43 results
(View BibTeX file of all listed publications)

**Projected Newton-type methods in machine learning**
In *Optimization for Machine Learning*, pages: 305-330, (Editors: Sra, S., Nowozin, S. and Wright, S. J.), MIT Press, Cambridge, MA, USA, December 2011 (inbook)

**JMLR Workshop and Conference Proceedings Volume 19: COLT 2011**
pages: 834, MIT Press, Cambridge, MA, USA, 24th Annual Conference on Learning Theory , June 2011 (proceedings)

**Statistical Learning Theory: Models, Concepts, and Results**
In *Handbook of the History of Logic, Vol. 10: Inductive Logic*, 10, pages: 651-706, (Editors: Gabbay, D. M., Hartmann, S. and Woods, J. H.), Elsevier North Holland, Amsterdam, Netherlands, May 2011 (inbook)

**PAC-Bayesian Analysis of Martingales and Multiarmed Bandits **
Max Planck Institute for Biological Cybernetics, Tübingen, Germany, May 2011 (techreport)

**Non-stationary Correction of Optical Aberrations**
(1), Max Planck Institute for Intelligent Systems, Tübingen, Germany, May 2011 (techreport)

**Multiple Kernel Learning: A Unifying Probabilistic Viewpoint**
Max Planck Institute for Biological Cybernetics, March 2011 (techreport)

**Robot Learning**
In *Encyclopedia of Machine Learning*, pages: 865-869, Encyclopedia of machine learning, (Editors: Sammut, C. and Webb, G. I.), Springer, New York, NY, USA, January 2011 (inbook)

**Multiple testing, uncertainty and realistic pictures**
(2011-004), EURANDOM, Technische Universiteit Eindhoven, January 2011 (techreport)

**What You Expect Is What You Get? Potential Use of Contingent Negative Variation for Passive BCI Systems in Gaze-Based HCI**
In *Affective Computing and Intelligent Interaction*, 6975, pages: 447-456, Lecture Notes in Computer Science, (Editors: D’Mello, S., Graesser, A., Schuller, B. and Martin, J.-C.), Springer, Berlin, Germany, 2011 (inbook)

**Kernel Methods in Bioinformatics **
In *Handbook of Statistical Bioinformatics*, pages: 317-334, Springer Handbooks of Computational Statistics ; 3, (Editors: Lu, H.H.-S., Schölkopf, B. and Zhao, H.), Springer, Berlin, Germany, 2011 (inbook)

**Cue Combination: Beyond Optimality**
In *Sensory Cue Integration*, pages: 144-152, (Editors: Trommershäuser, J., Körding, K. and Landy, M. S.), Oxford University Press, 2011 (inbook)

**Nonconvex proximal splitting: batch and incremental algorithms**
(2), Max Planck Institute for Intelligent Systems, Tübingen, Germany, 2011 (techreport)

**Learning an Interactive Segmentation System**
Max Planck Institute for Biological Cybernetics, December 2009 (techreport)

**An Incremental GEM Framework for Multiframe Blind Deconvolution, Super-Resolution, and Saturation Correction**
(187), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, November 2009 (techreport)

**Efficient Filter Flow for Space-Variant Multiframe Blind Deconvolution**
(188), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, November 2009 (techreport)

**Consistent Nonparametric Tests of Independence**
(172), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, July 2009 (techreport)

**Text Clustering with Mixture of von Mises-Fisher Distributions**
In *Text mining: classification, clustering, and applications*, pages: 121-161, Chapman & Hall/CRC data mining and knowledge discovery series, (Editors: Srivastava, A. N. and Sahami, M.), CRC Press, Boca Raton, FL, USA, June 2009 (inbook)

**Semi-supervised subspace analysis of human functional magnetic resonance imaging data**
(185), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, May 2009 (techreport)

**Data Mining for Biologists**
In *Biological Data Mining in Protein Interaction Networks*, pages: 14-27, (Editors: Li, X. and Ng, S.-K.), Medical Information Science Reference, Hershey, PA, USA, May 2009 (inbook)

**Large Margin Methods for Part of Speech Tagging**
In *Automatic Speech and Speaker Recognition: Large Margin and Kernel Methods*, pages: 141-160, (Editors: Keshet, J. and Bengio, S.), Wiley, Hoboken, NJ, USA, January 2009 (inbook)

