@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.",
    note = "Preprint pdf at \url{http://www.cis.hut.fi/projects/mi/papers/mlsp07.pdf}",
    flags = "AIRC HIIT public",
    year = "2007",
    impactfactor = "D3",
    pages = "312-317"
}