Kernel Trick Embedded Gaussian Mixture Model

  title={Kernel Trick Embedded Gaussian Mixture Model},
  author={Jingdong Wang and Jianguo Lee and Changshui Zhang},
In this paper, we present a kernel trick embedded Gaussian Mixture Model (GMM), called kernel GMM. The basic idea is to embed kernel trick into EM algorithm and deduce a parameter estimation algorithm for GMM in feature space. Kernel GMM could be viewed as a Bayesian Kernel Method. Compared with most classical kernel methods, the proposed method can solve problems in probabilistic framework. Moreover, it can tackle nonlinear problems better than the traditional GMM. To avoid great computational… CONTINUE READING
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