{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,27]],"date-time":"2025-09-27T14:00:32Z","timestamp":1758981632689,"version":"3.44.0"},"publisher-location":"New York, NY, USA","reference-count":58,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,5,13]],"date-time":"2024-05-13T00:00:00Z","timestamp":1715558400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-sa\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,5,13]]},"DOI":"10.1145\/3589334.3645487","type":"proceedings-article","created":{"date-parts":[[2024,5,8]],"date-time":"2024-05-08T07:08:13Z","timestamp":1715152093000},"page":"1486-1496","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Mitigating Exploitation Bias in Learning to Rank with an Uncertainty-aware Empirical Bayes Approach"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7282-2463","authenticated-orcid":false,"given":"Tao","family":"Yang","sequence":"first","affiliation":[{"name":"Amazon, Palo Alto, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3957-0687","authenticated-orcid":false,"given":"Cuize","family":"Han","sequence":"additional","affiliation":[{"name":"Box.inc, Redwood City, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5339-5817","authenticated-orcid":false,"given":"Chen","family":"Luo","sequence":"additional","affiliation":[{"name":"Amazon, Palo Alto, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0232-3412","authenticated-orcid":false,"given":"Parth","family":"Gupta","sequence":"additional","affiliation":[{"name":"Amazon, Palo Alto, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1169-2965","authenticated-orcid":false,"given":"Jeff M.","family":"Phillips","sequence":"additional","affiliation":[{"name":"University of Utah, Salt Lake City, UT, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5030-709X","authenticated-orcid":false,"given":"Qingyao","family":"Ai","sequence":"additional","affiliation":[{"name":"DCST, Tsinghua University, Quan Cheng Laboratory, & Zhongguancun Laboratory, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2024,5,13]]},"reference":[{"volume-title":"Handbook of mathematical functions with formulas, graphs, and mathematical tables","author":"Abramowitz Milton","key":"e_1_3_2_2_1_1","unstructured":"Milton Abramowitz and Irene A Stegun. 1964. Handbook of mathematical functions with formulas, graphs, and mathematical tables. Vol. 55. US Government printing office."},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331202"},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3289600.3291017"},{"key":"e_1_3_2_2_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/1148170.1148177"},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3209978.3209985"},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3209978.3209986"},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3439861"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-46147-8_5"},{"key":"e_1_3_2_2_9_1","volume-title":"Proceedings of the learning to rank challenge. PMLR, 1--24","author":"Chapelle Olivier","year":"2011","unstructured":"Olivier Chapelle and Yi Chang. 2011. Yahoo! learning to rank challenge overview. In Proceedings of the learning to rank challenge. PMLR, 1--24."},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/1645953.1646033"},{"key":"e_1_3_2_2_11_1","volume-title":"Pessimistic Off-Policy Optimization for Learning to Rank. arXiv preprint arXiv:2206.02593","author":"Cief Matej","year":"2022","unstructured":"Matej Cief, Branislav Kveton, and Michal Kompan. 2022. Pessimistic Off-Policy Optimization for Learning to Rank. arXiv preprint arXiv:2206.02593 (2022)."},{"key":"e_1_3_2_2_12_1","volume-title":"Not All Relevance Scores are Equal: Efficient Uncertainty and Calibration Modeling for Deep Retrieval Models. arXiv preprint arXiv:2105.04651","author":"Cohen Daniel","year":"2021","unstructured":"Daniel Cohen, Bhaskar Mitra, Oleg Lesota, Navid Rekabsaz, and Carsten Eickhoff. 2021. Not All Relevance Scores are Equal: Efficient Uncertainty and Calibration Modeling for Deep Retrieval Models. arXiv preprint arXiv:2105.04651 (2021)."},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/1341531.1341545"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3015022.3015026"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/2987380"},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1977.tb01600.x"},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/1571941.1572003"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3366424.3382705"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557066"},{"key":"e_1_3_2_2_20_1","volume-title":"Predictive Uncertainty-based Bias Mitigation in Ranking. arXiv preprint arXiv:2309.09833","author":"Heuss Maria","year":"2023","unstructured":"Maria Heuss, Daniel Cohen, Masoud Mansoury, Maarten de Rijke, and Carsten Eickhoff. 