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        Department of Systems Engineering and Engineering Management

                            The Chinese University of Hong Kong

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Date: 4:30pm - 6:00pm on 11 September (Thursday)

Venue: ERB 513, The Chinese University of Hong Kong

Title: Bayesian optimisation of graph-based functions

Speaker: Xiaowen Dong, Department of Engineering Science, University of Oxford



Abstract:

The increasing availability of graph-structured data motivates a new type of optimisation problems over graph-based functions, i.e., searching for the graph or node that maximises the value of an underlying function. Such optimisation problems are challenging due to the search space that is discrete and high-dimensional, as well as the underlying function that is often black-box and expensive to evaluate. In this talk, I will provide several examples on how Bayesian optimisation can be used to optimise graph-based functions, with practical applications in computational, epidemiological, and social networks. More broadly, these examples demonstrate the promise in combining probabilistic and geometric reasoning in analysing complex functions.



Biography:

Xiaowen Dong is an associate professor in the Department of Engineering Science at the University of Oxford, where he is a member of both the Machine Learning Research Group and the Oxford-Man Institute. Prior to joining Oxford, he was a postdoctoral associate in the MIT Media Lab, where he remains as a research affiliate, and received his PhD degree from the Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland. His main research interests concern signal processing and machine learning techniques for analysing network data, and their applications in social and economic sciences.