Workshop Big data in biomedicine. Big models? University of Warwick

Most statistical methods learn from data using probability models. Now that data has grown to become "big data" and the complexity of the inference is also bigger, should our models grow? If so, which of the old lessons still apply and which need to be revised? The aim of the workshop is to provide a forum to discuss recent statistical modelling strategies to solve complex problems, with a focus on biomedicine, Bayesian methods and high-dimensional inference. Some specifics topics of interest are:

- Prior choice: objective approaches, model separation and the value of informative priors

- High-dimensional model selection, including graphical models and correlated data

- Bayesian non-parametrics

- Bioinformatics and medical applications

 Place and time: University of Warwick, Feb 27 2014

URL:http://www2.warwick.ac.uk/fac/sci/statistics/crism/workshops/bayesianapproches

Registration: free, but registration in advance is required. The capacity is limited, we recommend registering as soon as possible.

ORGANIZERS

David Rossell (Dept. of Statistics, Univ. of Warwick), Graham Cormode (Dept. of Computer Science, Univ. of Warwick)

Contact: D.Rossell@warwick.ac.uk