I am a Post Doc researcher in the Information Retrieval and Analysis Group. My current work involves applying machine learning techniques to information retrieval and information extraction problems. I am interested in learning to rank algorithms and also modeling user interactions with search engines. I am currently working on a project to model search queries and automatically extract entities/attributes from them. I work with Bayesian probabilistic models so that uncertainties can be consistently taken into account.
I was previously a PhD student of Zoubin Ghahramani, where my work was focused on Bayesian nonlinear regression models, in particular Gaussian processes and methods for applying them to large data sets. See my previous website for details and related code.
- John Guiver and Edward Snelson, Bayesian inference for Plackett-Luce ranking model, 17 June 2009
- John Guiver and Edward Snelson, Learning to Rank with SoftRank and Gaussian Processes, in SIGIR'08, Association for Computing Machinery, Inc., July 2008
- Onno Zoeter, Michael Taylor, Ed Snelson, John Guiver, Nick Craswell, and Martin Szummer, A Decision Theoretic Framework for Ranking using Implicit Feedback, in SIGIR 2008 Workshop on Learning to Rank for Information Retrieval, July 2008
- Joaquin Quiñonero Candela, Edward Snelson, and Oliver Williams, Sensible Priors for Sparse Bayesian Learning, no. MSR-TR-2007-121, September 2007
- Edward Snelson and Zoubin Ghahramani, Local and global sparse Gaussian process approximations, in Artificial Intelligence and Statistics 11 (AISTATS), 2007
- Edward Snelson, Flexible and efficient Gaussian process models for machine learning, Gatsby Computational Neuroscience Unit, University College London, 2007
- Edward Snelson and Zoubin Ghahramani, Variable noise and dimensionality reduction for sparse Gaussian processes, in Uncertainty in Artifical Intelligence 22 (UAI), 2006
- Edward Snelson and Zoubin Ghahramani, Sparse Gaussian Processes using Pseudo-inputs, in Neural Information Processing Systems 18 (NIPS), 2006
- Iain Murray and Edward Snelson, A pragmatic Bayesian approach to predictive uncertainty, in Machine Learning Challenges, Springer Verlag, 2006
- Edward Snelson and Zoubin Ghahramani, Compact Approximations to Bayesian Predictive Distributions, in Proceedings of the 22nd International Conference on Machine Learning (ICML), 2005
- Edward Snelson, Carl Edward Rasmussen, and Zoubin Ghahramani, Warped Gaussian processes, in Neural Information Processing Systems 16 (NIPS), 2004
