Counterfactual Ranking Evaluation with Flexible Click Models
Author:
Affiliation:
1. Amazon Music, Berlin, Germany
2. Amazon Music, Seattle, WA, USA
3. Amazon Music, Ithaca, NY, NY, USA
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3626772.3657810
Reference54 articles.
1. A. Agarwal, S. Basu, T. Schnabel, and T. Joachims. 2017. Effective Evaluation using Logged Bandit Feedback from Multiple Loggers. In ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD).
2. A General Framework for Counterfactual Learning-to-Rank
3. Addressing Trust Bias for Unbiased Learning-to-Rank
4. Estimating Position Bias without Intrusive Interventions
5. Imad Aouali, Victor-Emmanuel Brunel, David Rohde, and Anna Korba. 2023. Exponential smoothing for off-policy learning. In International Conference on Machine Learning. PMLR, 984--1017.
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