I am a post-doctoral researcher in the Machine Learning and Perception (MLP) group at Microsoft Research, Cambridge, UK.
My research focuses on structured prediction problems. Often, if we want to predict the outcome of multiple random variables at the same time, we will find that these variables are correlated. In order to make a good decision, these correlations have to be taken into account.
I develop methods that are based on statistical principles and apply them to real-world problems. At present, I work on low-level vision and image processing. In the past, I have also worked on speech and language processing, and I maintain an active interest in the topic.
Please see my private website for further information and for publications prior to joining Microsoft Research.
- Jeremy Jancsary, Sebastian Nowozin, and Carsten Rother, Learning Convex QP Relaxations for Structured Prediction, in 30th International Conference on Machine Learning (ICML), June 2013
- Uwe Schmidt, Carsten Rother, Sebastian Nowozin, Jeremy Jancsary, and Stefan Roth, Discriminative Non-blind Deblurring, in 2013 Conference on Computer Vision and Pattern Recognition (CVPR 2013), IEEE Computer Society, 20 April 2013
- Jeremy Jancsary, Sebastian Nowozin, and Carsten Rother, Non-parametric CRFs for Image Labeling, in NIPS Workshop on Modern Nonparametric Methods in Machine Learning, December 2012
- Jeremy Jancsary, Sebastian Nowozin, and Carsten Rother, Loss-Specific Training of Non-Parametric Image Restoration Models: A New State of the Art, in 12th European Conference on Computer Vision, Springer, 2 August 2012
- Jeremy Jancsary, Sebastian Nowozin, Toby Sharp, and Carsten Rother, Regression Tree Fields - An Efficient, Non-parametric Approach to Image Labeling Problems, in IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), IEEE Computer Society, 10 April 2012