20 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)

**Special Issue on Causal Discovery and Inference**
*ACM Transactions on Intelligent Systems and Technology (TIST)*, 7(2), January 2016, (Guest Editors) (misc)

**Empirical Inference (2010-2015)**
Scientific Advisory Board Report, 2016 (misc)

**Unsupervised Domain Adaptation in the Wild : Dealing with Asymmetric Label Set**
2016 (misc)

**Screening Rules for Convex Problems**
2016 (unpublished) Submitted

**Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik**
Springer, 2013 (book)

**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)

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

**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)

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

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

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

**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)