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Seminar: Fredrik Johansson – What would have happened if...? ML and causal inference

SEMINAR

Inferences made by machine learning methods increasingly form the basis of actions in the real world. To learn how to act requires understanding of cause-effect relationships, and while often overlooked in machine learning, modern applications like personalised medicine cannot function without causal inference. A common problem arising in such settings is that of counterfactual inference: “What would have happened if X instead of Y?” We put this question in the context of machine learning methods, such as contextual bandits and representation learning, and discuss relevant theory and applications.

Date: 2016-02-11 10:30 - 12:00

Location: EDIT-room 3364, Chalmers Johanneberg

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Page updated: 2016-02-10 11:42

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