Differential Entropic Clustering of Multivariate Gaussians

  title={Differential Entropic Clustering of Multivariate Gaussians},
  author={Jason V. Davis and Inderjit S. Dhillon},
Gaussian data is pervasive and many learning algorithms (e.g., k-means) model their inputs as a single sample drawn from a multivariate Gaussian. However, in many real-life settings, each input object is best described by multiple samples drawn from a multivariate Gaussian. Such data can arise, for example, in a movie review database where each movie is rated by several users, or in time-series domains such as sensor networks. Here, each input can be naturally described by both a mean vector… CONTINUE READING
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