88 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)

**Elements of Causal Inference - Foundations and Learning Algorithms**
Adaptive Computation and Machine Learning Series, The MIT Press, Cambridge, MA, USA, 2017 (book)

**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)

**New Directions for Learning with Kernels and Gaussian Processes (Dagstuhl Seminar 16481)**
*Dagstuhl Reports*, 6(11):142-167, 2017 (book)

**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)

**easyGWAS: An Integrated Computational Framework for Advanced Genome-Wide Association Studies**
Eberhard Karls Universität Tübingen, November 2015 (phdthesis)

**Causal Discovery Beyond Conditional Independences**
Eberhard Karls Universität Tübingen, Germany, October 2015 (phdthesis)

**From Points to Probability Measures: A Statistical Learning on Distributions with Kernel Mean Embedding**
University of Tübingen, Germany, University of Tübingen, Germany, September 2015 (phdthesis)

**Machine Learning Approaches to Image Deconvolution**
University of Tübingen, Germany, University of Tübingen, Germany, September 2015 (phdthesis)

**Kernel methods in medical imaging**
In *Handbook of Biomedical Imaging*, pages: 63-81, 4, (Editors: Paragios, N., Duncan, J. and Ayache, N.), Springer, Berlin, Germany, June 2015 (inbook)

**Blind Retrospective Motion Correction of MR Images**
University of Tübingen, Germany, May 2015 (phdthesis)

**Statistical and Machine Learning Methods for Neuroimaging: Examples, Challenges, and Extensions to Diffusion Imaging Data**
In *Visualization and Processing of Higher Order Descriptors for Multi-Valued Data*, pages: 299-319, (Editors: Hotz, I. and Schultz, T.), Springer, 2015 (inbook)

**A Cognitive Brain-Computer Interface for Patients with Amyotrophic Lateral Sclerosis**
Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2015 (mastersthesis)

**Sequential Image Deconvolution Using Probabilistic Linear Algebra**
Technical University of Munich, Germany, 2015 (mastersthesis)

**Causal Inference in Neuroimaging**
Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2015 (mastersthesis)

**The effect of frowning on attention**
Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2015 (mastersthesis)

**Justifying Information-Geometric Causal Inference**
In *Measures of Complexity: Festschrift for Alexey Chervonenkis*, pages: 253-265, 18, (Editors: Vovk, V., Papadopoulos, H. and Gammerman, A.), Springer, 2015 (inbook)

**Camera-specific Image Denoising**
Eberhard Karls Universität Tübingen, Germany, October 2013 (diplomathesis)

**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)

**Modelling and Learning Approaches to Image Denoising**
Eberhard Karls Universität Tübingen, Germany, 2013 (phdthesis)

**Proceedings of the 10th European Workshop on Reinforcement Learning, Volume 24 **
pages: 173, JMLR, European Workshop On Reinforcement Learning, EWRL, 2013 (proceedings)

**Linear mixed models for genome-wide association studies**
University of Tübingen, Germany, 2013 (phdthesis)

**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)

**Modeling and Learning Complex Motor Tasks: A case study on Robot Table Tennis**
Technical University Darmstadt, Germany, 2013 (phdthesis)

**Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik**
Springer, 2013 (book)

**Intention Inference and Decision Making with Hierarchical Gaussian Process Dynamics Models**
Technical University Darmstadt, Germany, 2013 (phdthesis)

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

**Kernel Learning Approaches for Image Classification**
Biologische Kybernetik, Universität des Saarlandes, Saarbrücken, Germany, October 2009 (phdthesis)

**A PAC-Bayesian Approach to Structure Learning**
Biologische Kybernetik, The Hebrew University of Jerusalem, Israel, September 2009 (phdthesis)

**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)

**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)

**Kernel Methods in Computer Vision:Object Localization, Clustering,and Taxonomy Discovery**
Biologische Kybernetik, Technische Universität Berlin, Berlin, Germany, March 2009 (phdthesis)

**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)

**Motor Control and Learning in Table Tennis**
Eberhard Karls Universität Tübingen, Gerrmany, 2009 (diplomathesis)

**Hierarchical Clustering and Density Estimation Based on k-nearest-neighbor graphs**
Eberhard Karls Universität Tübingen, Germany, 2009 (diplomathesis)

**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)

**Learning with Structured Data: Applications to Computer Vision**
Technische Universität Berlin, Germany, 2009 (phdthesis)

**From Differential Equations to Differential Geometry: Aspects of Regularisation in Machine Learning**
Universität des Saarlandes, Saarbrücken, Germany, 2009 (phdthesis)

**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)

**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)