41 results
(View BibTeX file of all listed publications)

**Relative gradient optimization of the jacobian term in unsupervised deep learning**
2020 (misc)

**Learning explanations that are hard to vary**
2020 (misc)

**TUM Flyers: Vision-Based MAV Navigation for Systematic Inspection of Structures**
In *Bringing Innovative Robotic Technologies from Research Labs to Industrial End-users: The Experience of the European Robotics Challenges*, 136, pages: 189-209, Springer International Publishing, 2020 (inbook)

**On the Fairness of Causal Algorithmic Recourse**
2020 (misc) Submitted

**A survey of algorithmic recourse: definitions, formulations, solutions, and prospects**
2020 (misc) Submitted

**A machine learning route between band mapping and band structure**
2020, *equal contribution (misc)

**Scaling Guarantees for Nearest Counterfactual Explanations**
2020 (misc) Submitted

**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)

**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

**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)

**New Frontiers in Characterizing Structure and Dynamics by NMR**
In *Computational Structural Biology: Methods and Applications*, pages: 655-680, (Editors: Schwede, T. , M. C. Peitsch), World Scientific, New Jersey, NJ, USA, May 2008 (inbook)

**A Robot System for Biomimetic Navigation: From Snapshots to Metric Embeddings of View Graphs**
In *Robotics and Cognitive Approaches to Spatial Mapping*, pages: 297-314, Springer Tracts in Advanced Robotics ; 38, (Editors: Jefferies, M.E. , W.-K. Yeap), Springer, Berlin, Germany, 2008 (inbook)

**Support Vector Machine Learning for Interdependent and Structured Output Spaces**
In *Predicting Structured Data*, pages: 85-104, Advances in neural information processing systems, (Editors: Bakir, G. H. , T. Hofmann, B. Schölkopf, A. J. Smola, B. Taskar, S. V. N. Vishwanathan), MIT Press, Cambridge, MA, USA, September 2007 (inbook)

**Brisk Kernel ICA**
In *Large Scale Kernel Machines*, pages: 225-250, Neural Information Processing, (Editors: Bottou, L. , O. Chapelle, D. DeCoste, J. Weston), MIT Press, Cambridge, MA, USA, September 2007 (inbook)

**Training a Support Vector Machine in the Primal**
In *Large Scale Kernel Machines*, pages: 29-50, Neural Information Processing, (Editors: Bottou, L. , O. Chapelle, D. DeCoste, J. Weston), MIT Press, Cambridge, MA, USA, September 2007, This is a slightly updated version of the Neural Computation paper (inbook)

**Approximation Methods for Gaussian Process Regression**
In *Large-Scale Kernel Machines*, pages: 203-223, Neural Information Processing, (Editors: Bottou, L. , O. Chapelle, D. DeCoste, J. Weston), MIT Press, Cambridge, MA, USA, September 2007 (inbook)

**Trading Convexity for Scalability**
In *Large Scale Kernel Machines*, pages: 275-300, Neural Information Processing, (Editors: Bottou, L. , O. Chapelle, D. DeCoste, J. Weston), MIT Press, Cambridge, MA, USA, September 2007 (inbook)

**Classifying Event-Related Desynchronization in EEG, ECoG and MEG signals**
In *Toward Brain-Computer Interfacing*, pages: 235-260, Neural Information Processing, (Editors: G Dornhege and J del R Millán and T Hinterberger and DJ McFarland and K-R Müller), MIT Press, Cambridge, MA, USA, September 2007 (inbook)

**Joint Kernel Maps**
In *Predicting Structured Data*, pages: 67-84, Advances in neural information processing systems, (Editors: GH Bakir and T Hofmann and B Schölkopf and AJ Smola and B Taskar and SVN Vishwanathan), MIT Press, Cambridge, MA, USA, September 2007 (inbook)

**Brain-Computer Interfaces for Communication in Paralysis: A Clinical Experimental Approach**
In *Toward Brain-Computer Interfacing*, pages: 43-64, Neural Information Processing, (Editors: G. Dornhege and J del R Millán and T Hinterberger and DJ McFarland and K-R Müller), MIT Press, Cambridge, MA, USA, September 2007 (inbook)

**Probabilistic Structure Calculation**
In *Structure and Biophysics: New Technologies for Current Challenges in Biology and Beyond*, pages: 81-98, NATO Security through Science Series, (Editors: Puglisi, J. D.), Springer, Berlin, Germany, March 2007 (inbook)

**On the Pre-Image Problem in Kernel Methods**
In *Kernel Methods in Bioengineering, Signal and Image Processing*, pages: 284-302, (Editors: G Camps-Valls and JL Rojo-Álvarez and M Martínez-Ramón), Idea Group Publishing, Hershey, PA, USA, January 2007 (inbook)

**Mathematik der Wahrnehmung: Wendepunkte**
*Akademische Mitteilungen zw{\"o}lf: F{\"u}nf Sinne*, pages: 32-37, 2007 (misc)

**An Introduction to Kernel-Based Learning Algorithms**
In *Handbook of Neural Network Signal Processing*, 4, (Editors: Yu Hen Hu and Jang-Neng Hwang), CRC Press, 2000 (inbook)