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Volumn , Issue , 2002, Pages

On spectral clustering: Analysis and an algorithm

Author keywords

[No Author keywords available]

Indexed keywords

EIGENVALUES AND EIGENFUNCTIONS; PERTURBATION TECHNIQUES;

EID: 84899013108     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (4839)

References (11)
  • 1
    • 0002334967 scopus 로고    scopus 로고
    • Spectral partitioning: The more eigenvectors, the better
    • C. Alpert, A. Kahng, and S. Yao. Spectral partitioning: The more eigenvectors, the better. Discrete Applied Math, 90:3-26, 1999.
    • (1999) Discrete Applied Math , vol.90 , pp. 3-26
    • Alpert, C.1    Kahng, A.2    Yao, S.3
  • 7
    • 0347243182 scopus 로고    scopus 로고
    • Nonlinear component analysis as a kernel eigenvalue problem
    • B. Scholkopf, A. Smola, and K.-R Mtiller. Nonlinear component analysis as a kernel eigenvalue problem. Neural Computation, 10:1299-1319, 1998.
    • (1998) Neural Computation , vol.10 , pp. 1299-1319
    • Scholkopf, B.1    Smola, A.2    Mtiller, K.-R.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.