Reaching the End of Unbiasedness

Author:

Oosterhuis Harrie1

Affiliation:

1. Radboud University, Nijmegen, Netherlands

Funder

Google Inc.

Publisher

ACM

Reference74 articles.

1. A General Framework for Counterfactual Learning-to-Rank

2. Aman Agarwal , Xuanhui Wang , Cheng Li , Michael Bendersky , and Marc Najork . 2019 . Addressing Trust Bias for Unbiased Learning-to-Rank. In The World Wide Web Conference. ACM, 4--14 . Aman Agarwal, Xuanhui Wang, Cheng Li, Michael Bendersky, and Marc Najork. 2019. Addressing Trust Bias for Unbiased Learning-to-Rank. In The World Wide Web Conference. ACM, 4--14.

3. Estimating Position Bias without Intrusive Interventions

4. Learning user interaction models for predicting web search result preferences

5. Unbiased Learning to Rank with Unbiased Propensity Estimation

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2. Safe Deployment for Counterfactual Learning to Rank with Exposure-Based Risk Minimization;Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval;2023-07-18

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4. An Offline Metric for the Debiasedness of Click Models;Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval;2023-07-18

5. Recent Advances in the Foundations and Applications of Unbiased Learning to Rank;Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval;2023-07-18

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