227 results
(View BibTeX file of all listed publications)

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

**Statistische Lerntheorie und Empirische Inferenz**
*Jahrbuch der Max-Planck-Gesellschaft*, 2004, pages: 377-382, 2004 (misc)

**Bayesian analysis of the Scatterometer Wind Retrieval Inverse Problem: Some New Approaches**
*Journal of the Royal Statistical Society B*, 66, pages: 1-17, 3, 2004 (article)

**Feature Selection for Support Vector Machines Using Genetic Algorithms**
*International Journal on Artificial Intelligence Tools (Special Issue on Selected Papers from the 15th IEEE International Conference on Tools with Artificial Intelligence 2003)*, 13(4):791-800, 2004 (article)

**Semi-supervised kernel regression using whitened function classes**
In *Pattern Recognition, Proceedings of the 26th DAGM Symposium, Lecture Notes in Computer Science, Vol. 3175*, LNCS 3175, pages: 18-26, (Editors: CE Rasmussen and HH Bülthoff and MA Giese and B Schölkopf), Springer, Berlin, Gerrmany, 26th DAGM Symposium, 2004 (inproceedings)

**Maximal Margin Classification for Metric Spaces**
In *Learning Theory and Kernel Machines*, pages: 72-86, (Editors: Schölkopf, B. and Warmuth, M. K.), Springer, Heidelberg, Germany, 16. Annual Conference on Computational Learning Theory / COLT Kernel, 2004 (inproceedings)

**On the Convergence of Spectral Clustering on Random Samples: The Normalized Case**
In *Proceedings of the 17th Annual Conference on Learning Theory*, pages: 457-471, Proceedings of the 17th Annual Conference on Learning Theory, 2004 (inproceedings)

**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)

**Confidence Sets for Ratios: A Purely Geometric Approach To Fieller’s Theorem**
(133), Max Planck Institute for Biological Cybernetics, 2004 (techreport)

**Transductive Inference with Graphs**
Max Planck Institute for Biological Cybernetics, 2004, See the improved version Regularization on Discrete Spaces. (techreport)

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

**Phenotypic Characterization of Human Chondrocyte Cell Line C-20/A4: A Comparison between Monolayer and Alginate Suspension Culture**
*Cells Tissues Organs*, 178(2):65-77, 2004 (article)

**Kernel Methods and their Potential Use in Signal Processing**
*IEEE Signal Processing Magazine*, (Special issue on Signal Processing for Mining), 2004 (article) Accepted

**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)

**Implicit Wiener series for capturing higher-order interactions in
images**
*Sensory coding and the natural environment*, (Editors: Olshausen, B.A. and M. Lewicki), 2004 (poster)

**Classification and Memory Behaviour of Man Revisited by Machine**
*CSHL Meeting on Computational & Systems Neuroscience (COSYNE)*, 2004 (poster)

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

**Advances in Large Margin Classifiers**
pages: 422, Neural Information Processing, MIT Press, Cambridge, MA, USA, October 2000 (book)

**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)

**Choosing nu in support vector regression with
different noise models — theory and experiments**
In *Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, IJCNN 2000, Neural Computing: New Challenges and Perspectives for the New Millennium*, IEEE, International Joint Conference on Neural Networks, 2000 (inproceedings)

**SVMs — a practical consequence of learning theory**
*IEEE Intelligent Systems and their Applications*, 13(4):18-21, July 1998 (article)

**Prior knowledge in support vector kernels**
In *Advances in Neural Information Processing Systems 10*, pages: 640-646 , (Editors: M Jordan and M Kearns and S Solla ), MIT Press, Cambridge, MA, USA, Eleventh Annual Conference on Neural Information Processing (NIPS), June 1998 (inproceedings)

**From regularization operators to support vector kernels**
In *Advances in Neural Information Processing Systems 10*, pages: 343-349, (Editors: M Jordan and M Kearns and S Solla), MIT Press, Cambridge, MA, USA, 11th Annual Conference on Neural Information Processing (NIPS), June 1998 (inproceedings)

**Learning view graphs for robot navigation**
*Autonomous Robots*, 5(1):111-125, March 1998 (article)