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• W108686177 abstract "In this paper we provide a fully distributed implementation of the k-means clustering algorithm, intended for wireless sensor networks where each agent is endowed with a possibly high-dimensional observation (e.g., position, humidity, temperature, etc.) The proposed algorithm, by means of one-hop communication, partitions the agents into measure-dependent groups that have small in-group and large out-group distances. Since the partitions may not have a relation with the topology of the network--members of the same clusters may not be spatially close--the algorithm is provided with a mechanism to compute the clusters'centroids even when the clusters are disconnected in several sub-clusters.The results of the proposed distributed algorithm coincide, in terms of minimization of the objective function, with the centralized k-means algorithm. Some numerical examples illustrate the capabilities of the proposed solution." @default.
• W108686177 created "2016-06-24" @default.
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• W108686177 date "2013-12-15" @default.
• W108686177 modified "2023-09-27" @default.
• W108686177 title "Distributed k-means algorithm." @default.
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