|Phone (external)||02(0)7 679 1879|
|Themes||Computational Statistics, Multivariate and High Dimensional Data|
Ricardo is a Lecturer at the Department of Statistical Science and Adjunct Faculty of the Gatsby Computational Neuroscience Unit. Prior to that, Ricardo got his PhD from the newly formed Machine Learning Department at Carnegie Mellon University in 2005. Ricardo also spent two years at the Gatsby Computational Neuroscience Unit as a Senior Research Fellow, and one year as a postdoctoral researcher at the Statistical Laboratory in Cambridge.
Multivariate analysis, graphical models, Bayesian inference, computational statistics, relational inference, data mining and causality.
- Silva R, Gramacy R. (2010). Gaussian process structural equation models with latent variables. Proceedings of the 26th Conference on Uncertainty on Artificial Intelligence, UAI 2010.
- Silva R, Heller K, Ghahramani Z, Airoldi R. (2010) Ranking relations using analogies in biological and information networks. Annals of Applied Statistics, 615-644.
- Silva R, Ghahramani Z. (2009). The hidden life of latent variables: Bayesian learning with mixed graph models. Journal of Machine Learning Research 10, 1187--1238.
- Silva R, Chu W, Ghahramani Z. (2007). Hidden common cause relations in relational learning. Neural Information Processing Systems, NIPS 2007.
- Silva R, Scheines R, Glymour C, Spirtes P. (2006). Learning the structure of linear latent variable models. Journal of Machine Learning Research 7(Feb):191--246, 2006