Kernel Feature Spaces and Nonlinear Blind Souce Separation
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Motoaki Kawanabe | Andreas Ziehe | Klaus-Robert Müller | Stefan Harmeling | M. Kawanabe | K. Müller | A. Ziehe | S. Harmeling
[1] Gilles Burel,et al. Blind separation of sources: A nonlinear neural algorithm , 1992, Neural Networks.
[2] Antoine Souloumiac,et al. Jacobi Angles for Simultaneous Diagonalization , 1996, SIAM J. Matrix Anal. Appl..
[3] A. Hyvärinen,et al. Nonlinear Blind Source Separation by Self-Organizing Maps , 1996 .
[4] Eric Moulines,et al. A blind source separation technique using second-order statistics , 1997, IEEE Trans. Signal Process..
[5] Juha Karhunen,et al. A Maximum Likelihood Approach to Nonlinear Blind Source Separation , 1997, ICANN.
[6] Juan K. Lin,et al. Faithful Representation of Separable Distributions , 1997, Neural Computation.
[7] Te-Won Lee,et al. Blind source separation of nonlinear mixing models , 1997, Neural Networks for Signal Processing VII. Proceedings of the 1997 IEEE Signal Processing Society Workshop.
[8] Andreas Ziehe,et al. TDSEP { an e(cid:14)cient algorithm for blind separation using time structure , 1998 .
[9] Bernhard Schölkopf,et al. Nonlinear Component Analysis as a Kernel Eigenvalue Problem , 1998, Neural Computation.
[10] Jean-Francois Cardoso,et al. Blind signal separation: statistical principles , 1998, Proc. IEEE.
[11] J. C. BurgesChristopher. A Tutorial on Support Vector Machines for Pattern Recognition , 1998 .
[12] Andrzej Cichocki,et al. Information-theoretic approach to blind separation of sources in non-linear mixture , 1998, Signal Process..
[13] Gunnar Rätsch,et al. Input space versus feature space in kernel-based methods , 1999, IEEE Trans. Neural Networks.
[14] Christian Jutten,et al. Source separation in post-nonlinear mixtures , 1999, IEEE Trans. Signal Process..
[15] Nello Cristianini,et al. An introduction to Support Vector Machines , 2000 .
[16] Nello Cristianini,et al. An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .
[17] Pei Ling Lai,et al. Ica Using Kernel Canonical Correlation Analysis , 2000 .
[18] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[19] Juha Karhunen,et al. Nonlinear Independent Component Analysis Using Ensemble Learning: Experiments and Discussion , 2000 .
[20] Gunnar Rätsch,et al. An introduction to kernel-based learning algorithms , 2001, IEEE Trans. Neural Networks.
[21] Erkki Oja,et al. Independent Component Analysis , 2001 .