[Time] 10:00am-11:00am, April 26th, 2019, Friday
[Venue] Room N510, Shunde building
[Speaker] Dr. Juergen Branke, University of Warwick, UK
[Host] Dr. Yanfu Li
[Title] Learning to optimise – optimal learning

[Abstract] This talk discusses the relationship between machine learning and optimisation. It demonstrates that many machine learning problems are actually optimisation problems, and could benefit from advances in operational research. On the other hand, the latest challenges in optimisation, such as parameter tuning, algorithm selection, Hyper heuristics or handling of uncertainty are actually closely related to machine learning. Furthermore, recent algorithmic developments such as Bayesian Optimisation very much blur the boundary between machine learning and optimisation, as they explicitly combine learning about the search space with optimisation.

[Bio] Juergen Branke is Professor of Operational Research and Systems of Warwick Business School, University of Warwick, UK. He has been working in evolutionary computation for 25 years, and his research interests include metaheuristics and Bayesian optimization, multiobjective optimization and decision making, optimization in the presence of uncertainty, and simulation-based optimization. He has published over 180 peer-reviewed papers in international journals and conferences. He is Area Editor for the Journal of Heuristics and the Journal on Multi Criteria Decision Analysis, and Associate Editor for IEEE Transaction on Evolutionary Computation,  and the Evolutionary Computation Journal.

All interested are welcome!