Professor Yee Whye Teh

Professor of Statistical Machine Learning

University Lecturer in Statistics
Fellow of  University College

+44 (0)1865 285388 (Direct)

Biographical sketch

Prior to joining Oxford, I was a Lecturer then Reader of Computational Statistics and Machine Learning at the Gatsby Neuroscience Unit, UCL from 2007 to 2012.  I obtained my PhD in Computer Science at the University of Toronto in 2003.  This was followed by two years as a postdoctoral fellow at University of California, Berkeley, then as Lee Kuan Yew Postdoctoral Fellow at the National University of Singapore.

I am interested in developing Bayesian statistical methods to address large and complex problems in science and engineering. Current application domains include unsupervised learning, computational linguistics and statistical genetics. I am particularly interested in Bayesian nonparametric modelling and efficient computational approaches to inference and learning in probabilistic models. 

Selected publications
Modelling Genetic Variations using Fragmentation-Coagulation Processes.  Y. W. Teh, C. Blundell and L. T. Elliott. Advances in Neural Information Processing Systems (NIPS) 2011.

Hierarchical Bayesian Nonparametric Models with Applications. Y.W. Teh and M.I. Jordan. Bayesian Nonparametrics, 2010. Cambridge University Press.

The Sequence Memoizer.  F. Wood, C. Archambeau, J. Gasthaus, L. F. James and Y.W. Teh. Communications of the ACM, 54(2):91-98, Feb 2011.

Hierarchical Dirichlet Processes. Y.W. Teh, M.I. Jordan, M.J. Beal and D.M. Blei. Journal of the American Statistical Association 101(476):1566-1581, 2006.

A Fast Learning Algorithm For Deep Belief Networks. G.E. Hinton, S. Osindero and Y.W. Teh. Neural Computation 18(7):1527-1554, 2006.

A Hierarchical Bayesian Language Model based on Pitman-Yor Processes. Y.W. Teh. Proceedings of the Conference on Computational Linguistics and Annual Meeting of the Association for Computational Linguistics, 2006.

List of publications

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