Learning $k$-Modal Distributions via Testing

@article{Daskalakis2012LearningD,
  title={Learning \$k\$-Modal Distributions via Testing},
  author={Constantinos Daskalakis and Ilias Diakonikolas and Rocco A. Servedio},
  journal={Theory of Computing},
  year={2012},
  volume={10},
  pages={535-570}
}
A k-modal probability distribution over the domain {1, ..., n} is one whose histogram has at most k “peaks” and “valleys.” Such distributions are natural generalizations of monotone (k = 0) and unimodal (k = 1) probability distributions, which have been intensively studied in probability theory and statistics. In this paper we consider the problem of learning an unknown k-modal distribution. The learning algorithm is given access to independent samples drawn from the k-modal distribution p, and… CONTINUE READING
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