Recent Advancements in Unbiased Learning to Rank

Author:

Gupta Shashank1ORCID,Hager Philipp K1ORCID,Oosterhuis Harrie2ORCID

Affiliation:

1. University of Amsterdam, Netherlands

2. Radboud University, Netherlands

Publisher

ACM

Reference59 articles.

1. 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. 4–14.

2. Qingyao Ai, Jiaxin Mao, Yiqun Liu, and W Bruce Croft. 2018. Unbiased learning to rank: Theory and practice. In Proceedings of the 27th ACM International Conference on Information and Knowledge Management. 2305–2306.

3. Asia J Biega, Krishna P Gummadi, and Gerhard Weikum. 2018. Equity of attention: Amortizing individual fairness in rankings. In The 41st international acm sigir conference on research & development in information retrieval. 405–414.

4. Adam Block, Rahul Kidambi, Daniel N Hill, Thorsten Joachims, and Inderjit S Dhillon. 2022. Counterfactual Learning To Rank for Utility-Maximizing Query Autocompletion. arXiv preprint arXiv:2204.10936 (2022).

5. Olivier Chapelle and Yi Chang. 2011. Yahoo! Learning to Rank Challenge Overview. In Proceedings of the learning to rank challenge. PMLR, 1–24.

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