CORDIS Project
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This project focuses on developing advanced Bayesian nonparametric models to analyze large and complex datasets. It aims to enhance machine learning techniques for applications in natural language processing and genetics, addressing the challenges posed by high-dimensional data.
As datasets grow ever larger in scale, complexity and variety, there is an increasing need for powerful machine learning and statistical techniques that are capable of learning from such data.
Bayesian nonparametrics is a promising approach to data analysis that is increasingly popular in machine learning and statistics.
Bayesian nonparametric models are highly flexible models with infinite-dimensional parameter spaces that can be used to directly parameterise and learn about functions, densiti…
THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
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