32 results
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**Maschinelles Lernen: Entwicklung ohne Grenzen?**
In *Mit Optimismus in die Zukunft schauen. Künstliche Intelligenz - Chancen und Rahmenbedingungen*, pages: 26-34, (Editors: Bender, G. and Herbrich, R. and Siebenhaar, K.), B&S Siebenhaar Verlag, 2018 (incollection)

**Methods in Psychophysics**
In *Stevens’ Handbook of Experimental Psychology and Cognitive Neuroscience*, 5 (Methodology), 7, 4th, John Wiley & Sons, Inc., 2018 (inbook)

**Transfer Learning for BCIs**
In *Brain–Computer Interfaces Handbook*, pages: 425-442, 22, (Editors: Chang S. Nam, Anton Nijholt and Fabien Lotte), CRC Press, 2018 (incollection)

**Method and device for blind correction of optical aberrations in a digital image**
International Patent Application, No. PCT/EP2012/068868, April 2014 (patent)

**Single-Source Domain Adaptation with Target and Conditional Shift**
In *Regularization, Optimization, Kernels, and Support Vector Machines*, pages: 427-456, 19, Chapman & Hall/CRC Machine Learning & Pattern Recognition, (Editors: Suykens, J. A. K., Signoretto, M. and Argyriou, A.), Chapman and Hall/CRC, Boca Raton, USA, 2014 (inbook)

**Higher-Order Tensors in Diffusion Imaging**
In *Visualization and Processing of Tensors and Higher Order Descriptors for Multi-Valued Data*, pages: 129-161, Mathematics + Visualization, (Editors: Westin, C.-F., Vilanova, A. and Burgeth, B.), Springer, 2014 (inbook)

**Fuzzy Fibers: Uncertainty in dMRI Tractography**
In *Scientific Visualization: Uncertainty, Multifield, Biomedical, and Scalable Visualization*, pages: 79-92, 8, Mathematics + Visualization, (Editors: Hansen, C. D., Chen, M., Johnson, C. R., Kaufman, A. E. and Hagen, H.), Springer, 2014 (inbook)

**Nonconvex Proximal Splitting with Computational Errors**
In *Regularization, Optimization, Kernels, and Support Vector Machines*, pages: 83-102, 4, (Editors: Suykens, J. A. K., Signoretto, M. and Argyriou, A.), CRC Press, 2014 (inbook)

**Active Learning - Modern Learning Theory**
In *Encyclopedia of Algorithms*, (Editors: Kao, M.-Y.), Springer Berlin Heidelberg, 2014 (incollection)

**Method for determining a property map of an object, particularly of a living being, based on at least a first image, particularly a magnetic resonance image**
United States Patent, No. 8290568, October 2012 (patent)

**Kernels for identifying patterns in datasets containing noise or transformation invariances**
United States Patent, No. 8209269, June 2012 (patent)

**Expectation-Maximization methods for solving (PO)MDPs and optimal control problems**
In *Inference and Learning in Dynamic Models*, (Editors: Barber, D., Cemgil, A.T. and Chiappa, S.), Cambridge University Press, Cambridge, UK, January 2012 (inbook) In press

**Active Learning Methods in Classification of Remote Sensing Images**
In *Signal and Image Processing for Remote Sensing*, (Editors: CH Chen), CRC Press, Boca Raton, FL, USA, January 2012 (inbook) In press

**Inferential structure determination from NMR data**
In *Bayesian methods in structural bioinformatics*, pages: 287-312, (Editors: Hamelryck, T., Mardia, K. V. and Ferkinghoff-Borg, J.), Springer, New York, 2012 (inbook)

**Robot Learning**
In *Encyclopedia of the sciences of learning*, (Editors: Seel, N.M.), Springer, Berlin, Germany, 2012 (inbook)

**Reinforcement Learning in Robotics: A Survey**
In *Reinforcement Learning*, 12, pages: 579-610, (Editors: Wiering, M. and Otterlo, M.), Springer, Berlin, Germany, 2012 (inbook)

**Higher-Order Tensors in Diffusion MRI**
In *Visualization and Processing of Tensors and Higher Order Descriptors for Multi-Valued Data*, (Editors: Westin, C. F., Vilanova, A. and Burgeth, B.), Springer, 2012 (inbook) Accepted

**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)

**Support Vector Machines**
In *Handbook of Brain Theory and Neural Networks (2nd edition)*, pages: 1119-1125, (Editors: MA Arbib), MIT Press, Cambridge, MA, USA, 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)

**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)

**Statistical Learning and Kernel Methods**
In *Adaptivity and Learning—An Interdisciplinary Debate*, pages: 161-186, (Editors: R.Kühn and R Menzel and W Menzel and U Ratsch and MM Richter and I-O Stamatescu), Springer, Berlin, Heidelberg, 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)

**Extracting egomotion from optic flow: limits of accuracy and neural matched filters**
In pages: 143-168, Springer, Berlin, 2001 (inbook)

**Robust ensemble learning**
In *Advances in Large Margin Classifiers*, pages: 207-220, Neural Information Processing Series, (Editors: AJ Smola and PJ Bartlett and B Schölkopf and D. Schuurmans), MIT Press, Cambridge, MA, USA, October 2000 (inbook)

**Entropy numbers for convex combinations and MLPs**
In *Advances in Large Margin Classifiers*, pages: 369-387, Neural Information Processing Series, (Editors: AJ Smola and PL Bartlett and B Schölkopf and D Schuurmans), MIT Press, Cambridge, MA,, October 2000 (inbook)

**Natural Regularization from Generative Models**
In *Advances in Large Margin Classifiers*, pages: 51-60, Neural Information Processing Series, (Editors: AJ Smola and PJ Bartlett and B Schölkopf and D Schuurmans), MIT Press, Cambridge, MA, USA, October 2000 (inbook)

**Solving Satisfiability Problems with Genetic Algorithms**
In *Genetic Algorithms and Genetic Programming at Stanford 2000*, pages: 206-213, (Editors: Koza, J. R.), Stanford Bookstore, Stanford, CA, USA, June 2000 (inbook)

**Statistical Learning and Kernel Methods**
In *CISM Courses and Lectures, International Centre for Mechanical Sciences Vol.431*, *CISM Courses and Lectures, International Centre for
Mechanical Sciences*, 431(23):3-24, (Editors: G Della Riccia and H-J Lenz and R Kruse), Springer, Vienna, Data Fusion and Perception, 2000 (inbook)

**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)