39 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)

**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)

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

**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)

**A New Projected Quasi-Newton Approach for the Nonnegative Least Squares Problem**
(TR-06-54), Univ. of Texas, Austin, December 2006 (techreport)

**Probabilistic inference for solving (PO)MDPs**
(934), School of Informatics, University of Edinburgh, December 2006 (techreport)

**Minimal Logical Constraint Covering Sets**
(155), Max Planck Institute for Biological Cybernetics, Tübingen, December 2006 (techreport)

**Prediction of Protein Function from Networks**
In *Semi-Supervised Learning*, pages: 361-376, Adaptive Computation and Machine Learning, (Editors: Chapelle, O. , B. Schölkopf, A. Zien), MIT Press, Cambridge, MA, USA, November 2006 (inbook)

**Discrete Regularization**
In *Semi-supervised Learning*, pages: 237-250, Adaptive computation and machine learning, (Editors: O Chapelle and B Schölkopf and A Zien), MIT Press, Cambridge, MA, USA, November 2006 (inbook)

**New Methods for the P300 Visual Speller**
(1), (Editors: Hill, J. ), Max-Planck Institute for Biological Cybernetics, Tübingen, Germany, November 2006 (techreport)

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

**A tutorial on spectral clustering**
(149), Max Planck Institute for Biological Cybernetics, Tübingen, August 2006 (techreport)

**Towards the Inference of Graphs on Ordered Vertexes**
(150), Max Planck Institute for Biological Cybernetics, Tübingen, August 2006 (techreport)

**Nonnegative Matrix Approximation: Algorithms and Applications**
Univ. of Texas, Austin, May 2006 (techreport)

**An Automated Combination of Sequence Motif Kernels for Predicting Protein Subcellular Localization**
(146), Max Planck Institute for Biological Cybernetics, Tübingen, April 2006 (techreport)

**Training a Support Vector Machine in the Primal**
(147), Max Planck Institute for Biological Cybernetics, Tübingen, April 2006, The version in the "Large Scale Kernel Machines" book is more up to date. (techreport)

**Cross-Validation Optimization for Structured Hessian Kernel Methods**
Max-Planck Institute for Biological Cybernetics, Tübingen, Germany, February 2006 (techreport)

**Combining a Filter Method with SVMs**
In *Feature Extraction: Foundations and Applications, Studies in Fuzziness and Soft Computing, Vol. 207*, pages: 439-446, Studies in Fuzziness and Soft Computing ; 207, (Editors: I Guyon and M Nikravesh and S Gunn and LA Zadeh), Springer, Berlin, Germany, 2006 (inbook)

**Embedded methods**
In *Feature Extraction: Foundations and Applications*, pages: 137-165, Studies in Fuzziness and Soft Computing ; 207, (Editors: Guyon, I. , S. Gunn, M. Nikravesh, L. A. Zadeh), Springer, Berlin, Germany, 2006 (inbook)

**Implicit Wiener Series, Part II: Regularised estimation**
(148), Max Planck Institute, 2006 (techreport)

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

**Global Geometry of SVM Classifiers**
Max Planck Institute for Biological Cybernetics, Tübingen, Germany, June 2002 (techreport)

**Computationally Efficient Face Detection**
(MSR-TR-2002-69), Microsoft Research, June 2002 (techreport)

**Kernel-based nonlinear blind source separation**
EU-Project BLISS, January 2002 (techreport)

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

**Feature Selection and Transduction for Prediction of Molecular Bioactivity for Drug Design**
Max Planck Institute for Biological Cybernetics / Biowulf Technologies, 2002 (techreport)

**Observations on the Nyström Method for Gaussian Process Prediction**
Max Planck Institute for Biological Cybernetics, Tübingen, Germany, 2002 (techreport)

**Kernel principal component analysis.**
In *Advances in Kernel Methods—Support Vector Learning*, pages: 327-352, (Editors: B Schölkopf and CJC Burges and AJ Smola), MIT Press, Cambridge, MA, 1999 (inbook)

**Estimating the support of a high-dimensional distribution**
(MSR-TR-99-87), Microsoft Research, 1999 (techreport)

**Generalization Bounds via Eigenvalues of the Gram matrix**
(99-035), NeuroCOLT, 1999 (techreport)

**Sparse kernel feature analysis**
(99-04), Data Mining Institute, 1999, 24th Annual Conference of Gesellschaft f{\"u}r Klassifikation, University of Passau (techreport)

**Entropy numbers, operators and support vector kernels.**
In *Advances in Kernel Methods - Support Vector Learning*, pages: 127-144, (Editors: B Schölkopf and CJC Burges and AJ Smola), MIT Press, Cambridge, MA, 1999 (inbook)