24 results
(View BibTeX file of all listed publications)

**Nonlinear functional causal models for distinguishing cause from effect**
In *Statistics and Causality: Methods for Applied Empirical Research*, pages: 185-201, 8, 1st, (Editors: Wolfgang Wiedermann and Alexander von Eye), John Wiley & Sons, Inc., 2016 (inbook)

**A cognitive brain–computer interface for patients with amyotrophic lateral sclerosis**
In *Brain-Computer Interfaces: Lab Experiments to Real-World Applications*, 228(Supplement C):221-239, 8, Progress in Brain Research, (Editors: Damien Coyle), Elsevier, 2016 (incollection)

**Screening Rules for Convex Problems**
2016 (unpublished) Submitted

**Learning Motor Skills: From Algorithms to Robot Experiments**
97, pages: 191, Springer Tracts in Advanced Robotics, Springer, 2014 (book)

**Computational Diffusion MRI and Brain Connectivity**
pages: 255, Mathematics and Visualization, Springer, 2014 (book)

**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)

**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)

**Optimization for Machine Learning**
pages: 494, Neural information processing series, MIT Press, Cambridge, MA, USA, December 2011 (book)

**Bayesian Time Series Models**
pages: 432, Cambridge University Press, Cambridge, UK, August 2011 (book)

**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)

**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)

**Handbook of Statistical Bioinformatics**
pages: 627, Springer Handbooks of Computational Statistics, Springer, Berlin, Germany, 2011 (book)

**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)

**Support Vector Machines and Kernel Algorithms**
In *Encyclopedia of Biostatistics (2nd edition), Vol. 8*, 8, pages: 5328-5335, (Editors: P Armitage and T Colton), John Wiley & Sons, NY USA, 2005 (inbook)

**Visual perception
I: Basic principles**
In *Handbook of Cognition*, pages: 3-47, (Editors: Lamberts, K. , R. Goldstone), Sage, London, 2005 (inbook)

**Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond**
pages: 644, Adaptive Computation and Machine Learning, MIT Press, Cambridge, MA, USA, December 2002, Parts of this book, including an introduction to kernel methods, can be downloaded here. (book)

**Support-Vektor-Lernen**
In *Ausgezeichnete Informatikdissertationen 1997*, pages: 135-150, (Editors: G Hotz and H Fiedler and P Gorny and W Grass and S Hölldobler and IO Kerner and R Reischuk), Teubner Verlag, Stuttgart, 1998 (inbook)

**Support vector learning**
pages: 173, Oldenbourg, München, Germany, 1997, Zugl.: Berlin, Techn. Univ., Diss., 1997 (book)