Counterfactual Evaluation and Learning for Search, Recommendation and Ad Placement

By Thorsten Joachims, Adith Swaminathan. 2016

72 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. James McInerney
2. Hugues Bouchard
3. Samantha Hansen
4. James Jordon
5. Rishabh Mehrotra
6. Alois Gruson
7. Karl Higley
8. B. Lacker

Citations in the corpus

• Deep-Treat: Learning Optimal Personalized Treatments From Observational Data Using Neural Networks (2018, background): “The IPS estimates learn the counterfactuals by re-weighting each instance with their inverse propensity scores (Swaminathan and Joachims 2015a; Joachims and Swaminathan 2016).”
• Explore, exploit, and explain: personalizing explainable recommendations with bandits (2018, methodology): “We use counterfactual risk minimization (CRM) to train the contextual bandit [10].”