64 results
(View BibTeX file of all listed publications)

**Causal Inference for Empirical Time Series Based on the Postulate of Independence of Cause and Mechanism**
*53rd Annual Allerton Conference on Communication, Control, and Computing*, September 2015 (talk)

**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)

**Independence of cause and mechanism in brain networks**
*DALI workshop on Networks: Processes and Causality*, April 2015 (talk)

**Information-Theoretic Implications of Classical and Quantum Causal Structures **
18th Conference on Quantum Information Processing (QIP), 2015 (talk)

**Assessment of brain tissue damage in the Sub-Acute Stroke Region by Multiparametric Imaging using [89-Zr]-Desferal-EPO-PET/MRI**
World Molecular Imaging Conference, 2015 (talk)

**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)

**Early time point in vivo PET/MR is a promising biomarker for determining efficacy of a novel Db(\alphaEGFR)-scTRAIL fusion protein therapy in a colon cancer model**
World Molecular Imaging Conference, 2015 (talk)

**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)

**The search for single exoplanet transits in the Kepler light curves**
*IAU General Assembly*, 22, pages: 2258352, 2015 (talk)

**Spectral clustering and transductive inference for graph data**
NIPS Workshop on Kernel Methods and Structured Domains, December 2005 (talk)

**Some thoughts about Gaussian Processes**
NIPS Workshop on Open Problems in Gaussian Processes for Machine Learning, December 2005 (talk)

Chapelle, O.
**A taxonomy of semi-supervised learning algorithms**
Yahoo!, December 2005 (talk)

**Building Sparse Large Margin Classifiers**
The 22nd International Conference on Machine Learning (ICML), August 2005 (talk)

**Learning from Labeled and Unlabeled Data on a Directed Graph**
The 22nd International Conference on Machine Learning, August 2005 (talk)

**Machine-Learning Approaches to BCI in Tübingen**
Brain-Computer Interface Technology, June 2005, Talk given by NJH. (talk)

**Learning Motor Primitives with Reinforcement Learning**
ROBOTICS Workshop on Modular Foundations for Control and Perception, June 2005 (talk)

**Motor Skill Learning for Humanoid Robots**
First Conference Undergraduate Computer Sciences and Informations Sciences (CS/IS), May 2005 (talk)

**Kernel Constrained Covariance for Dependence Measurement**
AISTATS, January 2005 (talk)

**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)

Zhou, D.
**How to learn from very few examples?**
October 2004 (talk)

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

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)

**Advanced Lectures on Machine Learning**
*ML Summer Schools 2003*, LNAI 3176, pages: 240, Springer, Berlin, Germany, ML Summer Schools, September 2004 (proceedings)

**Pattern Recognition: 26th DAGM Symposium, LNCS, Vol. 3175**
*Proceedings of the 26th Pattern Recognition Symposium (DAGM‘04)*, pages: 581, Springer, Berlin, Germany, 26th Pattern Recognition Symposium, August 2004 (proceedings)

**The benefit of liquid Helium cooling for Cryo-Electron Tomography: A quantitative
comparative study**
The thirteenth European Microscopy Congress, August 2004 (talk)

**Analysis of differential gene expression in healthy and osteoarthritic cartilage and isolated chondrocytes by microarray analysis**
In Volume 1: Cellular and Molecular Tools, pages: 109-128, (Editors: Sabatini, M., P. Pastoureau and F. De Ceuninck), Humana Press, July 2004 (inbook)

**Advances in Neural Information Processing Systems 16: Proceedings of the 2003 Conference**
*Proceedings of the Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003)*, pages: 1621, MIT Press, Cambridge, MA, USA, 17th Annual Conference on Neural Information Processing Systems (NIPS), June 2004 (proceedings)

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

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

**Local Alignment Kernels for Biological Sequences**
In *Kernel Methods in Computational Biology*, pages: 131-153, MIT Press, Cambridge, MA,, 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)

Bousquet, O.
**Advanced Statistical Learning Theory**
Machine Learning Summer School, 2004 (talk)

**Learning Control and Planning from the View of Control Theory and Imitation**
NIPS Workshop "Planning for the Real World: The promises and challenges of dealing with uncertainty", December 2003 (talk)

**Recurrent neural networks from learning attractor dynamics**
NIPS Workshop on RNNaissance: Recurrent Neural Networks, December 2003 (talk)

**Learning Theory and Kernel Machines: 16th Annual Conference on Learning Theory and 7th Kernel Workshop (COLT/Kernel 2003), LNCS Vol. 2777**
*Proceedings of the 16th Annual Conference on Learning Theory and 7th Kernel Workshop (COLT/Kernel 2003)*, *COLT/Kernel 2003*, pages: 746, Springer, Berlin, Germany, 16th Annual Conference on Learning Theory and 7th Kernel Workshop, November 2003, Lecture Notes in Computer Science ; 2777 (proceedings)

Bousquet, O.
**Statistical Learning Theory**
Machine Learning Summer School, August 2003 (talk)

**Remarks on Statistical Learning Theory**
Machine Learning Summer School, August 2003 (talk)

**Rademacher and Gaussian averages in Learning Theory**
Universite de Marne-la-Vallee, March 2003 (talk)

Bousquet, O., Schölkopf, B.
**Statistical Learning Theory**
March 2003 (talk)

**Concentration Inequalities and Data-Dependent Error Bounds**
Uni. Jena, February 2003 (talk)