39 results
(View BibTeX file of all listed publications)

**Camera-specific Image Denoising**
Eberhard Karls Universität Tübingen, Germany, October 2013 (diplomathesis)

**A Review of Performance Variations in SMR-Based Brain–Computer Interfaces (BCIs)**
In *Brain-Computer Interface Research*, pages: 39-51, 4, SpringerBriefs in Electrical and Computer Engineering, (Editors: Guger, C., Allison, B. Z. and Edlinger, G.), Springer, 2013 (inbook)

**Semi-supervised learning in causal and anticausal settings**
In *Empirical Inference*, pages: 129-141, 13, Festschrift in Honor of Vladimir Vapnik, (Editors: Schölkopf, B., Luo, Z. and Vovk, V.), Springer, 2013 (inbook)

**Tractable large-scale optimization in machine learning**
In *Tractability: Practical Approaches to Hard Problems*, pages: 202-230, 7, (Editors: Bordeaux, L., Hamadi , Y., Kohli, P. and Mateescu, R. ), Cambridge University Press , 2013 (inbook)

**Modelling and Learning Approaches to Image Denoising**
Eberhard Karls Universität Tübingen, Germany, 2013 (phdthesis)

**Animating Samples from Gaussian Distributions**
(8), Max Planck Institute for Intelligent Systems, Tübingen, Germany, 2013 (techreport)

**Proceedings of the 10th European Workshop on Reinforcement Learning, Volume 24 **
pages: 173, JMLR, European Workshop On Reinforcement Learning, EWRL, 2013 (proceedings)

**Linear mixed models for genome-wide association studies**
University of Tübingen, Germany, 2013 (phdthesis)

**Maximizing Kepler science return per telemetered pixel: Detailed models of the focal plane in the two-wheel era**
*arXiv:1309.0653*, 2013 (techreport)

**Maximizing Kepler science return per telemetered pixel: Searching the habitable zones of the brightest stars**
*arXiv:1309.0654*, 2013 (techreport)

**On the Relations and Differences between Popper Dimension, Exclusion Dimension and VC-Dimension**
In *Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik*, pages: 53-57, 6, (Editors: Schölkopf, B., Luo, Z. and Vovk, V.), Springer, 2013 (inbook)

**Modeling and Learning Complex Motor Tasks: A case study on Robot Table Tennis**
Technical University Darmstadt, Germany, 2013 (phdthesis)

**Intention Inference and Decision Making with Hierarchical Gaussian Process Dynamics Models**
Technical University Darmstadt, Germany, 2013 (phdthesis)

**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)

**Crowdsourcing for optimisation of deconvolution methods via an iPhone application**
Hochschule Reutlingen, Germany, April 2011 (mastersthesis)

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

**Learning functions with kernel methods**
University of Pavia, Italy, January 2011 (phdthesis)

**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)

**Model Learning in Robot Control**
Albert-Ludwigs-Universität Freiburg, Germany, 2011 (phdthesis)

**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)

**Nonlinear Multivariate Analysis with Geodesic Kernels**
Biologische Kybernetik, Technische Universität Berlin, February 2002 (diplomathesis)

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

**Concentration Inequalities and Empirical Processes Theory Applied to the Analysis of Learning Algorithms**
Biologische Kybernetik, Ecole Polytechnique, 2002 (phdthesis) Accepted

**Support Vector Machines: Induction Principle, Adaptive Tuning and Prior Knowledge**
Biologische Kybernetik, 2002 (phdthesis)

**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)

**A New Method for Constructing Artificial Neural Networks**
AT & T Bell Laboratories, 1995 (techreport)