An Effective and Efficient Algorithm for K-Means Clustering With New Formulation-Reference-Cited by-同舟云学术

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An Effective and Efficient Algorithm for K-Means Clustering With New Formulation

Published:2023-04-01 Issue:4 Volume:35 Page:3433-3443
ISSN:1041-4347
Container-title:IEEE Transactions on Knowledge and Data Engineering
language:
Short-container-title:IEEE Trans. Knowl. Data Eng.

Author:

Nie Feiping¹^ORCID,Li Ziheng¹^ORCID,Wang Rong¹^ORCID,Li Xuelong¹

Affiliation:

1. School of Computer Science, School of Artificial Intelligence, Optics and Electronics (iOPEN), and the Key Laboratory of Intelligent Interaction and Applications (Ministry of Industry and Information Technology), Northwestern Polytechnical University, Xi'an, Shaanxi, China

Funder

National Key Research and Development Program of China

Natural Science Basic Research Program of Shaanxi

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Computer Science Applications,Information Systems

Link

http://xplorestaging.ieee.org/ielx7/69/10063074/09723527.pdf?arnumber=9723527

Reference44 articles.

1. Least squares quantization in PCM

2. Compressed K-Means for Large-Scale Clustering

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

4. Unsupervised feature selection for multi-cluster data

5. A comparative study of efficient initialization methods for the k-means clustering algorithm

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