고    scopus 로고
    • Statistical convergence of kernel canonical correlation analysis
    • K. Fukumizu, F. Bach, and A. Gretton. Statistical convergence of kernel canonical correlation analysis. JLMR, 8, 2007.
    • (2007) JLMR , vol.8
    • Fukumizu, K.1    Bach, F.2    Gretton, A.3
  • 21
    • 51349154782 scopus 로고    scopus 로고
    • Finite-dimensional projection for classification and statistical learning
    • G. Blanchard and L. Zwald. Finite-dimensional projection for classification and statistical learning. IEEE Transactions on Information Theory, 54(9):4169-4182, 2008.
    • (2008) IEEE Transactions on Information Theory , vol.54 , Issue.9 , pp. 4169-4182
    • Blanchard, G.1    Zwald, L.2
  • 22
    • 70349226806 scopus 로고    scopus 로고
    • A regularized kernel-based approach to unsupervised audio segmentation
    • Z. Harchaoui, F. Vallet, A. Lung-Yut-Fong, and O. Cappé. A regularized kernel-based approach to unsupervised audio segmentation. In ICASSP, 2009.
    • (2009) ICASSP
    • Harchaoui, Z.1    Vallet, F.2    Lung-Yut-Fong, A.3    Cappé, O.4
  • 23
    • 25444451110 scopus 로고    scopus 로고
    • An online Kernel change detection algorithm
    • DOI 10.1109/TSP.2005.851098
    • F. Désobry, M. Davy, and C. Doncarli. An online kernel change detection algorithm. IEEE Trans. on Signal Processing, 53(8):2961-2974, August 2005. (Pubitemid 41372807)
    • (2005) IEEE Transactions on Signal Processing , vol.53 , Issue.8 , pp. 2961-2974
    • Desobry, F.1    Davy, M.2    Doncarli, C.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.