56 results
(View BibTeX file of all listed publications)

**Reaction graph kernels for discovering missing enzymes in the plant secondary metabolism**
NIPS Workshop on Machine Learning in Computational Biology, December 2007 (talk)

**Positional Oligomer Importance Matrices**
NIPS Workshop on Machine Learning in Computational Biology, December 2007 (talk)

**Machine Learning Algorithms for Polymorphism Detection**
NIPS Workshop on Machine Learning in Computational Biology, December 2007 (talk)

**An Automated Combination of Kernels for Predicting Protein Subcellular Localization**
NIPS Workshop on Machine Learning in Computational Biology, December 2007 (talk)

**Challenges in Brain-Computer Interface Development: Induction, Measurement, Decoding, Integration**
Invited keynote talk at the launch of BrainGain, the Dutch BCI research consortium, November 2007 (talk)

**Policy Learning for Robotics**
14th International Conference on Neural Information Processing (ICONIP), November 2007 (talk)

**Hilbert Space Representations of Probability Distributions**
2nd Workshop on Machine Learning and Optimization at the ISM, October 2007 (talk)

**Regression with Intervals**
International Workshop on Data-Mining and Statistical Science (DMSS2007), October 2007, JSAI Incentive Award. Talk was given by Hisashi Kashima. (talk)

**Support Vector Machine Learning for Interdependent and Structured Output Spaces**
In *Predicting Structured Data*, pages: 85-104, Advances in neural information processing systems, (Editors: Bakir, G. H. , T. Hofmann, B. Schölkopf, A. J. Smola, B. Taskar, S. V. N. Vishwanathan), MIT Press, Cambridge, MA, USA, September 2007 (inbook)

**Brisk Kernel ICA**
In *Large Scale Kernel Machines*, pages: 225-250, Neural Information Processing, (Editors: Bottou, L. , O. Chapelle, D. DeCoste, J. Weston), MIT Press, Cambridge, MA, USA, September 2007 (inbook)

**MR-Based PET Attenuation Correction: Method and Validation**
Joint Molecular Imaging Conference, September 2007 (talk)

**Predicting Structured Data**
pages: 360, Advances in neural information processing systems, MIT Press, Cambridge, MA, USA, September 2007 (book)

**Training a Support Vector Machine in the Primal**
In *Large Scale Kernel Machines*, pages: 29-50, Neural Information Processing, (Editors: Bottou, L. , O. Chapelle, D. DeCoste, J. Weston), MIT Press, Cambridge, MA, USA, September 2007, This is a slightly updated version of the Neural Computation paper (inbook)

**Approximation Methods for Gaussian Process Regression**
In *Large-Scale Kernel Machines*, pages: 203-223, Neural Information Processing, (Editors: Bottou, L. , O. Chapelle, D. DeCoste, J. Weston), MIT Press, Cambridge, MA, USA, September 2007 (inbook)

**Large-Scale Kernel Machines**
pages: 416, Neural Information Processing Series, MIT Press, Cambridge, MA, USA, September 2007 (book)

**Density Estimation of Structured Outputs in Reproducing Kernel Hilbert Spaces**
In *Predicting Structured Data*, pages: 283-300, Advances in neural information processing systems, (Editors: BakIr, G. H., T. Hofmann, B. Schölkopf, A. J. Smola, B. Taskar, S. V.N. Vishwanathan), MIT Press, Cambridge, MA, USA, September 2007 (inbook)

**Trading Convexity for Scalability**
In *Large Scale Kernel Machines*, pages: 275-300, Neural Information Processing, (Editors: Bottou, L. , O. Chapelle, D. DeCoste, J. Weston), MIT Press, Cambridge, MA, USA, September 2007 (inbook)

**Bayesian methods for NMR structure determination**
29th Annual Discussion Meeting: Magnetic Resonance in Biophysical Chemistry, September 2007 (talk)

