Efficient Algorithm for the $k$-Means Problem with Must-Link and Cannot-Link Constraints-Reference-Cited by-同舟云学术

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Efficient Algorithm for the $k$-Means Problem with Must-Link and Cannot-Link Constraints

Published:2023-12 Issue:6 Volume:28 Page:1050-1062
ISSN:1007-0214
Container-title:Tsinghua Science and Technology
language:
Short-container-title:Tsinghua Sci. Technol.

Author:

Jia Chaoqi¹,Guo Longkun¹,Liao Kewen²,Lu Zhigang³

Affiliation:

1. Qilu University of Technology (Shandong Academy of Sciences),Faculty of Computer Science and Technology,Jinan,China,250353

2. Peter Faber Business School, Australian Catholic University,HilstLab,Sydney,Australia,2060

3. Macquarie University Cyber Security Hub, Macquarie University,Sydney,Australia,2109

Funder

National Natural Science Foundation of China

Publisher

Tsinghua University Press

Subject

Multidisciplinary

Link

http://xplorestaging.ieee.org/ielx7/5971803/10197185/10197186.pdf?arnumber=10197186

Reference26 articles.

1. Constrained $k$-means clustering with background knowledge;wagstaff;Proc 18th Int Conf Machine Learning,2001

2. Clustering with instance-level constraints;wagstaff;Proc 17th Int Conf Machine Learning,2000

3. Learning with Constrained and Unlabelled Data

4. Better Guarantees for k-Means and Euclidean k-Median by Primal-Dual Algorithms

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