44 results
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**Maschinelles Lernen: Entwicklung ohne Grenzen?**
In *Mit Optimismus in die Zukunft schauen. Künstliche Intelligenz - Chancen und Rahmenbedingungen*, pages: 26-34, (Editors: Bender, G. and Herbrich, R. and Siebenhaar, K.), B&S Siebenhaar Verlag, 2018 (incollection)

**Methods in Psychophysics**
In *Stevens’ Handbook of Experimental Psychology and Cognitive Neuroscience*, 5 (Methodology), 7, 4th, John Wiley & Sons, Inc., 2018 (inbook)

**Transfer Learning for BCIs**
In *Brain–Computer Interfaces Handbook*, pages: 425-442, 22, (Editors: Chang S. Nam, Anton Nijholt and Fabien Lotte), CRC Press, 2018 (incollection)

**A New Projected Quasi-Newton Approach for the Nonnegative Least Squares Problem**
(TR-06-54), Univ. of Texas, Austin, December 2006 (techreport)

**Probabilistic inference for solving (PO)MDPs**
(934), School of Informatics, University of Edinburgh, December 2006 (techreport)

**Minimal Logical Constraint Covering Sets**
(155), Max Planck Institute for Biological Cybernetics, Tübingen, December 2006 (techreport)

**Prediction of Protein Function from Networks**
In *Semi-Supervised Learning*, pages: 361-376, Adaptive Computation and Machine Learning, (Editors: Chapelle, O. , B. Schölkopf, A. Zien), MIT Press, Cambridge, MA, USA, November 2006 (inbook)

**Discrete Regularization**
In *Semi-supervised Learning*, pages: 237-250, Adaptive computation and machine learning, (Editors: O Chapelle and B Schölkopf and A Zien), MIT Press, Cambridge, MA, USA, November 2006 (inbook)

**New Methods for the P300 Visual Speller**
(1), (Editors: Hill, J. ), Max-Planck Institute for Biological Cybernetics, Tübingen, Germany, November 2006 (techreport)

**Geometric Analysis of Hilbert Schmidt Independence criterion based ICA contrast function**
(PA006080), National ICT Australia, Canberra, Australia, October 2006 (techreport)

**Semi-Supervised Learning**
pages: 508, Adaptive computation and machine learning, MIT Press, Cambridge, MA, USA, September 2006 (book)

**A tutorial on spectral clustering**
(149), Max Planck Institute for Biological Cybernetics, Tübingen, August 2006 (techreport)

**Towards the Inference of Graphs on Ordered Vertexes**
(150), Max Planck Institute for Biological Cybernetics, Tübingen, August 2006 (techreport)

**Nonnegative Matrix Approximation: Algorithms and Applications**
Univ. of Texas, Austin, May 2006 (techreport)

**An Automated Combination of Sequence Motif Kernels for Predicting Protein Subcellular Localization**
(146), Max Planck Institute for Biological Cybernetics, Tübingen, April 2006 (techreport)

**Training a Support Vector Machine in the Primal**
(147), Max Planck Institute for Biological Cybernetics, Tübingen, April 2006, The version in the "Large Scale Kernel Machines" book is more up to date. (techreport)

**Cross-Validation Optimization for Structured Hessian Kernel Methods**
Max-Planck Institute for Biological Cybernetics, Tübingen, Germany, February 2006 (techreport)

**Gaussian Processes for Machine Learning**
pages: 248, Adaptive Computation and Machine Learning, MIT Press, Cambridge, MA, USA, January 2006 (book)

**Combining a Filter Method with SVMs**
In *Feature Extraction: Foundations and Applications, Studies in Fuzziness and Soft Computing, Vol. 207*, pages: 439-446, Studies in Fuzziness and Soft Computing ; 207, (Editors: I Guyon and M Nikravesh and S Gunn and LA Zadeh), Springer, Berlin, Germany, 2006 (inbook)

**Embedded methods**
In *Feature Extraction: Foundations and Applications*, pages: 137-165, Studies in Fuzziness and Soft Computing ; 207, (Editors: Guyon, I. , S. Gunn, M. Nikravesh, L. A. Zadeh), Springer, Berlin, Germany, 2006 (inbook)

**Implicit Wiener Series, Part II: Regularised estimation**
(148), Max Planck Institute, 2006 (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)

**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)

**Natural Regularization from Generative Models**
In *Advances in Large Margin Classifiers*, pages: 51-60, Neural Information Processing Series, (Editors: AJ Smola and PJ Bartlett and B Schölkopf and D Schuurmans), MIT Press, Cambridge, MA, USA, October 2000 (inbook)

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

**Solving Satisfiability Problems with Genetic Algorithms**
In *Genetic Algorithms and Genetic Programming at Stanford 2000*, pages: 206-213, (Editors: Koza, J. R.), Stanford Bookstore, Stanford, CA, USA, June 2000 (inbook)

**Statistical Learning and Kernel Methods**
In *CISM Courses and Lectures, International Centre for Mechanical Sciences Vol.431*, *CISM Courses and Lectures, International Centre for
Mechanical Sciences*, 431(23):3-24, (Editors: G Della Riccia and H-J Lenz and R Kruse), Springer, Vienna, Data Fusion and Perception, 2000 (inbook)

**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)

**The Kernel Trick for Distances**
(MSR-TR-2000-51), Microsoft Research, Redmond, WA, USA, 2000 (techreport)

**Kernel method for percentile feature extraction**
(MSR-TR-2000-22), Microsoft Research, 2000 (techreport)

**Generalization bounds and learning rates for Regularized principal manifolds**
NeuroCOLT, 1998, NeuroColt2-TR 1998-027 (techreport)

**Generalization Bounds for Convex Combinations of Kernel Functions**
Royal Holloway College, 1998 (techreport)

**Generalization Performance of Regularization Networks and Support Vector Machines via Entropy
Numbers of Compact Operators**
(19), NeuroCOLT, 1998, Accepted for publication in IEEE Transactions on Information Theory (techreport)

**Quantization Functionals and Regularized PrincipalManifolds**
NeuroCOLT, 1998, NC2-TR-1998-028 (techreport)

**Support-Vektor-Lernen**
In *Ausgezeichnete Informatikdissertationen 1997*, pages: 135-150, (Editors: G Hotz and H Fiedler and P Gorny and W Grass and S Hölldobler and IO Kerner and R Reischuk), Teubner Verlag, Stuttgart, 1998 (inbook)

**Support Vector Machine Reference Manual**
(CSD-TR-98-03), Department of Computer Science, Royal Holloway, University of London, 1998 (techreport)