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Counterfactual Reasoning and Learning Systems: The Example of Computational Advertising

Leon Bottou, Jonas Peters, Joaquin Quiñonero-Candela, Denis X. Charles, D. Max Chickering, Elon Portugaly, Dipankar Ray, Patrice Simard, and Ed Snelson

Abstract

This work shows how to leverage causal inference to understand the behavior of complex learning systems interacting with their environment and predict the consequences of changes to the system. Such predictions allow both humans and algorithms to select the changes that would have improved the system performance. This work is illustrated by experiments on the ad placement system associated with the Bing search engine.

Details

Publication typeArticle
Published inJournal of Machine Learning Research
URLhttp://jmlr.org/papers/v14/bottou13a.html
Pages3207–3260
Volume14
NumberNov
PublisherJournal of Machine Learning Research
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