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Volumn 2006, Issue , 2006, Pages 367-373

Learning sparse metrics via linear programming

Author keywords

Convex optimization; Dimensionality reduction; Linear programming; Linear projections; Metric learning; Relative distance constraints

Indexed keywords

CONFORMAL MAPPING; FUNCTION EVALUATION; LINEAR PROGRAMMING; OBJECT RECOGNITION; OPTIMIZATION; PROBLEM SOLVING;

EID: 33749562338     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1150402.1150444     Document Type: Conference Paper
Times cited : (69)

References (18)
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    • G. Fung, O. L. Mangasarian, and A. Smola. Minimal kernel classifiers. Journal of Machine Learning Research, pages 303-321, 2002. University of Wisconsin Data Mining Institute Technical Report 00-08, November 200, ftp://ftp.cs.wisc.edu/pub/dini/tech-reports/00-08.ps.
    • (2002) Journal of Machine Learning Research , pp. 303-321
    • Fung, G.1    Mangasarian, O.L.2    Smola, A.3
  • 8
    • 0004236492 scopus 로고    scopus 로고
    • The John Hopkins University Press, Baltimore, Maryland, 3rd edition
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    • A global geometric framework for nonlinear dimensionality reduction
    • J. B. Tenenbaum, V. de Silva, and J. C. Langford. A global geometric framework for nonlinear dimensionality reduction. Science, 290:2319-2323, 2000.
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    • Tenenbaum, J.B.1    De Silva, V.2    Langford, J.C.3
  • 14
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    • SDPT3 - A Matlab software package for semidefinite programming
    • K. C. Toh, M. J. Todd, and R. Tutuncu. SDPT3 - a Matlab software package for semidefinite programming. Optimization Methods and Software, 11:545-581, 1999.
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    • Toh, K.C.1    Todd, M.J.2    Tutuncu, R.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.