James Grant, Lecturer in Statistics at Lancaster University on "Multi-armed Bandits"

Conference TFNetworkAutumn21

Data Science - The beating heart of AI
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James Grant is a Lecturer in Statistics at Lancaster University where he completed his PhD in 2019. His research considers mathematical models of decision-making and learning, and combines ideas from Statistics, Operational Research, and Machine Learning. He is particularly interested in multi-armed bandit problems, online optimisation, recommender systems, and time series.

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Multi-armed Bandits

In modern data science applications, there is often the opportunity to observe the effects of a decision and revise it, and to iterate this process repeatedly, experimenting in order to learn an optimal action. Multi-armed bandits provide mathematical models of such settings, where designing an optimal sequence of decisions can be highly challenging. This talk will give an introduction to multi-armed bandit models, and explore the best techniques used to tackle the problems.