Counterfactual Reasoning and Learning Systems: The Example of Computational Advertising

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.

bottou13a.pdf
PDF file

In  Journal of Machine Learning Research

Publisher  Journal of Machine Learning Research
(c) 2013 Léon Bottou, Jonas Peters, Joaquin Quiñonero-Candela, Denis X. Charles, D. Max Chickering, Elon Portugaly, Dipankar Ray, Patrice Simard and Ed Snelson

Details

TypeArticle
URLhttp://jmlr.org/papers/v14/bottou13a.html
Pages3207–3260
Volume14
NumberNov
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