@inproceedings{
    Peltonen07mlsp,
    editor = {Diamantaras, Konstantinos and Adali, T{\"u}lay and Pitas, Ioannis and Larsen, Jan and Papadimitriou, Theophilos and Douglas, Scott},
    author = "Peltonen, Jaakko and Goldberger, Jacob and Kaski, Samuel",
    publisher = "IEEE",
    title = "Fast Semi-supervised Discriminative Component Analysis",
    booktitle = "Machine Learning for Signal Processing XVII",
    abstract = "We introduce a method that learns a class-discriminative subspace or discriminative components of data. Such a subspace is useful for visualization, dimensionality reduction, feature extraction, and for learning a regularized distance metric. We learn the subspace by optimizing a probabilistic semiparametric model, a mixture of Gaussians, of classes in the subspace. The semiparametric modeling leads to fast computation (O(N) for N samples) in each iteration of optimization, in contrast to recent nonparametric methods that take O(N^2) time, but with equal accuracy. Moreover, we learn the subspace in a semi-supervised manner from three kinds of data: labeled and unlabeled samples, and unlabeled samples with pairwise constraints, with a unified objective. \par $\copyright$2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. \par This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. \par S. Kaski and J. Peltonen were supported by the Academy of Finland, decision numbers 108515 and 207467. This work was also supported in part by the IST Programme of the European Community, under the PASCAL Network of Excellence, IST-2002-506778. This publication only reflects the authors' views. All rights are reserved because of other commitments.",
    note = "Preprint pdf at \url{http://www.cis.hut.fi/projects/mi/papers/mlsp07.pdf}",
    flags = "AIRC copy",
    year = "2007",
    impactfactor = "D3",
    pages = "312--317"
}