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Volumn , Issue , 2011, Pages

Fast and accurate κ-means for large datasets

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATION THEORY; NEAREST NEIGHBOR SEARCH;

EID: 85162439676     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (124)

References (29)
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    • Alexandr Andoni and Piotr Indyk. Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions. Communications of the ACM, January 2008.
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    • David Arthur and Sergei Vassilvitskii. k-means++: The Advantages of Careful Seeding. In SODA, 2007.
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    • Arthur, D.1    Vassilvitskii, S.2
  • 8
    • 0034819501 scopus 로고    scopus 로고
    • Local search heuristic for κ-median and facility location problems
    • Vijay Arya, Naveen Garg, Rohit Khandekar, Adam Meyerson, Kamesh Munagala, and Vinayaka Pandit. Local search heuristic for k-median and facility location problems. In STOC, 2001.
    • (2001) STOC
    • Arya, V.1    Garg, N.2    Khandekar, R.3    Meyerson, A.4    Munagala, K.5    Pandit, V.6
  • 10
    • 0036036832 scopus 로고    scopus 로고
    • Approximate clustering via core-sets
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    • Badoiu, M.1    Har-Peled, S.2    Indyk, P.3
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    • Better streaming algorithms for clustering problems
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    • Charikar, M.1    O'Callaghan, L.2    Panigrahy, R.3
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    • On coresets for κ-median and k-means clustering in metric and euclidean spaces and their applications
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    • Chen, K.1
  • 13
    • 35348830377 scopus 로고    scopus 로고
    • A PTAS for k-means clustering based on weak coresets
    • Dan Feldman, Morteza Monemizadeh, and Christian Sohler. A PTAS for k-means clustering based on weak coresets. In SCG, 2007.
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    • Har-Peled, S.1    Mazumdar, S.2
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    • June
    • Andrea vattani. k-means requires exponentially many iterations even in the plane. Disc ete Computational Geometry, June 2011.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.