Schmidt, M., Kim, D., Sra, S.
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)
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Optimization for Machine Learning
pages: 494, Neural information processing series, MIT Press, Cambridge, MA, USA, December 2011 (book)
Barber, D., Cemgil, A., Chiappa, S.
Bayesian Time Series Models
pages: 432, Cambridge University Press, Cambridge, UK, August 2011 (book)
Kakade, S., von Luxburg, U.
JMLR Workshop and Conference Proceedings Volume 19: COLT 2011
pages: 834, MIT Press, Cambridge, MA, USA, 24th Annual Conference on Learning Theory , June 2011 (proceedings)
von Luxburg, U., Schölkopf, B.
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)
Peters, J., Tedrake, R., Roy, N., Morimoto, J.
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)
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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)
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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)
Lu, H., Schölkopf, B., Zhao, H.
Handbook of Statistical Bioinformatics
pages: 627, Springer Handbooks of Computational Statistics, Springer, Berlin, Germany, 2011 (book)
Rosas, P., Wichmann, F.
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)
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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)