363 results
(View BibTeX file of all listed publications)

**ICA with Sparse Connections**
In *Intelligent Data Engineering and Automated Learning – IDEAL 2006*, pages: 530-537, (Editors: E Corchado and H Yin and V Botti und Colin Fyfe), Springer, 7th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2006, Lecture Notes in Computer Science, 2006, Volume 4224/2006 (inproceedings)

**How to choose the covariance for Gaussian process regression independently of the basis**
In *Proceedings of the Workshop Gaussian Processes in Practice*, Workshop Gaussian Processes in Practice (GPIP), 2006 (inproceedings)

**Learning operational space control**
In *Robotics: Science and Systems II (RSS 2006)*, pages: 255-262, (Editors: Gaurav S. Sukhatme and Stefan Schaal and Wolfram Burgard and Dieter Fox), Cambridge, MA: MIT Press, RSS , 2006, clmc (inproceedings)

**Reinforcement Learning for Parameterized Motor Primitives**
In *Proceedings of the 2006 International Joint Conference on Neural Networks*, pages: 73-80, IJCNN, 2006, clmc (inproceedings)

**The rate adapting poisson model for information retrieval and object recognition**
In *Proceedings of the 23rd international conference on Machine learning*, pages: 337-344, ICML ’06, ACM, New York, NY, USA, 2006 (inproceedings)

**Policy gradient methods for robotics**
In *Proceedings of the IEEE International Conference on Intelligent Robotics Systems*, pages: 2219-2225, IROS, 2006, clmc (inproceedings)

**Attentional Modulation of Auditory Event-Related Potentials in a Brain-Computer Interface**
In *BioCAS04*, (S3/5/INV- S3/17-20):4, IEEE Computer Society, Los Alamitos, CA, USA, 2004 IEEE International Workshop on Biomedical Circuits and Systems, December 2004 (inproceedings)

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)

**Using kernel PCA for Initialisation of Variational Bayesian Nonlinear Blind Source Separation Method**
In *ICA 2004*, pages: 790-797, (Editors: Puntonet, C. G., A. Prieto), Springer, Berlin, Germany, Fifth International Conference on Independent Component Analysis and Blind Signal Separation, October 2004 (inproceedings)

**Robust ICA for Super-Gaussian Sources**
In *ICA 2004*, pages: 217-224, (Editors: Puntonet, C. G., A. Prieto), Springer, Berlin, Germany, Fifth International Conference on Independent Component Analysis and Blind Signal Separation, October 2004 (inproceedings)

**Modelling Spikes with Mixtures of Factor Analysers**
In *Pattern Recognition*, pages: 391-398, LNCS 3175, (Editors: Rasmussen, C. E. , H.H. Bülthoff, B. Schölkopf, M.A. Giese), Springer, Berlin, Germany, 26th DAGM Symposium, September 2004 (inproceedings)

**Learning Depth From Stereo**
In *26th DAGM Symposium*, pages: 245-252, LNCS 3175, (Editors: Rasmussen, C. E., H. H. Bülthoff, B. Schölkopf, M. A. Giese), Springer, Berlin, Germany, 26th DAGM Symposium, September 2004 (inproceedings)

**Grundlagen von Support Vector Maschinen und Anwendungen in der Bildverarbeitung**
September 2004 (talk)

**Stability of Hausdorff-based Distance Measures**
In *VIIP*, pages: 1-6, VIIP, September 2004 (inproceedings)

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

**Learning to Find Graph Pre-Images**
In *Pattern Recognition*, pages: 253-261, (Editors: Rasmussen, C. E., H. H. Bülthoff, B. Schölkopf, M. A. Giese), Springer, Berlin, Germany, 26th DAGM Symposium, August 2004 (inproceedings)

**Gaussian Process Classification for Segmenting and Annotating Sequences**
In *Proceedings of the 21st International Conference on Machine Learning (ICML 2004)*, pages: 25-32, (Editors: Greiner, R. , D. Schuurmans), ACM Press, New York, USA, 21st International Conference on Machine Learning (ICML), July 2004 (inproceedings)

**Learning with Non-Positive Kernels**
In *ICML 2004*, pages: 81-81, ACM Press, New York, NY, USA, Twenty-First International Conference on Machine Learning, July 2004 (inproceedings)