**Classifying Event-Related Desynchronization in EEG, ECoG and MEG signals**
In *Toward Brain-Computer Interfacing*, pages: 235-260, Neural Information Processing, (Editors: G Dornhege and J del R Millán and T Hinterberger and DJ McFarland and K-R Müller), MIT Press, Cambridge, MA, USA, September 2007 (inbook)

**Joint Kernel Maps**
In *Predicting Structured Data*, pages: 67-84, Advances in neural information processing systems, (Editors: GH Bakir and T Hofmann and B Schölkopf and AJ Smola and B Taskar and SVN Vishwanathan), MIT Press, Cambridge, MA, USA, September 2007 (inbook)

**Brain-Computer Interfaces for Communication in Paralysis: A Clinical Experimental Approach**
In *Toward Brain-Computer Interfacing*, pages: 43-64, Neural Information Processing, (Editors: G. Dornhege and J del R Millán and T Hinterberger and DJ McFarland and K-R Müller), MIT Press, Cambridge, MA, USA, September 2007 (inbook)

**Collaborative Filtering via Ensembles of Matrix Factorizations**
KDD Cup and Workshop, August 2007 (talk)

**Thinking Out Loud: Research and Development of Brain Computer Interfaces**
Invited keynote talk at the Max Planck Society‘s PhDNet Workshop., July 2007 (talk)

**Local Learning Algorithms for Transductive Classification, Clustering and Data Projection**
Yahoo Inc., July 2007 (talk)

**Dirichlet Process Mixtures of Factor Analysers**
Fifth Workshop on Bayesian Inference in Stochastic Processes (BSP5), June 2007 (talk)

**New BCI approaches: Selective Attention to Auditory and Tactile Stimulus Streams**
Invited talk at the PASCAL Workshop on Methods of Data Analysis in Computational Neuroscience and Brain Computer Interfaces, June 2007 (talk)

**Towards Motor Skill Learning in Robotics**
Interactive Robot Learning - RSS workshop, June 2007 (talk)

**Transductive Support Vector Machines for Structured Variables**
International Conference on Machine Learning (ICML), June 2007 (talk)

**Impact of target-to-target interval on classification performance in the P300 speller**
Scientific Meeting "Applied Neuroscience for Healthy Brain Function", May 2007 (talk)

Peters, J.
**Benchmarking of Policy Gradient Methods**
ADPRL Workshop, April 2007 (talk)

**Probabilistic Structure Calculation**
In *Structure and Biophysics: New Technologies for Current Challenges in Biology and Beyond*, pages: 81-98, NATO Security through Science Series, (Editors: Puglisi, J. D.), Springer, Berlin, Germany, March 2007 (inbook)

**New Margin- and Evidence-Based Approaches for EEG Signal Classification**
Invited talk at the FaSor Jahressymposium, February 2007 (talk)

**On the Pre-Image Problem in Kernel Methods**
In *Kernel Methods in Bioengineering, Signal and Image Processing*, pages: 284-302, (Editors: G Camps-Valls and JL Rojo-Álvarez and M Martínez-Ramón), Idea Group Publishing, Hershey, PA, USA, January 2007 (inbook)

**Some comments on ν-SVM**
In *A tribute to Antonio Lepschy*, pages: -, (Editors: Picci, G. , M. E. Valcher), Edizione Libreria Progetto, Padova, Italy, 2007 (inbook)

**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)

**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)

**Extracting egomotion from optic flow: limits of accuracy and neural matched filters**
In pages: 143-168, Springer, Berlin, 2001 (inbook)

**Robust ensemble learning**
In *Advances in Large Margin Classifiers*, pages: 207-220, Neural Information Processing Series, (Editors: AJ Smola and PJ Bartlett and B Schölkopf and D. Schuurmans), MIT Press, Cambridge, MA, USA, October 2000 (inbook)

**Entropy numbers for convex combinations and MLPs**
In *Advances in Large Margin Classifiers*, pages: 369-387, Neural Information Processing Series, (Editors: AJ Smola and PL Bartlett and B Schölkopf and D Schuurmans), MIT Press, Cambridge, MA,, October 2000 (inbook)