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Strachey Lecture - Probabilistic machine learning: foundations and frontiers

The Strachey Lectures are generously supported by OxFORD Asset Management

Professor Zoubin Ghahramani ( University of Cambridge )

Probabilistic modelling provides a mathematical framework for understanding what learning is, and has therefore emerged as one of the principal approaches for designing computer algorithms that learn from data acquired through experience. I will review the foundations of this field, from basics to Bayesian nonparametric models and scalable inference. I will then highlight some current areas of research at the frontiers of machine learning, leading up to topics such as probabilistic programming, Bayesian optimisation, the rational allocation of computational resources, and the Automatic Statistician. 

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The Strachey Lectures are generously supported by OxFORD Asset Management.

The lecture will followed by refreshments. Doors open at 1.30 pm, please be seated by 1.50 pm.

Speaker bio

Zoubin Ghahramani is Professor of Information Engineering at the University of Cambridge, Co-Director of Uber AI Labs, and the Cambridge Director of the Alan Turing Institute, the UK's national institute for Data Science. He is also the Deputy Academic Director of the Leverhulme Centre for the Future of Intelligence. He has worked and studied at the University of Pennsylvania, MIT, the University of Toronto, the Gatsby Unit at UCL, and CMU. His research spans Neuroscience, AI, Machine Learning and Statistics. In 2015 he was elected a Fellow of the Royal Society.



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