45 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)

**BCPy2000**
Workshop "Machine Learning Open-Source Software" at NIPS, December 2008 (talk)

**Logistic Regression for Graph Classification**
NIPS Workshop on "Structured Input - Structured Output" (NIPS SISO), December 2008 (talk)

**New Projected Quasi-Newton Methods with Applications**
Microsoft Research Tech-talk, December 2008 (talk)

**MR-Based PET Attenuation Correction: Initial Results for Whole Body**
Medical Imaging Conference, October 2008 (talk)

**Nonparametric Indepedence Tests: Space Partitioning and Kernel Approaches**
19th International Conference on Algorithmic Learning Theory (ALT08), October 2008 (talk)

**Data-driven goodness-of-fit tests**
2008 Barcelona Conference on Asymptotic Statistics (BAS), September 2008 (talk)

**mGene: A Novel Discriminative Gene Finder**
Worm Genomics and Systems Biology meeting, July 2008 (talk)

**Discovering Common Sequence Variation in
Arabidopsis thaliana**
16th Annual International Conference Intelligent Systems for Molecular Biology (ISMB), July 2008 (talk)

**Coding Theory in Brain-Computer Interfaces**
Soria Summerschool on Computational Mathematics "Algebraic Coding Theory" (S3CM), July 2008 (talk)

**Motor Skill Learning for Cognitive Robotics**
6th International Cognitive Robotics Workshop (CogRob), July 2008 (talk)

**Painless Embeddings of Distributions: the Function Space View (Part 1)**
25th International Conference on Machine Learning (ICML), July 2008 (talk)

**Reinforcement Learning for Robotics**
8th European Workshop on Reinforcement Learning for Robotics (EWRL), July 2008 (talk)

**Multi-Classification by Categorical Features via Clustering**
25th International Conference on Machine Learning (ICML), June 2008 (talk)

**Thin-Plate Splines Between Riemannian Manifolds**
Workshop on Geometry and Statistics of Shapes, June 2008 (talk)

**Machine Learning for Robotics: Learning Methods for Robot Motor Skills**
pages: 107 , (Editors: J Peters), VDM-Verlag, Saarbrücken, Germany, May 2008 (book)

**Learning resolved velocity control**
2008 IEEE International Conference on Robotics and Automation (ICRA), May 2008 (talk)

**Bayesian methods for protein structure determination**
Machine Learning in Structural Bioinformatics, April 2008 (talk)

**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)

**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)

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

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

**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)

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

**Advances in Kernel Methods - Support Vector Learning**
MIT Press, Cambridge, MA, 1999 (book)

**Support vector learning**
pages: 173, Oldenbourg, München, Germany, 1997, Zugl.: Berlin, Techn. Univ., Diss., 1997 (book)