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Volumn , Issue , 2010, Pages 630-649

Coresets and sketches for high dimensional subspace approximation problems

Author keywords

[No Author keywords available]

Indexed keywords

POLYNOMIAL APPROXIMATION;

EID: 77951676610     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1137/1.9781611973075.53     Document Type: Conference Paper
Times cited : (107)

References (26)
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    • M. Belkin and P. Niyogi, Semi-supervised learning on riemannian manifolds, Machine Learning Journal, 56, 2004.
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    • Matrix approximation and projective clustering via volume sampling
    • A. Deshpande, L. Rademacher, S. Vempala, and G. Wang, Matrix approximation and projective clustering via volume sampling, Theory of Computing, volume 2(12), pp. 225-247, 2006.
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    • Fast monte-carlo algorithms for finding low-rank approximations
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  • 15
    • 84867921047 scopus 로고    scopus 로고
    • How to get close to the median shape
    • S. Har-Peled, How to get close to the median shape, CGTA, 36(1), pp. 39-51, 2007.
    • (2007) CGTA , vol.36 , Issue.1 , pp. 39-51
    • Har-Peled, S.1
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    • 33746851190 scopus 로고    scopus 로고
    • Stable distributions, pseudorandom generators, embeddings, and data stream computation
    • P. Indyk, Stable distributions, pseudorandom generators, embeddings, and data stream computation, J. ACM, 53(3), pp. 307-323, 2006.
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    • 34547975563 scopus 로고    scopus 로고
    • Online kernel PCA with entropic matrix updates
    • DOI 10.1145/1273496.1273555, Proceedings, Twenty-Fourth International Conference on Machine Learning, ICML 2007
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.