48 results
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**Robot Learning for Muscular Systems**
Technical University Darmstadt, Germany, December 2019 (phdthesis)

**Real Time Probabilistic Models for Robot Trajectories**
Technical University Darmstadt, Germany, December 2019 (phdthesis)

**Reinforcement Learning for a Two-Robot Table Tennis Simulation**
RWTH Aachen University, Germany, July 2019 (mastersthesis)

**Learning Transferable Representations**
University of Cambridge, UK, 2019 (phdthesis)

**Sample-efficient deep reinforcement learning for continuous control**
University of Cambridge, UK, 2019 (phdthesis)

**Spatial Filtering based on Riemannian Manifold for Brain-Computer Interfacing**
Technical University of Munich, Germany, 2019 (mastersthesis)

**Pragmatism and Variable Transformations in Causal Modelling**
ETH Zurich, 2019 (phdthesis)

**Formally justified and modular Bayesian inference for probabilistic programs**
University of Cambridge, UK, 2019 (phdthesis)

**Quantification of tumor heterogeneity using PET/MRI and machine learning**
Eberhard Karls Universität Tübingen, Germany, 2019 (phdthesis)

**Advances in Probabilistic Modelling: Sparse Gaussian Processes, Autoencoders, and Few-shot Learning**
University of Cambridge, UK, 2019 (phdthesis)

**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)

**Nonparametric Disturbance Correction and Nonlinear Dual Control**
(24098), ETH Zurich, 2017 (phdthesis)

**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)

**Development and Evaluation of a Portable BCI System for Remote Data Acquisition**
Graduate School of Neural Information Processing, Eberhard Karls Universität Tübingen, Germany, 2017 (mastersthesis)

**Brain-Computer Interfaces for patients with Amyotrophic Lateral Sclerosis**
Eberhard Karls Universität Tübingen, Germany, 2017 (phdthesis)

**Causal models for decision making via integrative inference**
University of Stuttgart, Germany, 2017 (phdthesis)

**Learning Optimal Configurations for Modeling Frowning by Transcranial Electrical Stimulation**
Graduate School of Neural Information Processing, Eberhard Karls Universität Tübingen, Germany, 2017 (mastersthesis)

**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)

**Crowdsourcing for optimisation of deconvolution methods via an iPhone application**
Hochschule Reutlingen, Germany, April 2011 (mastersthesis)

**Learning functions with kernel methods**
University of Pavia, Italy, January 2011 (phdthesis)

**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)

**Model Learning in Robot Control**
Albert-Ludwigs-Universität Freiburg, Germany, 2011 (phdthesis)

**Extension to Kernel Dependency Estimation with Applications to Robotics**
Biologische Kybernetik, Technische Universität Berlin, Berlin, November 2005 (phdthesis)

**Geometrical aspects of statistical learning theory**
Biologische Kybernetik, Darmstadt, Darmstadt, November 2005 (phdthesis)

**Implicit Surfaces For Modelling
Human Heads**
Biologische Kybernetik, Eberhard-Karls-Universität, Tübingen, September 2005 (diplomathesis)

**Machine Learning Methods for Brain-Computer Interdaces**
Biologische Kybernetik, University of Darmstadt, September 2005 (phdthesis)

**Liver Perfusion using Level Set Methods**
Biologische Kybernetik, Shanghai JiaoTong University, Shanghai, China, July 2005 (diplomathesis)

**Efficient Adaptive Sampling of the Psychometric Function by Maximizing Information Gain**
Biologische Kybernetik, Eberhard-Karls University Tübingen, Tübingen, Germany, May 2005 (diplomathesis)

**Discriminative Methods for Label Sequence Learning**
Brown University, Providence, RI, USA, May 2005 (phdthesis)

**Support Vector Classification of Images with Local Features**
Biologische Kybernetik, University of Massachusetts, Amherst, May 2005 (diplomathesis)

**Efficient Pattern Selection for Support Vector Classifiers and its CRM Application**
Biologische Kybernetik, Seoul National University, Seoul, Korea, February 2005 (phdthesis)

**Kernels: Regularization and Optimization**
Biologische Kybernetik, The Australian National University, Canberra, Australia, 2005 (phdthesis)

**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)

**Nonlinear Multivariate Analysis with Geodesic Kernels**
Biologische Kybernetik, Technische Universität Berlin, February 2002 (diplomathesis)

**Concentration Inequalities and Empirical Processes Theory Applied to the Analysis of Learning Algorithms**
Biologische Kybernetik, Ecole Polytechnique, 2002 (phdthesis) Accepted

**Support Vector Machines: Induction Principle, Adaptive Tuning and Prior Knowledge**
Biologische Kybernetik, 2002 (phdthesis)

**Eine beweistheoretische Anwendung der **
Biologische Kybernetik, Westfälische Wilhelms-Universität Münster, Münster, May 1998 (diplomathesis)

**Qualitative Modeling for Data Miner‘s Requirement**
Biologische Kybernetik, Hong-Ik University, Seoul, Korea, February 1998, Written in Korean (diplomathesis)

**Support Vector Machines for Image Classification**
Biologische Kybernetik, Ecole Normale Superieure de Lyon, 1998 (diplomathesis)

**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)