Duration: 26:51

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Taking the real world example of ad placement on web search result pages, this talk (1) provides a real world example demonstrating the value of causal inference for large-scale interactive machine learning systems, (2) describes a collection of practical causal inference techniques applicable to a variety of interactive machine learning problems, (3) elucidates the relation between the exploration-exploitation dilemma and the counterfactual confidence intervals, and (4) proposes a combination of causal inference techniques and dynamical system analysis techniques to clarify the connection between auction theory and machine learning.