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Fast support-based clustering method for large-scale problems
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DOI：10.1016/j.patcog.2009.12.010.png)
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摘要
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In many support vector-based clustering algorithms, a key computational bottleneck is the cluster labeling time of each data point which restricts the scalability of the method In this paper, we review a general framework of support vector-based clustering using dynamical system and propose a novel method to speed up labeling time which is log-linear to the size of data. We also give theoretical background of the proposed method Various large-scale benchmark results are provided to show the effectiveness and efficiency of the proposed method. (C) 2009 Elsevier Ltd. All rights reserved
Keyword:
Large-scale problem
Kernel methods
Support vector clustering
Cluster labeling
Dynamical system
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期刊
IF:
7.6
论文数:
1.4W
被引数:
5.0W
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