**Exponential Families for Conditional Random Fields**
In *Proceedings of the 20th Annual Conference on Uncertainty in Artificial Intelligence (UAI 2004)*, pages: 2-9, (Editors: Chickering, D.M. , J.Y. Halpern), Morgan Kaufmann, San Francisco, CA, USA, 20th Annual Conference on Uncertainty in Artificial Intelligence (UAI), July 2004 (inproceedings)

**Using Conditional Random Fields to Predict Pitch Accent in Conversational Speech**
In pages: 677-684, (Editors: Scott, D. , W. Daelemans, M. Walker), ACL, East Stroudsburg, PA, USA, 42nd Annual Meeting of the Association for Computational Linguistics (ACL), July 2004 (inproceedings)

**Support vector machine learning for interdependent and structured output spaces**
In pages: 1-8, (Editors: Greiner, R. , D. Schuurmans), AAAI Press, Menlo Park, CA, USA, Twenty-first International Conference on Machine Learning (ICML), July 2004 (inproceedings)

**PAC-Bayesian Generic Chaining**
In *Advances in Neural Information Processing Systems 16*, pages: 1125-1132 , (Editors: Thrun, S., L.K. Saul, B. Schölkopf), MIT Press, Cambridge, MA, USA, Seventeenth Annual Conference on Neural Information Processing Systems (NIPS), June 2004 (inproceedings)

**Prediction on Spike Data Using Kernel Algorithms**
In *Advances in Neural Information Processing Systems 16*, pages: 1367-1374, (Editors: S Thrun and LK Saul and B Schölkopf), MIT Press, Cambridge, MA, USA, 17th Annual Conference on Neural Information Processing Systems (NIPS), June 2004 (inproceedings)

**Warped Gaussian Processes**
In *Advances in Neural Information Processing Systems 16*, pages: 337-344, (Editors: Thrun, S., L.K. Saul, B. Schölkopf), MIT Press, Cambridge, MA, USA, Seventeenth Annual Conference on Neural Information Processing Systems (NIPS), June 2004 (inproceedings)

**Ranking on Data Manifolds**
In *Advances in neural information processing systems 16*, pages: 169-176, (Editors: S Thrun and L Saul and B Schölkopf), MIT Press, Cambridge, MA, USA, 17th Annual Conference on Neural Information Processing Systems (NIPS), June 2004 (inproceedings)

**Gaussian Processes in Reinforcement Learning**
In *Advances in Neural Information Processing Systems 16*, pages: 751-759, (Editors: Thrun, S., L. K. Saul, B. Schölkopf), MIT Press, Cambridge, MA, USA, Seventeenth Annual Conference on Neural Information Processing Systems (NIPS), June 2004 (inproceedings)

**Learning with Local and Global Consistency**
In *Advances in Neural Information Processing Systems 16*, pages: 321-328, (Editors: S Thrun and LK Saul and B Schölkopf), MIT Press, Cambridge, MA, USA, 17th Annual Conference on Neural Information Processing Systems (NIPS), June 2004 (inproceedings)

**Learning to Find Pre-Images**
In *Advances in Neural Information Processing Systems 16*, pages: 449-456, (Editors: S Thrun and LK Saul and B Schölkopf), MIT Press, Cambridge, MA, USA, 17th Annual Conference on Neural Information Processing Systems (NIPS), June 2004 (inproceedings)

**Measure Based Regularization**
In *Advances in Neural Information Processing Systems 16*, pages: 1221-1228, (Editors: Thrun, S., L. Saul, B. Schölkopf), MIT Press, Cambridge, MA, USA, Seventeenth Annual Conference on Neural Information Processing Systems (NIPS), June 2004 (inproceedings)

**Insights from Machine Learning Applied to Human Visual Classification**
In *Advances in Neural Information Processing Systems 16*, pages: 905-912, (Editors: Thrun, S., L. Saul, B. Schölkopf), MIT Press, Cambridge, MA, USA, Seventeenth Annual Conference on Neural Information Processing Systems (NIPS), June 2004 (inproceedings)

