Uplift Modeling: From Causal Inference to Personalization

Author:

Moraes Felipe1ORCID,Manuel Proença Hugo1ORCID,Kornilova Anastasiia1ORCID,Albert Javier2ORCID,Goldenberg Dmitri2ORCID

Affiliation:

1. Booking.com, Amsterdam, Netherlands

2. Booking.com, Tel-Aviv, Israel

Publisher

ACM

Reference35 articles.

1. E-Commerce Promotions Personalization via Online Multiple-Choice Knapsack with Uplift Modeling

2. Susan Athey and Guido W Imbens . 2015. Machine learning methods for estimating heterogeneous causal effects. stat , Vol. 1050 , 5 ( 2015 ), 1--26. Susan Athey and Guido W Imbens. 2015. Machine learning methods for estimating heterogeneous causal effects. stat, Vol. 1050, 5 (2015), 1--26.

3. Causal Inference Meets Machine Learning

4. Floris Devriendt , Darie Moldovan , and Wouter Verbeke . 2018. A literature survey and experimental evaluation of the state-of-the-art in uplift modeling: A stepping stone toward the development of prescriptive analytics. Big data , Vol. 6 , 1 ( 2018 ), 13--41. Floris Devriendt, Darie Moldovan, and Wouter Verbeke. 2018. A literature survey and experimental evaluation of the state-of-the-art in uplift modeling: A stepping stone toward the development of prescriptive analytics. Big data, Vol. 6, 1 (2018), 13--41.

5. Eustache Diemert Artem Betlei Christophe Renaudin and Massih-Reza Amini. 2018. A large scale benchmark for uplift modeling. In KDD. Eustache Diemert Artem Betlei Christophe Renaudin and Massih-Reza Amini. 2018. A large scale benchmark for uplift modeling. In KDD.

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