Effective Evaluation using Logged Bandit Feedback from Multiple Loggers

17 Mar 2017Aman AgarwalSoumya BasuTobias SchnabelThorsten Joachims

Accurately evaluating new policies (e.g. ad-placement models, ranking functions, recommendation functions) is one of the key prerequisites for improving interactive systems. While the conventional approach to evaluation relies on online A/B tests, recent work has shown that counterfactual estimators can provide an inexpensive and fast alternative, since they can be applied offline using log data that was collected from a different policy fielded in the past... (read more)

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