**Image Construction by Linear Programming**
In *Advances in Neural Information Processing Systems 16*, pages: 57-64, (Editors: Thrun, S., L.K. Saul, B. Schölkopf), MIT Press, Cambridge, MA, USA, Seventeenth Annual Conference on Neural Information Processing Systems (NIPS), June 2004 (inproceedings)

**Semi-Supervised Protein Classification using Cluster Kernels**
In *Advances in Neural Information Processing Systems 16*, pages: 595-602, (Editors: Thrun, S., L.K. Saul, B. Schölkopf), MIT Press, Cambridge, MA, USA, Seventeenth Annual Conference on Neural Information Processing Systems (NIPS), June 2004 (inproceedings)

**Kernel Hebbian Algorithm for single-frame super-resolution**
In *Computer Vision - ECCV 2004, LNCS vol. 3024*, pages: 135-149, (Editors: A Leonardis and H Bischof), Springer, Berlin, Germany, 8th European Conference on Computer Vision (ECCV), May 2004 (inproceedings)

**Pattern Selection for SVM based "Futures Trading System"**
In *Proc. of the Korean Data Mining Conference*, pages: 175-183, Korean Data Mining Society Conference, April 2004 (inproceedings)

**Minimum Sum-Squared Residue based clustering of Gene Expression Data**
In *SIAM Data Mining*, pages: 00-00, SDM, April 2004 (inproceedings)

**Preservation of Neighborhood Relation under Input to Feature Space Mapping in SVM Training**
In *Proc. of the 33rd International Conference on Computers and Industrial Engineering (C&IE 2004)*, pages: 1-10, the 33rd International Conference on Computers and Industrial Engineering (C&IE), April 2004, in CD (inproceedings)

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

**Unifying Colloborative and Content-Based Filtering.**
In *ACM International Conference Proceeding Series*, pages: 65 , (Editors: Greiner, R. , D. Schuurmans), ACM Press, New York, USA, ICLM, 2004 (inproceedings)

**Clustering Protein Sequence and Structure Space with Infinite Gaussian Mixture Models**
In *Pacific Symposium on Biocomputing 2004; Vol. 9*, pages: 399-410, World Scientific Publishing, Singapore, Pacific Symposium on Biocomputing, 2004 (inproceedings)

**Efficient Approximations for Support Vector Machines in Object Detection**
In *DAGM 2004*, pages: 54-61, (Editors: CE Rasmussen and HH Bülthoff and B Schölkopf and MA Giese), Springer, Berlin, Germany, Pattern Recognition, Proceedings of the 26th DAGM Symposium, 2004 (inproceedings)

**Kernel Methods for Manifold Estimation**
In *Proceedings in Computational Statistics*, pages: 441-452, (Editors: J Antoch), Physica-Verlag/Springer, Heidelberg, Germany, COMPSTAT, 2004 (inproceedings)

**A Regularization Framework for Learningfrom Graph Data**
In *ICML Workshop on Statistical Relational Learning and Its Connections to Other Fields*, pages: 132-137, ICML, 2004 (inproceedings)

**A kernel view of the dimensionality reduction of manifolds**
In *Proceedings of the Twenty-First International Conference on Machine Learning*, pages: 369-376, (Editors: CE Brodley), ACM, New York, NY, USA, ICML, 2004, also appeared as MPI-TR 110 (inproceedings)

**Protein Functional Class Prediction with a Combined Graph**
In *Proceedings of the Korean Data Mining Conference*, pages: 200-219, Proceedings of the Korean Data Mining Conference, 2004 (inproceedings)

**Learning from Labeled and Unlabeled Data Using Random Walks**
In *Pattern Recognition, Proceedings of the 26th DAGM Symposium*, pages: 237-244, (Editors: Rasmussen, C.E., H.H. Bülthoff, M.A. Giese and B. Schölkopf), Pattern Recognition, Proceedings of the 26th DAGM Symposium, 2004 (inproceedings)

**Multivariate Regression via Stiefel Manifold Constraints**
In *Lecture Notes in Computer Science, Vol. 3175*, pages: 262-269, (Editors: CE Rasmussen and HH Bülthoff and B Schölkopf and MA Giese), Springer, Berlin, Germany, Pattern Recognition, Proceedings of the 26th DAGM Symposium, 2004 (inproceedings)