95 results
(BibTeX)

**A Kernel Statistical Test of Independence**
In *Advances in neural information processing systems 20*, pages: 585-592, (Editors: JC Platt and D Koller and Y Singer and S Roweis), Curran, Red Hook, NY, USA, 21st Annual Conference on Neural Information Processing Systems (NIPS), September 2008 (inproceedings)

**Taxonomy Inference Using Kernel Dependence
Measures**
(181), Max-Planck Institute for Biological Cybernetics, Tübingen, Germany, November 2008 (techreport)

**Analysis of Pattern Recognition Methods in Classifying Bold Signals in Monkeys at 7-Tesla**
*AREADNE 2008: Research in Encoding and Decoding of Neural Ensembles*, 2, pages: 67, June 2008 (poster)

**Nonparametric Indepedence Tests: Space Partitioning and Kernel Approaches**
19th International Conference on Algorithmic Learning Theory (ALT08), October 2008 (talk)

**Supervised Feature Selection via Dependence Estimation**
In *Proceedings of the 24th Annual International Conference on Machine Learning (ICML 2007)*, pages: 823-830, (Editors: Ghahramani, Z. ), ACM Press, New York, NY, USA, Twenty-Fourth Annual International Conference on Machine Learning (ICML), June 2007 (inproceedings)

**Brisk Kernel ICA**
In *Large Scale Kernel Machines*, pages: 225-250, Neural Information Processing, (Editors: Bottou, L. , O. Chapelle, D. DeCoste, J. Weston), MIT Press, Cambridge, MA, USA, September 2007 (inbook)

**Hilbert Space Representations of Probability Distributions**
2nd Workshop on Machine Learning and Optimization at the ISM, October 2007 (talk)

**A Kernel Method for the Two-Sample-Problem**
In *Advances in Neural Information Processing Systems 19*, pages: 513-520, (Editors: B Schölkopf and J Platt and T Hofmann), MIT Press, Cambridge, MA, USA, 20th Annual Conference on Neural Information Processing Systems (NIPS), September 2007 (inproceedings)

**A Kernel Approach to Comparing Distributions**
In *Proceedings of the 22. AAAI Conference on Artificial Intelligence*, pages: 1637-1641, AAAI Press, Menlo Park, CA, USA, Twenty-Second AAAI Conference on Artificial Intelligence (AAAI), July 2007 (inproceedings)

**Fast Kernel ICA using an Approximate Newton Method**
In *JMLR Workshop and Conference Proceedings Volume 2: AISTATS 2007*, pages: 476-483, (Editors: Meila, M. , X. Shen), MIT Press, Cambridge, MA, USA, 11th International Conference on Artificial Intelligence and Statistics, March 2007 (inproceedings)

**A Hilbert Space Embedding for Distributions**
*Proceedings of the 10th International Conference on Discovery Science (DS 2007)*, 10, pages: 40-41, October 2007 (poster)

**Gene selection via the BAHSIC family of algorithms**
*Bioinformatics*, 23(13: ISMB/ECCB 2007 Conference Proceedings):i490-i498, July 2007 (article)

**A Hilbert Space Embedding for Distributions**
In *Algorithmic Learning Theory, Lecture Notes in Computer Science 4754 *, pages: 13-31, (Editors: M Hutter and RA Servedio and E Takimoto), Springer, Berlin, Germany, 18th International Conference on Algorithmic Learning Theory (ALT), October 2007 (inproceedings)

**A time/frequency decomposition of information transmission by LFPs and spikes in the primary visual cortex**
*37th Annual Meeting of the Society for Neuroscience (Neuroscience 2007)*, 37, pages: 1, November 2007 (poster)

**Statistical Consistency of Kernel Canonical Correlation Analysis**
*Journal of Machine Learning Research*, 8, pages: 361-383, February 2007 (article)

**Correcting Sample Selection Bias by Unlabeled Data**
In *Advances in Neural Information Processing Systems 19*, pages: 601-608, (Editors: B Schölkopf and J Platt and T Hofmann), MIT Press, Cambridge, MA, USA, 20th Annual Conference on Neural Information Processing Systems (NIPS), September 2007 (inproceedings)

**A Dependence Maximization View of Clustering**
In *Proceedings of the 24th Annual International Conference on Machine Learning (ICML 2007)*, pages: 815-822, (Editors: Ghahramani, Z. ), ACM Press, New York, NY, USA, Twenty-Fourth Annual International Conference on Machine Learning (ICML), June 2007 (inproceedings)

**An Online Support Vector Machine for Abnormal Events Detection**
*Signal Processing*, 86(8):2009-2025, August 2006 (article)

**Statistical Convergence of Kernel CCA**
In *Advances in neural information processing systems 18*, pages: 387-394, (Editors: Weiss, Y. , B. Schölkopf, J. Platt), MIT Press, Cambridge, MA, USA, Nineteenth Annual Conference on Neural Information Processing Systems (NIPS), May 2006 (inproceedings)

