Benjamin Guedj, University College London, gives a OxCSML Seminar on 26th March 2021.
A primer on PAC-Bayesian learning *followed by* News from the PAC-Bayes frontline
Abstract: PAC-Bayes is a generic and flexible framework to address generalisation abilities of machine learning algorithms. It leverages the power of Bayesian inference and allows to derive new learning strategies. I will briefly present the key concepts of PAC-Bayes and highlight a few recent contributions from my group.
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The Department of Statistics at Oxford is a world leader in research including computational statistics and statistical methodology, applied probability, bioinformatics and mathematical genetics. In the 2014 Research Excellence Framework (REF), Oxford's Mathematical Sciences submission was ranked overall best in the UK.
This is an exciting time for the Department. We have now moved into our new home on St Giles and we are currently settling in.
The new building provides...