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Volumn , Issue , 2013, Pages

Memory limited, streaming PCA

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; DIGITAL STORAGE; PRINCIPAL COMPONENT ANALYSIS; WHITE NOISE;

EID: 84898955433     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (159)

References (22)
  • 3
    • 33645149161 scopus 로고    scopus 로고
    • Fast low-rank modifications of the thin singular value decomposition
    • Brand, M. Fast low-rank modifications of the thin singular value decomposition. Linear algebra and its applications, 415(1):20-30, 2006.
    • (2006) Linear Algebra and Its Applications , vol.415 , Issue.1 , pp. 20-30
    • Brand, M.1
  • 4
    • 84944416149 scopus 로고    scopus 로고
    • Incremental singular value decomposition of uncertain data with missing values
    • Brand, Matthew. Incremental singular value decomposition of uncertain data with missing values. Computer Vision-ECCV 2002, pp. 707-720, 2002.
    • (2002) Computer Vision-ECCV 2002 , pp. 707-720
    • Brand, M.1
  • 6
    • 0025474239 scopus 로고
    • Tracking a few extreme singular values and vectors in signal processing
    • IEEE
    • Comon, P. and Golub, G. H. Tracking a few extreme singular values and vectors in signal processing. Proceedings of the IEEE, 78(8):1327-1343, 1990.
    • (1990) Proceedings of the , vol.78 , Issue.8 , pp. 1327-1343
    • Comon, P.1    Golub, G.H.2
  • 8
    • 79960425522 scopus 로고    scopus 로고
    • Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions
    • Halko, Nathan, Martinsson, Per-Gunnar, and Tropp, Joel A. Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions. SIAM review, 53(2):217-288, 2011.
    • (2011) SIAM Review , vol.53 , Issue.2 , pp. 217-288
    • Halko, N.1    Martinsson, P.-G.2    Tropp, J.A.3
  • 11
    • 0035641726 scopus 로고    scopus 로고
    • On the distribution of the largest eigenvalue in principal components analysis
    • Johnstone, IainM. On the distribution of the largest eigenvalue in principal components analysis.(english. Ann. Statist, 29(2):295-327, 2001.
    • (2001) English. Ann. Statist , vol.29 , Issue.2 , pp. 295-327
    • Johnstone, I.M.1
  • 12
    • 2442471723 scopus 로고    scopus 로고
    • On incremental and robust subspace learning
    • Li, Y. On incremental and robust subspace learning. Pattern recognition, 37(7):1509-1518, 2004.
    • (2004) Pattern Recognition , vol.37 , Issue.7 , pp. 1509-1518
    • Li, Y.1
  • 14
    • 62349121558 scopus 로고    scopus 로고
    • Finite sample approximation results for principal component analysis: A matrix perturbation approach
    • Nadler, Boaz. Finite sample approximation results for principal component analysis: a matrix perturbation approach. The Annals of Statistics, pp. 2791-2817, 2008.
    • (2008) The Annals of Statistics , pp. 2791-2817
    • Nadler, B.1
  • 20
    • 84898935950 scopus 로고    scopus 로고
    • How close is the sample covariance matrix to the actual covariance matrix?
    • Vershynin, R. How close is the sample covariance matrix to the actual covariance matrix? Journal of Theoretical Probability, pp. 1-32, 2010a.
    • (2010) Journal of Theoretical Probability , pp. 1-32
    • Vershynin, R.1
  • 22
    • 56349165656 scopus 로고    scopus 로고
    • Randomized online PCA algorithms with regret bounds that are logarithmic in the dimension
    • Warmuth, Manfred K. and Kuzmin, Dima. Randomized online PCA algorithms with regret bounds that are logarithmic in the dimension. Journal of Machine Learning Research, 9:2287-2320, 2008.
    • (2008) Journal of Machine Learning Research , vol.9 , pp. 2287-2320
    • Warmuth, M.K.1    Kuzmin, D.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.