26 results
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**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

**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

**An Introduction to Random Forests for Multi-class Object Detection**
In *Outdoor and Large-Scale Real-World Scene Analysis*, 7474, pages: 243-263, LNCS, (Editors: Dellaert, Frank and Frahm, Jan-Michael and Pollefeys, Marc and Rosenhahn, Bodo and Leal-Taix’e, Laura), Springer, 2012 (incollection)

**Home 3D body scans from noisy image and range data**
In *Consumer Depth Cameras for Computer Vision: Research Topics and Applications*, pages: 99-118, 6, (Editors: Andrea Fossati and Juergen Gall and Helmut Grabner and Xiaofeng Ren and Kurt Konolige), Springer-Verlag, 2012 (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)

**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)

**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)

**Benchmark datasets for pose estimation and tracking**
In *Visual Analysis of Humans: Looking at People*, pages: 253-274, (Editors: Moesland and Hilton and Kr"uger and Sigal), Springer-Verlag, London, 2011 (incollection)

**Steerable random fields for image restoration and inpainting**
In *Markov Random Fields for Vision and Image Processing*, pages: 377-387, (Editors: Blake, A. and Kohli, P. and Rother, C.), MIT Press, 2011 (incollection)

**Distributed Command Execution**
In *BSD Hacks: 100 industrial-strength tips & tools*, pages: 152-152, (Editors: Lavigne, Dru), O’Reilly, Beijing, May 2004 (inbook)

**Gaussian Processes in Machine Learning**
In 3176, pages: 63-71, Lecture Notes in Computer Science, (Editors: Bousquet, O., U. von Luxburg and G. Rätsch), Springer, Heidelberg, 2004, Copyright by Springer (inbook)

**Protein Classification via Kernel Matrix Completion**
In pages: 261-274, (Editors: Schoelkopf, B., K. Tsuda and J.P. Vert), MIT Press, Cambridge, MA; USA, 2004 (inbook)

**Introduction to Statistical Learning Theory**
In Lecture Notes in Artificial Intelligence 3176, pages: 169-207, (Editors: Bousquet, O., U. von Luxburg and G. Rätsch), Springer, Heidelberg, Germany, 2004 (inbook)

**A Primer on Kernel Methods**
In *Kernel Methods in Computational Biology*, pages: 35-70, (Editors: B Schölkopf and K Tsuda and JP Vert), MIT Press, Cambridge, MA, USA, 2004 (inbook)

**Concentration Inequalities**
In Lecture Notes in Artificial Intelligence 3176, pages: 208-240, (Editors: Bousquet, O., U. von Luxburg and G. Rätsch), Springer, Heidelberg, Germany, 2004 (inbook)

**Kernels for graphs**
In pages: 155-170, (Editors: Schoelkopf, B., K. Tsuda and J.P. Vert), MIT Press, Cambridge, MA; USA, 2004 (inbook)

**A primer on molecular biology**
In pages: 3-34, (Editors: Schoelkopf, B., K. Tsuda and J. P. Vert), MIT Press, Cambridge, MA, USA, 2004 (inbook)

**Computational approaches to motor learning by imitation**
In *The Neuroscience of Social Interaction*, (1431):199-218, (Editors: Frith, C. D.;Wolpert, D.), Oxford University Press, Oxford, 2004, clmc (inbook)

**Batting a ball: Dynamics of a rhythmic skill**
In *Studies in Perception and Action*, pages: 119-122, (Editors: Bardy, B.;Bostma, R.;Guiard, Y.), Erlbaum, Hillsdayle, NJ, 1995, clmc (inbook)

**Informationssysteme mit CAD (Information systems within CAD)**
In *CAD/CAM Grundlagen*, pages: 199-204, (Editors: Milberg, J.), Springer, Buchreihe CIM-TT. Berlin, 1992, clmc (inbook)