About HIPS

In the HIPS group, we are interested in building intelligent algorithms. What makes a system intelligent? Our philosophy is that "intelligence" means making decisions under uncertainty, adapting to experience, and discovering structure in high-dimensional noisy data. The unifying theme for research in these areas is developing new approaches to statistical inference: uncovering the coherent structure that we cannot directly observe and using it for exploration and to make decisions or predictions. We develop new models for data, new tools for performing inference, and new computational structures for representing knowledge and uncertainty.

Selected Publications

Elliptical Slice Sampling. Murray, I, Adams RP, MacKay DJC.  Journal of Machine Learning Research: Workshop and Conference Proceedings (AISTATS). 9:541-548. 2010.   { arXiv:1001.0175 [stat.CO] | PDF | Code }
Learning the Structure of Deep Sparse Graphical Models. Adams, RP, Wallach HM, Ghahramani Z.  Journal of Machine Learning Research: Workshop and Conference Proceedings (AISTATS). 9:1-8. 2010.   { arXiv:1001.0160 [stat.ML] | PDF }