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Volumn , Issue , 2011, Pages

Scalable training of mixture models via coresets

Author keywords

[No Author keywords available]

Indexed keywords

CORE SET; DATAPOINTS; GAUSSIAN-MIXTURES; MASSIVE DATA SETS; MIXTURE MODELING; MIXTURE OF GAUSSIANS; MODEL FITTING; NATURAL GENERALIZATION; SIZE INDEPENDENTS;

EID: 85162421236     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (128)

References (23)
  • 2
    • 33846677514 scopus 로고    scopus 로고
    • Sublinear-time approximation algorithms for clustering via random sampling
    • A. Czumaj and C. Sohler. Sublinear-time approximation algorithms for clustering via random sampling. Random Struct. Algorithms (RSA), 30(1-2):226-256, 2007.
    • (2007) Random Struct. Algorithms (RSA) , vol.30 , Issue.1-2 , pp. 226-256
    • Czumaj, A.1    Sohler, C.2
  • 3
    • 14544275956 scopus 로고    scopus 로고
    • Learning mixtures of separated nonspherical gaussians
    • Sanjeev Arora and Ravi Kannan. Learning mixtures of separated nonspherical gaussians. Annals of Applied Probability, 15(1A):69-92, 2005.
    • (2005) Annals of Applied Probability , vol.15 , Issue.1 A , pp. 69-92
    • Arora, S.1    Kannan, R.2
  • 5
    • 33846811413 scopus 로고    scopus 로고
    • Smaller coresets for κ-median and κ-means clustering
    • S. Har-Peled and A. Kushal. Smaller coresets for κ-median and κ-means clustering. Discrete & Computational Geometry, 37(1):3-19, 2007.
    • (2007) Discrete & Computational Geometry , vol.37 , Issue.1 , pp. 3-19
    • Har-Peled, S.1    Kushal, A.2
  • 7
    • 0000108833 scopus 로고
    • Decomposable searching problems i: Static-to-dynamic transformation
    • Jon Louis Bentley and James B. Saxe. Decomposable searching problems i: Static-to-dynamic transformation. J. Algorithms, 1(4):301-358, 1980.
    • (1980) J. Algorithms , vol.1 , Issue.4 , pp. 301-358
    • Bentley, J.L.1    Saxe, J.B.2
  • 17
    • 84889743261 scopus 로고    scopus 로고
    • Pac learning axis-aligned mixtures of gaussians with no separation assumption
    • J. Feldman, R. A. Servedio, and R. O'Donnell. Pac learning axis-aligned mixtures of gaussians with no separation assumption. In COLT, 2006.
    • (2006) COLT
    • Feldman, J.1    Servedio, R.A.2    O'donnell, R.3
  • 20
    • 0002192516 scopus 로고
    • Decision theoretic generalizations of the PAC model for neural net and other learning applications
    • D. Haussler. Decision theoretic generalizations of the PAC model for neural net and other learning applications. Inf. Comput., 100(1):78-150, 1992.
    • (1992) Inf. Comput. , vol.100 , Issue.1 , pp. 78-150
    • Haussler, D.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.