A churn prediction dataset from the telecom sector: a new benchmark for uplift modeling
Théo Verhelst, Denis Mercier, Jeevan Shrestha, Gianluca Bontempi

ECML PKDD 2023 Workshops - Workshop on Uplift Modeling and Causal Machine Learning for Operational Decision Making

Workshop page

Partial counterfactual identification and uplift modeling: theoretical results and real-world assessment
Théo Verhelst, Denis Mercier, Jeevan Shrestha, Gianluca Bontempi

Machine Learning, 2023

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Predicting reach to find persuadable customers: improving uplift models for churn prevention
Théo Verhelst, Denis Mercier, Jeevan Shrestha, Jean-Christophe Dewitte, Gianluca Bontempi

24th International Conference on Discovery Science (DS 2021)

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Transfer learning strategies for credit card fraud detection
Bertrand Lebichot, Théo Verhelst, Yann-Aël Le Borgne, Liyun He-Guelton, Frédéric Oblé, Gianluca Bontempi

IEEE Access, 2021

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Understanding telecom customer churn with machine learning: from prediction to causal inference
Théo Verhelst, Olivier Caelen, Jean-Christophe Dewitte, Bertrand Lebichot, Gianluca Bontempi

31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019)

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Churn Prediction and Causal Analysis on Telecom Customer Data
Théo Verhelst, supervised by Gianluca Bontempi

Université Libre de Bruxelles, 2019

Master thesis