67 results
(View BibTeX file of all listed publications)

**Modeling the polygenic architecture of complex traits**
Eberhard Karls Universität Tübingen, November 2014 (phdthesis)

**Unsupervised identification of neural events in local field potentials**
44th Annual Meeting of the Society for Neuroscience (Neuroscience), 2014 (talk)

**A Novel Causal Inference Method for Time Series**
Eberhard Karls Universität Tübingen, Germany, Eberhard Karls Universität Tübingen, Germany, 2014 (mastersthesis)

**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)

**Quantifying statistical dependency**
Research Network on Learning Systems Summer School, 2014 (talk)

**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)

**A global analysis of extreme events and consequences for the terrestrial carbon cycle**
Diss. No. 22043, ETH Zurich, Switzerland, ETH Zurich, Switzerland, 2014 (phdthesis)

**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)

**Development of advanced methods for improving astronomical images**
Eberhard Karls Universität Tübingen, Germany, Eberhard Karls Universität Tübingen, Germany, 2014 (diplomathesis)

**The Feasibility of Causal Discovery in Complex Systems: An Examination of Climate Change Attribution and Detection**
Graduate Training Centre of Neuroscience, University of Tübingen, Germany, Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2014 (mastersthesis)

**Causal Discovery in the Presence of Time-Dependent Relations or Small Sample Size**
Graduate Training Centre of Neuroscience, University of Tübingen, Germany, Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2014 (mastersthesis)

**Causal Inference from Passive Observations**
24th Summer School University of Jyväskylā, Finland, August, 2014 (talk)

**Analysis of Distance Functions in Graphs**
University of Hamburg, Germany, University of Hamburg, Germany, 2014 (phdthesis)

**A Kernel Method for the Two-Sample-Problem**
20th Annual Conference on Neural Information Processing Systems (NIPS), December 2006 (talk)

**Ab-initio gene finding using machine learning**
NIPS Workshop on New Problems and Methods in Computational Biology, December 2006 (talk)

**Graph boosting for molecular QSAR analysis**
NIPS Workshop on New Problems and Methods in Computational Biology, December 2006 (talk)

**Inferring Causal Directions by Evaluating the Complexity of Conditional Distributions**
NIPS Workshop on Causality and Feature Selection, December 2006 (talk)

**Learning Optimal EEG Features Across Time, Frequency and Space**
NIPS Workshop on Current Trends in Brain-Computer Interfacing, December 2006 (talk)

**Semi-Supervised Learning**
Advanced Methods in Sequence Analysis Lectures, November 2006 (talk)

**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)

**A Machine Learning Approach for Determining the PET Attenuation Map from Magnetic Resonance Images**
IEEE Medical Imaging Conference, November 2006 (talk)

**Semi-Supervised Support Vector Machines and Application to Spam Filtering**
ECML Discovery Challenge Workshop, September 2006 (talk)

**Inferential Structure Determination: Probabilistic determination and validation of NMR structures**
Gordon Research Conference on Computational Aspects of Biomolecular
NMR, September 2006 (talk)

**Machine Learning Algorithms for Polymorphism Detection**
2nd ISCB Student Council Symposium, August 2006 (talk)

**Inferential structure determination: Overview and new developments**
Sixth CCPN Annual Conference: Efficient and Rapid Structure Determination by NMR, July 2006 (talk)

**MCMC inference in (Conditionally) Conjugate Dirichlet Process Gaussian Mixture Models**
ICML Workshop on Learning with Nonparametric Bayesian Methods, June 2006 (talk)

**Sampling for non-conjugate infinite latent feature models**
(Editors: Bernardo, J. M.), 8th Valencia International Meeting on Bayesian Statistics (ISBA), June 2006 (talk)

**Kernel PCA for Image Compression**
Biologische Kybernetik, Eberhard-Karls-Universität, Tübingen, Germany, April 2006 (diplomathesis)

**An Inventory of Sequence Polymorphisms For Arabidopsis**
17th International Conference on Arabidopsis Research, April 2006 (talk)

**Gaussian Process Models for Robust Regression, Classification, and Reinforcement Learning**
Biologische Kybernetik, Technische Universität Darmstadt, Darmstadt, Germany, March 2006, passed with distinction, published online (phdthesis)

**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)

ei
Zhou, D.
**Discrete vs. Continuous: Two Sides of Machine Learning**
October 2004 (talk)

ei
Zhou, D.
**Discrete vs. Continuous: Two Sides of Machine Learning**
October 2004 (talk)

**Grundlagen von Support Vector Maschinen und Anwendungen in der Bildverarbeitung**
September 2004 (talk)

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

**Learning from Labeled and Unlabeled Data: Semi-supervised Learning and Ranking**
January 2004 (talk)

ei
Bousquet, O.
**Introduction to Category Theory**
Internal Seminar, January 2004 (talk)

**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)

**Statistical Learning with Similarity and Dissimilarity Functions**
pages: 1-166, Technische Universität Berlin, Germany, Technische Universität Berlin, Germany, 2004 (phdthesis)

**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)

**Classification and Feature Extraction in Man and Machine**
Biologische Kybernetik, University of Tübingen, Germany, 2004, online publication (phdthesis)

**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)