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2014 Milner Award Lecture - Statistical and causal approaches to machine learning

In machine learning, we use data to automatically find dependences in the world, with the goal of predicting future observations. Most machine learning methods build on statistics, but one can also try to go beyond this, assaying causal structures underlying statistical dependences. The hope is that this also allows prediction in certain situations where systems change, for instance by interventions.


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