Robust Estimation of Unbalanced Mixture Models on Samples with Outliers

@article{Galimzianova2015RobustEO,
  title={Robust Estimation of Unbalanced Mixture Models on Samples with Outliers},
  author={A. Galimzianova and F. Pernus and B. Likar and Ziga Spiclin},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2015},
  volume={37},
  pages={2273-2285}
}
  • A. Galimzianova, F. Pernus, +1 author Ziga Spiclin
  • Published 2015
  • Medicine, Mathematics, Computer Science
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Mixture models are often used to compactly represent samples from heterogeneous sources. However, in real world, the samples generally contain an unknown fraction of outliers and the sources generate different or unbalanced numbers of observations. Such unbalanced and contaminated samples may, for instance, be obtained by high density data sensors such as imaging devices. Estimation of unbalanced mixture models from samples with outliers requires robust estimation methods. In this paper, we… CONTINUE READING
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