International Conference on Web-Age Information Management

WAIM 2015: Web-Age Information Management pp 413-425 | Cite as

Fast Multiway Maximum Margin Clustering Based on Genetic Algorithm via the NystrÖm Method

  • Ying Kang
  • Dong Zhang
  • Bo Yu
  • Xiaoyan Gu
  • Weiping Wang
  • Dan Meng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9098)

Abstract

Motivated by theories of support vector machine, the concept of maximum margin has been extended to the applications in the unsupervised scenario, developing a novel clustering methodmaximum margin clustering (MMC). MMC shows an outstanding performance in computational accuracy, which is superior to other traditional clustering methods. But the integer programming of labels of data instances induces MMC to be a hard non-convex optimization problem to settle. Currently, many techniques like semi-definite programming, cutting plane etc. are embedded in MMC to tackle this problem. However, the increasing time complexity and premature convergence of these methods limit the analytic capability of MMC for large datasets. This paper proposes a fast multiway maximum margin clustering method based on genetic algorithm (GAM3C). GAM3C initially adopts the NystrÖm method to generate a low-rank approximate kernel matrix in the dual form of MMC, reducing the scale of original problem and speeding up the subsequent analyzing process; and then makes use of the solution-space alternation of genetic algorithm to compute the non-convex optimization of MMC explicitly, obtaining the multiway clustering results simultaneously. Experimental results on real world datasets reflect that GAM3C outperforms the state-of-the-art maximum margin clustering algorithms in terms of computational accuracy and running time.

Keywords

Maximum margin clustering NystrÖm method Genetic algorithm 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Ying Kang
    • 1
    • 2
  • Dong Zhang
    • 3
    • 4
  • Bo Yu
    • 1
  • Xiaoyan Gu
    • 1
  • Weiping Wang
    • 1
  • Dan Meng
    • 1
  1. 1.Institute of Information EngineeringChinese Academy of SciencesBeijingChina
  2. 2.University of Chinese Academy of SciencesBeijingChina
  3. 3.State Key Laboratory of High-end Server and Storage TechnologyJinanChina
  4. 4.Inspur Group Corporation Ltd.JinanChina

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