Clustering Needles in a Haystack: An Information Theoretic Analysis of Minority and Outlier Detection

@article{Ando2007ClusteringNI,
  title={Clustering Needles in a Haystack: An Information Theoretic Analysis of Minority and Outlier Detection},
  author={Shin Ando},
  journal={Seventh IEEE International Conference on Data Mining (ICDM 2007)},
  year={2007},
  pages={13-22}
}
Identifying atypical objects is one of the traditional topics in machine learning. Recently, novel approaches, e.g., Minority Detection and One-class clustering, have explored further to identify clusters of atypical objects which strongly contrast from the rest of the data in terms of their distribution or density. This paper analyzes such tasks from an information theoretic perspective. Based on Information Bottleneck formalization, these tasks interpret to increasing the averaged… CONTINUE READING
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