Robust probabilistic projections

@article{Archambeau2006RobustPP,
  title={Robust probabilistic projections},
  author={C. Archambeau and N. Delannay and M. Verleysen},
  journal={Proceedings of the 23rd international conference on Machine learning},
  year={2006}
}
Principal components and canonical correlations are at the root of many exploratory data mining techniques and provide standard pre-processing tools in machine learning. Lately, probabilistic reformulations of these methods have been proposed (Roweis, 1998; Tipping & Bishop, 1999b; Bach & Jordan, 2005). They are based on a Gaussian density model and are therefore, like their non-probabilistic counterpart, very sensitive to atypical observations. In this paper, we introduce robust probabilistic… Expand
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