Minimum Epsilon-Kernel Computation for Large-Scale Data Processing-Reference-Cited by-同舟云学术

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Minimum Epsilon-Kernel Computation for Large-Scale Data Processing

Published:2022-11-30 Issue:6 Volume:37 Page:1398-1411
ISSN:1000-9000
Container-title:Journal of Computer Science and Technology
language:en
Short-container-title:J. Comput. Sci. Technol.

Author:

Guo Hong-Jie,Li Jian-Zhong,Gao Hong

Publisher

Springer Science and Business Media LLC

Subject

Computational Theory and Mathematics,Computer Science Applications,Hardware and Architecture,Theoretical Computer Science,Software

Link

https://link.springer.com/content/pdf/10.1007/s11390-022-2429-6.pdf

Reference23 articles.

1. Agarwal P K, Har-Peled S, Varadarajan K R. Approximating extent measures of points. Journal of the ACM, 2004, 51(4): 606-635. https://doi.org/10.1145/1008731.1008736.

2. Wang Y, Li Y, Tan K L. Coresets for minimum enclosing balls over sliding windows. In Proc. the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Aug. 2019, pp.314-323. https://doi.org/10.1145/3292500.3330826.

3. Bachem O, Lucic M, Krause A. Scalable k-means clustering via lightweight coresets. In Proc. the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Aug. 2018, pp.1119-1127. https://doi.org/10.1145/3219819.3219973.

4. Har-Peled S, Mazumdar S. On coresets for k-means and k-median clustering. In Proc. the 36th Annual ACM Symposium on Theory of Computing, Jun. 2004, pp.291-300. https://doi.org/10.1145/1007352.1007400.

5. Yu A, Agarwal P K, Yang J. Processing a large number of continuous preference top-k queries. In Proc. the 2012 ACM SIGMOD International Conference on Management of Data, May 2012, pp.397-408. https://doi.org/10.1145/2213836.2213882.

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