57 results
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**Projected Newton-type methods in machine learning**
In *Optimization for Machine Learning*, pages: 305-330, (Editors: Sra, S., Nowozin, S. and Wright, S. J.), MIT Press, Cambridge, MA, USA, December 2011 (inbook)

**Optimization for Machine Learning**
pages: 494, Neural information processing series, MIT Press, Cambridge, MA, USA, December 2011 (book)

**Bayesian Time Series Models**
pages: 432, Cambridge University Press, Cambridge, UK, August 2011 (book)

**Statistical Learning Theory: Models, Concepts, and Results**
In *Handbook of the History of Logic, Vol. 10: Inductive Logic*, 10, pages: 651-706, (Editors: Gabbay, D. M., Hartmann, S. and Woods, J. H.), Elsevier North Holland, Amsterdam, Netherlands, May 2011 (inbook)

**PAC-Bayesian Analysis of Martingales and Multiarmed Bandits **
Max Planck Institute for Biological Cybernetics, Tübingen, Germany, May 2011 (techreport)

**Non-stationary Correction of Optical Aberrations**
(1), Max Planck Institute for Intelligent Systems, Tübingen, Germany, May 2011 (techreport)

**Multiple Kernel Learning: A Unifying Probabilistic Viewpoint**
Max Planck Institute for Biological Cybernetics, March 2011 (techreport)

**Multiple testing, uncertainty and realistic pictures**
(2011-004), EURANDOM, Technische Universiteit Eindhoven, January 2011 (techreport)

**Robot Learning**
In *Encyclopedia of Machine Learning*, pages: 865-869, Encyclopedia of machine learning, (Editors: Sammut, C. and Webb, G. I.), Springer, New York, NY, USA, January 2011 (inbook)

**What You Expect Is What You Get? Potential Use of Contingent Negative Variation for Passive BCI Systems in Gaze-Based HCI**
In *Affective Computing and Intelligent Interaction*, 6975, pages: 447-456, Lecture Notes in Computer Science, (Editors: D’Mello, S., Graesser, A., Schuller, B. and Martin, J.-C.), Springer, Berlin, Germany, 2011 (inbook)

**Kernel Methods in Bioinformatics **
In *Handbook of Statistical Bioinformatics*, pages: 317-334, Springer Handbooks of Computational Statistics ; 3, (Editors: Lu, H.H.-S., Schölkopf, B. and Zhao, H.), Springer, Berlin, Germany, 2011 (inbook)

**Handbook of Statistical Bioinformatics**
pages: 627, Springer Handbooks of Computational Statistics, Springer, Berlin, Germany, 2011 (book)

**Cue Combination: Beyond Optimality**
In *Sensory Cue Integration*, pages: 144-152, (Editors: Trommershäuser, J., Körding, K. and Landy, M. S.), Oxford University Press, 2011 (inbook)

**Nonconvex proximal splitting: batch and incremental algorithms**
(2), Max Planck Institute for Intelligent Systems, Tübingen, Germany, 2011 (techreport)

**Bayesian Estimators for Robins-Ritovs Problem**
(EDI-INF-RR-1189), School of Informatics, University of Edinburgh, October 2007 (techreport)

**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)

**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)

**Learning with Transformation Invariant Kernels**
(165), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, September 2007 (techreport)

**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)

**Scalable Semidefinite Programming using Convex Perturbations**
(TR-07-47), University of Texas, Austin, TX, USA, September 2007 (techreport)

**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)

**Sparse Multiscale Gaussian Process Regression**
(162), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, August 2007 (techreport)

**Efficient Subwindow Search for Object Localization**
(164), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, August 2007 (techreport)

**Cluster Identification in Nearest-Neighbor Graphs**
(163), Max-Planck-Institute for Biological Cybernetics, Tübingen, Germany, May 2007 (techreport)

**Exploring model selection techniques for nonlinear dimensionality reduction**
(EDI-INF-RR-0960), School of Informatics, University of Edinburgh, March 2007 (techreport)

**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)

**Dirichlet Mixtures of Bayesian Linear Gaussian State-Space Models: a Variational Approach**
(161), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, March 2007 (techreport)

**Modeling data using directional distributions: Part II**
(TR-07-05), University of Texas, Austin, TX, USA, February 2007 (techreport)

**Automatic 3D Face Reconstruction from Single Images or Video**
(160), Max Planck Institute for Biological Cybernetics, Tübingen, Germany, February 2007 (techreport)

**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)

**Mathematik der Wahrnehmung: Wendepunkte**
*Akademische Mitteilungen zw{\"o}lf: F{\"u}nf Sinne*, pages: 32-37, 2007 (misc)

**Relative Entropy Policy Search**
*CLMC Technical Report: TR-CLMC-2007-2*, Computational Learning and Motor Control Lab, Los Angeles, CA, 2007, clmc (techreport)

**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)

**Kernel Dependency Estimation**
(98), Max Planck Institute for Biological Cybernetics, August 2002 (techreport)

**Global Geometry of SVM Classifiers**
Max Planck Institute for Biological Cybernetics, Tübingen, Germany, June 2002 (techreport)

**Computationally Efficient Face Detection**
(MSR-TR-2002-69), Microsoft Research, June 2002 (techreport)

**Kernel-based nonlinear blind source separation**
EU-Project BLISS, January 2002 (techreport)

**A compression approach to support vector model selection**
(101), Max Planck Institute for Biological Cybernetics, 2002, see more detailed JMLR version (techreport)

**Feature Selection and Transduction for Prediction of Molecular Bioactivity for Drug Design**
Max Planck Institute for Biological Cybernetics / Biowulf Technologies, 2002 (techreport)

**Observations on the Nyström Method for Gaussian Process Prediction**
Max Planck Institute for Biological Cybernetics, Tübingen, Germany, 2002 (techreport)

**Kernel principal component analysis.**
In *Advances in Kernel Methods—Support Vector Learning*, pages: 327-352, (Editors: B Schölkopf and CJC Burges and AJ Smola), MIT Press, Cambridge, MA, 1999 (inbook)

**Estimating the support of a high-dimensional distribution**
(MSR-TR-99-87), Microsoft Research, 1999 (techreport)