An LP-based k-means algorithm for balancing weighted point sets-Reference-Cited by-同舟云学术

An LP-based k-means algorithm for balancing weighted point sets

Published:2017-12 Issue:2 Volume:263 Page:349-355
ISSN:0377-2217
Container-title:European Journal of Operational Research
language:en
Short-container-title:European Journal of Operational Research

Author:

Borgwardt S.,Brieden A.,Gritzmann P.

Publisher

Elsevier BV

Subject

Information Systems and Management,Management Science and Operations Research,Modeling and Simulation,General Computer Science,Industrial and Manufacturing Engineering

Reference37 articles.

1. NP-hardness of Euclidean sum-of-squares clustering;Aloise;Machine Learning,2009

2. Tools from higher algebra;Alon,1995

3. Generalized balanced power diagrams for 3D representations of polycrystals;Alpers;Philosophical Magazine,2015

4. k-Means has polynomial smoothed complexity;Arthur,2009

5. Smoothed analysis of the k-means method;Arthur;Journal of the Association for Computing Machinery,2010

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