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Volumn 4, Issue January, 2014, Pages 3113-3121

Improved distributed principal component analysis

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION THEORY; COMPUTATIONAL EFFICIENCY; COST BENEFIT ANALYSIS; DISTRIBUTED COMPUTER SYSTEMS; GEOMETRY; INFORMATION SCIENCE; PROBABILITY;

EID: 84937837293     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (129)

References (22)
  • 11
    • 79960425522 scopus 로고    scopus 로고
    • Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions
    • N. Halko, P.-G. Martinsson, and J. A. Tropp. Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions. SIAM review, 2011.
    • (2011) SIAM Review
    • Halko, N.1    Martinsson, P.-G.2    Tropp, J.A.3
  • 13
    • 84937896941 scopus 로고    scopus 로고
    • Combining structured and unstructured randomness in large scale PCA
    • N. Karampatziakis and P. Mineiro. Combining structured and unstructured randomness in large scale pca. CoRR, abs/1310.6304, 2013.
    • (2013) CoRR, abs/1310.6304
    • Karampatziakis, N.1    Mineiro, P.2
  • 14
    • 50849139935 scopus 로고    scopus 로고
    • Distributed principal component analysis for wireless sensor networks
    • Y.-A. Le Borgne, S. Raybaud, and G. Bontempi. Distributed principal component analysis for wireless sensor networks. Sensors, 2008.
    • (2008) Sensors
    • Le Borgne, Y.-A.1    Raybaud, S.2    Bontempi, G.3
  • 22


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.