61 results
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**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2016 (unpublished) Submitted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)

**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)

**Detection of objects in noisy images and site percolation on square lattices**
(2009-035), EURANDOM, Technische Universiteit Eindhoven, November 2009 (techreport)

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

**Toward a Theory of Consciousness**
In *The Cognitive Neurosciences*, pages: 1201-1220, (Editors: Gazzaniga, M.S.), MIT Press, Cambridge, MA, USA, October 2009 (inbook)

**Algebraic polynomials and moments of stochastic integrals**
(2009-031), EURANDOM, Technische Universiteit Eindhoven, October 2009 (techreport)

**Expectation Propagation on the Maximum of Correlated Normal Variables**
Cavendish Laboratory: University of Cambridge, July 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)

**Model selection, large deviations and consistency of data-driven tests**
(2009-007), EURANDOM, Technische Universiteit Eindhoven, March 2009 (techreport)

**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)

**An introduction to Kernel Learning Algorithms**
In *Kernel Methods for Remote Sensing Data Analysis*, pages: 25-48, 2, (Editors: Gustavo Camps-Valls and Lorenzo Bruzzone), Wiley, New York, NY, USA, 2009 (inbook)

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

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

**Technical report on
Separation methods for nonlinear
mixtures**
(D29), EU-Project BLISS, October 2003 (techreport)

**Technical report on implementation
of linear methods and validation on
acoustic sources**
EU-Project BLISS, September 2003 (techreport)

**On optimization, parallelization and convergence of the Expectation-Maximization algorithm for finite mixtures of Bernoulli distributions.**
Helsinki University of Technology, Helsinki, Finland, August 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 Metric Nearness Problem with Applications**
Univ. of Texas at Austin, 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)

**Expectation Maximization for Clustering on Hyperspheres**
Univ. of Texas at Austin, February 2003 (techreport)

**Modeling Data using Directional Distributions**
Univ. of Texas at Austin, January 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)

**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)

**Prediction at an Uncertain Input for Gaussian Processes and Relevance Vector Machines - Application to Multiple-Step Ahead Time-Series Forecasting**
(IMM-2003-18), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, 2003 (techreport)

**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)

**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)