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Volumn , Issue , 2013, Pages 89-94

Semi-supervised vector quantization for proximity data

Author keywords

[No Author keywords available]

Indexed keywords

LABELED AND UNLABELED DATA; LIFE-SCIENCES; SEMI-SUPERVISED; SEMI-SUPERVISED LEARNING (SSL); STATISTICAL INFORMATION; TIME CONSTRAINTS; UNLABELED DATA;

EID: 84887051683     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (6)

References (10)
  • 7
    • 78149341007 scopus 로고    scopus 로고
    • Topographic mapping of large dissimilarity data sets
    • Barbara Hammer and Alexander Hasenfuss. Topographic mapping of large dissimilarity data sets. Neural Computation, 22(9):2229-2284, 2010.
    • (2010) Neural Computation , vol.22 , Issue.9 , pp. 2229-2284
    • Hammer, B.1    Hasenfuss, A.2
  • 8
    • 85156210800 scopus 로고
    • Generalized learning vector quantization
    • David S. Touretzky, Michael Mozer, and Michael E. Hasselmo, editors, MIT Press
    • Atsushi Sato and Keiji Yamada. Generalized learning vector quantization. In David S. Touretzky, Michael Mozer, and Michael E. Hasselmo, editors, NIPS, pages 423-429. MIT Press, 1995.
    • (1995) NIPS , pp. 423-429
    • Sato, A.1    Yamada, K.2
  • 10
    • 33745360257 scopus 로고    scopus 로고
    • Edit distance based kernel functions for structural pattern classification
    • M. Neuhaus and H. Bunke. Edit distance based kernel functions for structural pattern classification. Pattern Recognition, 39(10):1852-1863, 2006.
    • (2006) Pattern Recognition , vol.39 , Issue.10 , pp. 1852-1863
    • Neuhaus, M.1    Bunke, H.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.