15 results
(View BibTeX file of all listed publications)

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

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

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)

**Kernel Methods in Computational Biology**
pages: 410, Computational Molecular Biology, MIT Press, Cambridge, MA, USA, August 2004 (book)

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

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

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

**Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond**
pages: 644, Adaptive Computation and Machine Learning, MIT Press, Cambridge, MA, USA, December 2002, Parts of this book, including an introduction to kernel methods, can be downloaded here. (book)

Bousquet, O.
**Transductive Learning: Motivation, Models, Algorithms**
January 2002 (talk)

**Support Vector methods in learning and feature extraction**
*Ninth Australian Conference on Neural Networks*, pages: 72-78, (Editors: T. Downs, M. Frean and M. Gallagher), 1998 (talk)