@INPROCEEDINGS{MikRaeWesSchSmoMue00,
    author = {Mika, S. and R{\"a}tsch, G. and Weston, J. and Sch{\"o}lkopf, B. and Smola, A.J. and M{\"u}ller, K.--R.},
    editor = {Solla, S.A. and Leen, T.K. and M{\"u}ller, K.-R.},
    title = "Invariant Feature Extraction and Classification in Kernel Spaces",
    booktitle = "Proc. NIPS 12",
    year = "2000",
    pages = "526--532",
    publisher = "MIT Press",
    abstract = "We incorporate prior knowledge to construct nonlinear algorithms for invariant feature extraction and discrimination. Employing a unified framework in terms of a nonlinear variant of the Rayleigh coefficient, we propose non-linear generalizations of Fisher's discriminant and oriented PCA using Support Vector kernel functions. Extensive simulations show the utility of our approach.",
    pdf = "http://doc.ml.tu-berlin.de/publications/publications/MikRaeWesSchSmoMue00.pdf",
    postscript = "http://doc.ml.tu-berlin.de/publications/publications/MikRaeWesSchSmoMue00.ps"
}