Distributed Consensus-Based <Emphasis Type="Italic">K</Emphasis>-Means Algorithm in Switching Multi-Agent Networks |
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Authors: | Peng Lin Yinghui Wang Hongsheng Qi Yiguang Hong |
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Institution: | 1.Key Laboratory of Systems and Control, Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing,China;2.School of Mathematical Sciences,University of Chinese Academy of Sciences,Beijing,China |
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Abstract: | This paper discusses a distributed design for clustering based on the K-means algorithm in a switching multi-agent network, for the case when data are decentralized stored and unavailable to all agents. The authors propose a consensus-based algorithm in distributed case, that is, the double-clock consensus-based K-means algorithm (DCKA). With mild connectivity conditions, the authors show convergence of DCKA to guarantee a distributed solution to the clustering problem, even though the network topology is time-varying. Moreover, the authors provide experimental results on various clustering datasets to illustrate the effectiveness of the fully distributed algorithm DCKA, whose performance may be better than that of the centralized K-means algorithm. |
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