Efficient Greedy Learning of Gaussian Mixture Models

  title={Efficient Greedy Learning of Gaussian Mixture Models},
  author={Jakob J. Verbeek and Nikos A. Vlassis and Ben J. A. Kr{\"o}se},
  journal={Neural Computation},
This article concerns the greedy learning of gaussian mixtures. In the greedy approach, mixture components are inserted into the mixture one aftertheother.We propose a heuristic for searching for the optimal component to insert. In a randomized manner, a set of candidate new components is generated. For each of these candidates, we find the locally optimal new component and insert it into the existing mixture. The resulting algorithm resolves the sensitivity to initialization of state-of-the… CONTINUE READING
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