**A Kernel Method for the Two-Sample-Problem**
20th Annual Conference on Neural Information Processing Systems (NIPS), December 2006 (talk)

**The Effect of Artifacts on Dependence Measurement in fMRI**
*Magnetic Resonance Imaging*, 24(4):401-409, April 2006 (article)

**Integrating Structured Biological data by Kernel Maximum Mean Discrepancy**
*Bioinformatics*, 22(4: ISMB 2006 Conference Proceedings):e49-e57, August 2006 (article)

**Geometric Analysis of Hilbert Schmidt Independence criterion based ICA contrast function**
(PA006080), National ICT Australia, Canberra, Australia, October 2006 (techreport)

**Kernel Methods for Measuring Independence**
*Journal of Machine Learning Research*, 6, pages: 2075-2129, December 2005 (article)

**Kernel ICA for Large Scale Problems**
In pages: -, NIPS Workshop on Large Scale Kernel Machines, December 2005 (inproceedings)

**Measuring Statistical Dependence with Hilbert-Schmidt Norms**
(140), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, June 2005 (techreport)

**Measuring Statistical Dependence with Hilbert-Schmidt Norms**
In *Algorithmic Learning Theory, Lecture Notes in Computer Science, Vol. 3734*, pages: 63-78, (Editors: S Jain and H-U Simon and E Tomita), Springer, Berlin, Germany, 16th International Conference ALT, October 2005 (inproceedings)

**Consistency of Kernel Canonical Correlation Analysis**
(942), Institute of Statistical Mathematics, 4-6-7 Minami-azabu, Minato-ku, Tokyo 106-8569 Japan, June 2005 (techreport)

**Kernel Constrained Covariance for Dependence Measurement**
In *Proceedings of the 10th International Workshop on Artificial Intelligence and Statistics*, pages: 112-119, (Editors: R Cowell, R and Z Ghahramani), AISTATS, January 2005 (inproceedings)

**Kernel Constrained Covariance for Dependence Measurement**
AISTATS, January 2005 (talk)

**Kernel methods for dependence testing in LFP-MUA**
35(689.17), 35th Annual Meeting of the Society for Neuroscience (Neuroscience), November 2005 (poster)

**Multivariate Regression with Stiefel Constraints**
(128), MPI for Biological Cybernetics, Spemannstr 38, 72076, Tuebingen, 2004 (techreport)

**Multivariate Regression via Stiefel Manifold Constraints**
In *Lecture Notes in Computer Science, Vol. 3175*, pages: 262-269, (Editors: CE Rasmussen and HH Bülthoff and B Schölkopf and MA Giese), Springer, Berlin, Germany, Pattern Recognition, Proceedings of the 26th DAGM Symposium, 2004 (inproceedings)

**Ranking on Data Manifolds**
In *Advances in neural information processing systems 16*, pages: 169-176, (Editors: S Thrun and L Saul and B Schölkopf), MIT Press, Cambridge, MA, USA, 17th Annual Conference on Neural Information Processing Systems (NIPS), June 2004 (inproceedings)

**Behaviour and Convergence of the Constrained Covariance**
(130), MPI for Biological Cybernetics, 2004 (techreport)

**Ranking on Data Manifolds**
(113), Max Planck Institute for Biological Cybernetics, 72076 Tuebingen, Germany, June 2003 (techreport)

**Kernel Methods for Classification and Signal Separation**
pages: 226, Biologische Kybernetik, University of Cambridge, Cambridge, April 2003 (phdthesis)

**On-Line One-Class Support Vector Machines. An Application to Signal Segmentation**
In *IEEE ICASSP Vol. 2*, pages: 709-712, IEEE ICASSP, April 2003 (inproceedings)

**The Kernel Mutual Information**
Max Planck Institute for Biological Cybernetics, April 2003 (techreport)

**The Kernel Mutual Information**
In *IEEE ICASSP Vol. 4*, pages: 880-883, IEEE ICASSP, April 2003 (inproceedings)

**Optimized Support Vector Machines for Nonstationary Signal Classification**
*IEEE Signal Processing Letters*, 9(12):442-445, December 2002 (article)

**Nonstationary Signal Classification using Support Vector Machines**
In *11th IEEE Workshop on Statistical Signal Processing*, pages: 305-305, 11th IEEE Workshop on Statistical Signal Processing, 2001 (inproceedings)

**Bound on the Leave-One-Out Error for Density Support Estimation using nu-SVMs**
University of Cambridge, 2001 (techreport)

**Support Vector Regression for Black-Box System Identification**
In *11th IEEE Workshop on Statistical Signal Processing*, pages: 341-344, IEEE Signal Processing Society, Piscataway, NY, USA, 11th IEEE Workshop on Statistical Signal Processing, 2001 (inproceedings)

**Bound on the Leave-One-Out Error for 2-Class Classification using nu-SVMs**
University of Cambridge, 2001, Updated May 2003 (literature review expanded) (techreport)