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Volumn , Issue , 2007, Pages 641-650

Sampling-based dimension reduction for subspace approximation

Author keywords

Subspace approximation

Indexed keywords

ERROR ANALYSIS; OPTIMIZATION; PROBABILITY; PROBLEM SOLVING;

EID: 35448929865     PISSN: 07378017     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1250790.1250884     Document Type: Conference Paper
Times cited : (58)

References (13)
  • 2
    • 20444450258 scopus 로고    scopus 로고
    • Fast Monte Carlo Algorithms for Matrices II: Computing a Low-Rank Approximation to a Matrix
    • YALEU/DCS/TR-1270
    • P. Drineas, R. Kannan, M. Mahoney. Fast Monte Carlo Algorithms for Matrices II: Computing a Low-Rank Approximation to a Matrix. Yale University Technical R-eport, YALEU/DCS/TR-1270, 2004.
    • (2004) Yale University Technical R-eport
    • Drineas, P.1    Kannan, R.2    Mahoney, M.3
  • 3
    • 35448972445 scopus 로고    scopus 로고
    • P. Drineas, M. Mahoney, S. Muthukrishnan. Polynomial time algorithm for column-row based relative error low-rank matrix approximation. DIMACS Technical Report 2006-04, 2006.
    • P. Drineas, M. Mahoney, S. Muthukrishnan. Polynomial time algorithm for column-row based relative error low-rank matrix approximation. DIMACS Technical Report 2006-04, 2006.
  • 9
    • 35348843307 scopus 로고    scopus 로고
    • Low-Rank Matrix Approximation in Linear Time
    • manuscript
    • S. Har-Peled. Low-Rank Matrix Approximation in Linear Time, manuscript.
    • Har-Peled, S.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.