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BIGBAYES Report Summary

Project ID: 617071
Funded under: FP7-IDEAS-ERC
Country: United Kingdom

Mid-Term Report Summary - BIGBAYES (Rich, Structured and Efficient Learning of Big Bayesian Models)

With complex heterogeneous and large scale data becoming ever more common, we need sophisticated machine learning models that allow us to learn as much as possible and as efficiently as possible from such data. This project aims to explore the use of Bayesian and nonparametric models, with diverse challenges ranging from theoretical understanding, to modelling and algorithmic developments, to software systems allowing ease of use by end users.

At the mid-point of the project, we have developed both generic models and methods that are flexible and scalable, as well as specialised methods addressing application problems arising in population genetics, cancer genetics, document processing, collaborative filtering, and policy research.


Gill Wells, (Head of European Team)
Tel.: +44 1865 289800
Fax: +44 1865 289801
Record Number: 195427 / Last updated on: 2017-03-13
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