24 results
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**Robot Learning**
In *Springer Handbook of Robotics*, pages: 357-394, 15, 2nd, (Editors: Siciliano, Bruno and Khatib, Oussama), Springer International Publishing, 2017 (inbook)

**Policy Gradient Methods**
In *Encyclopedia of Machine Learning and Data Mining*, pages: 982-985, 2nd, (Editors: Sammut, Claude and Webb, Geoffrey I.), Springer US, 2017 (inbook)

**Unsupervised clustering of EOG as a viable substitute for optical eye-tracking**
In *First Workshop on Eye Tracking and Visualization (ETVIS 2015)*, pages: 151-167, Mathematics and Visualization, (Editors: Burch, M., Chuang, L., Fisher, B., Schmidt, A., and Weiskopf, D.), Springer, 2017 (inbook)

**Statistical Asymmetries Between Cause and Effect**
In *Time in Physics*, pages: 129-139, Tutorials, Schools, and Workshops in the Mathematical Sciences, (Editors: Renner, Renato and Stupar, Sandra), Springer International Publishing, Cham, 2017 (inbook)

**Robot Learning**
In *Encyclopedia of Machine Learning and Data Mining*, pages: 1106-1109, 2nd, (Editors: Sammut, Claude and Webb, Geoffrey I.), Springer US, 2017 (inbook)

**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)

**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)

**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)

**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)

**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)

**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)

**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)

**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)

**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)