Turning Big Data Into Tiny Data: Constant-Size Coresets for $k$-Means, PCA, and Projective Clustering-Reference-Cited by-同舟云学术

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Turning Big Data Into Tiny Data: Constant-Size Coresets for $k$-Means, PCA, and Projective Clustering

Published:2020-01 Issue:3 Volume:49 Page:601-657
ISSN:0097-5397
Container-title:SIAM Journal on Computing
language:en
Short-container-title:SIAM J. Comput.

Author:

Feldman Dan,Schmidt Melanie,Sohler Christian

Funder

Deutsche Forschungsgemeinschaft

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Subject

General Mathematics,General Computer Science

Link

https://epubs.siam.org/doi/pdf/10.1137/18M1209854

Reference39 articles.

1. NP-hardness of Euclidean sum-of-squares clustering

2. Approximating extent measures of points

3. Approximating extent measures of points

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