**Covariate shift and local learning by distribution matching**
In *Dataset Shift in Machine Learning*, pages: 131-160, (Editors: Quiñonero-Candela, J., Sugiyama, M., Schwaighofer, A. and Lawrence, N. D.), MIT Press, Cambridge, MA, USA, 2009 (inbook)

**Support Vector Channel Selection in BCI**
(120), Max Planck Institute for Biological Cybernetics, Tuebingen, Germany, December 2003 (techreport)

**Learning Theory and Kernel Machines: 16th Annual Conference on Learning Theory and 7th Kernel Workshop (COLT/Kernel 2003), LNCS Vol. 2777**
*Proceedings of the 16th Annual Conference on Learning Theory and 7th Kernel Workshop (COLT/Kernel 2003)*, *COLT/Kernel 2003*, pages: 746, Springer, Berlin, Germany, 16th Annual Conference on Learning Theory and 7th Kernel Workshop, November 2003, Lecture Notes in Computer Science ; 2777 (proceedings)

**Image Reconstruction by Linear Programming**
(118), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, October 2003 (techreport)

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

**Kernel Hebbian Algorithm for Iterative Kernel Principal Component Analysis**
(109), MPI f. biologische Kybernetik, Tuebingen, June 2003 (techreport)

**Learning with Local and Global Consistency**
(112), Max Planck Institute for Biological Cybernetics, Tuebingen, Germany, June 2003 (techreport)

**Implicit Wiener Series**
(114), Max Planck Institute for Biological Cybernetics, June 2003 (techreport)

**Machine Learning approaches to protein ranking: discriminative, semi-supervised, scalable algorithms**
(111), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, June 2003 (techreport)

**The Geometry Of Kernel Canonical Correlation Analysis**
(108), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, May 2003 (techreport)

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

**A Note on Parameter Tuning for On-Line Shifting Algorithms**
Max Planck Institute for Biological Cybernetics, Tübingen, Germany, 2003 (techreport)

**Extension of the nu-SVM range for classification**
In *Advances in Learning Theory: Methods, Models and Applications, NATO Science Series III: Computer and Systems Sciences, Vol. 190*, 190, pages: 179-196, NATO Science Series III: Computer and Systems Sciences, (Editors: J Suykens and G Horvath and S Basu and C Micchelli and J Vandewalle), IOS Press, Amsterdam, 2003 (inbook)

**An Introduction to Support Vector Machines**
In *Recent Advances and Trends in Nonparametric Statistics
*, pages: 3-17, (Editors: MG Akritas and DN Politis), Elsevier, Amsterdam, The Netherlands, 2003 (inbook)

**Statistical Learning and Kernel Methods in Bioinformatics**
In *Artificial Intelligence and Heuristic Methods in Bioinformatics*, 183, pages: 1-21, 3, (Editors: P Frasconi und R Shamir), IOS Press, Amsterdam, The Netherlands, 2003 (inbook)

**Interactive Images**
(MSR-TR-2003-64), Microsoft Research, Cambridge, UK, 2003 (techreport)

**A Short Introduction to Learning with Kernels**
In *Proceedings of the Machine Learning Summer School, Lecture Notes in Artificial Intelligence, Vol. 2600*, pages: 41-64, LNAI 2600, (Editors: S Mendelson and AJ Smola), Springer, Berlin, Heidelberg, Germany, 2003 (inbook)

**Bayesian Kernel Methods**
In *Advanced Lectures on Machine Learning, Machine Learning Summer School 2002, Lecture Notes in Computer Science, Vol. 2600*, LNAI 2600, pages: 65-117, 0, (Editors: S Mendelson and AJ Smola), Springer, Berlin, Germany, 2003 (inbook)

**Stability of ensembles of kernel machines**
In 190, pages: 111-124, NATO Science Series III: Computer and Systems Science, (Editors: Suykens, J., G. Horvath, S. Basu, C. Micchelli and J. Vandewalle), IOS press, Netherlands, 2003 (inbook)

**Kernel Dependency Estimation**
(98), Max Planck Institute for Biological Cybernetics, August 2002 (techreport)

**A compression approach to support vector model selection**
(101), Max Planck Institute for Biological Cybernetics, 2002, see more detailed JMLR version (techreport)

**Inference Principles and Model Selection**
(01301), Dagstuhl Seminar, 2001 (techreport)

**An Introduction to Kernel-Based Learning Algorithms**
In *Handbook of Neural Network Signal Processing*, 4, (Editors: Yu Hen Hu and Jang-Neng Hwang), CRC Press, 2000 (inbook)