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pro vyhledávání: '"Annakula, ChandraVyas"'
Autor:
Annakula, Chandravyas
Master of Science
Department of Computing and Information Sciences
William H. Hsu
(Higgins, Savje, & Sekhon, 2016) Provides us with a sampling blocking algorithm that enables large and complex experiments to run in polynomial time with
Department of Computing and Information Sciences
William H. Hsu
(Higgins, Savje, & Sekhon, 2016) Provides us with a sampling blocking algorithm that enables large and complex experiments to run in polynomial time with
Externí odkaz:
http://hdl.handle.net/2097/35468
Autor:
Luo, Jianmei, Annakula, ChandraVyas, Kannamareddy, Aruna Sai, Sekhon, Jasjeet S., Hsu, William Henry, Higgins, Michael
As the size $n$ of datasets become massive, many commonly-used clustering algorithms (for example, $k$-means or hierarchical agglomerative clustering (HAC) require prohibitive computational cost and memory. In this paper, we propose a solution to the
Externí odkaz:
http://arxiv.org/abs/1907.02907