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Gaussian process regression on graphs

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If you have a question about this talk, please contact Dr Jes Frellsen.

I will give an overview of our work over the last few years on understanding Gaussian process learning of functions on graphs, including kernel properties on locally treelike graphs and exact learning curve predictions for large graphs. Time permitting I will describe ongoing work on mismatched problems, which are best tackled with replicated belief propagation, and multi-task learning.

This talk is part of the Machine Learning @ CUED series.

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