2023. Predictive Uncertainty-based Bias Mitigation in Ranking. arXiv preprint arXiv:2309.09833 (2023)."},{"key":"e_1_3_2_2_21_1","volume-title":"ACM Transactions on Information Systems (TOIS)","volume":"20","author":"Jaana Kalervo","year":"2002","unstructured":"Kalervo J\"arvelin and Jaana Kek\"al\"ainen. 2002. Cumulated gain-based evaluation of IR techniques. ACM Transactions on Information Systems (TOIS), Vol. 20, 4 (2002), 422--446."},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3460231.3474247"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3018661.3018699"},{"key":"e_1_3_2_2_24_1","volume-title":"International Conference on Artificial Intelligence and Statistics. PMLR, 6880--6892","author":"Kveton Branislav","year":"2022","unstructured":"Branislav Kveton, Ofer Meshi, Masrour Zoghi, and Zhen Qin. 2022. On the Value of Prior in Online Learning to Rank. In International Conference on Artificial Intelligence and Statistics. PMLR, 6880--6892."},{"key":"e_1_3_2_2_25_1","unstructured":"Chang Li Branislav Kveton Tor Lattimore Ilya Markov Maarten de Rijke Csaba Szepesv\u00e1ri and Masrour Zoghi. 2020. BubbleRank: Safe online learning to re-rank via implicit click feedback. In Uncertainty in Artificial Intelligence. PMLR 196--206."},{"key":"e_1_3_2_2_26_1","volume-title":"Local Policy Improvement for Recommender Systems. arXiv preprint arXiv:2212.11431","author":"Liang Dawen","year":"2022","unstructured":"Dawen Liang and Nikos Vlassis. 2022. Local Policy Improvement for Recommender Systems. arXiv preprint arXiv:2212.11431 (2022)."},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3341981.3344234"},{"key":"e_1_3_2_2_28_1","volume-title":"Foundations and Trends\u00ae in Information Retrieval","volume":"3","author":"Tie-Yan","year":"2009","unstructured":"Tie-Yan Liu et al. 2009. Learning to rank for information retrieval. Foundations and Trends\u00ae in Information Retrieval, Vol. 3, 3 (2009), 225--331."},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/2396761.2398691"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401100"},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3271686"},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401102"},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3437963.3441794"},{"key":"e_1_3_2_2_34_1","volume-title":"Proceedings of the Web Conference","author":"Oosterhuis Harrie","year":"2021","unstructured":"Harrie Oosterhuis and Maarten de de Rijke. 2021b. Robust Generalization and Safe Query-Specializationin Counterfactual Learning to Rank. In Proceedings of the Web Conference 2021. 158--170."},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380255"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.eacl-main.12"},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10791-009-9123-y"},{"key":"e_1_3_2_2_38_1","unstructured":"Howard Raiffa Robert Schlaifer et al. 1961. Applied statistical decision theory. (1961)."},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/3121050.3121087"},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3336191.3371783"},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/2513150.2513162"},{"key":"e_1_3_2_2_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/2835776.2835804"},{"key":"e_1_3_2_2_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220088"},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/1321440.1321528"},{"key":"e_1_3_2_2_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482020"},{"key":"e_1_3_2_2_46_1","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3412031"},{"key":"e_1_3_2_2_47_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331264"},{"key":"e_1_3_2_2_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/3209978.3210045"},{"key":"e_1_3_2_2_49_1","volume-title":"Deep bayesian active learning for learning to rank: A case study in answer selection","author":"Wang Qunbo","year":"2021","unstructured":"Qunbo Wang, Wenjun Wu, Yuxing Qi, and Yongchi Zhao. 2021. Deep bayesian active learning for learning to rank: A case study in answer selection. IEEE Transactions on Knowledge and Data Engineering (2021)."},{"key":"e_1_3_2_2_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/2911451.2911537"},{"key":"e_1_3_2_2_51_1","doi-asserted-by":"publisher","DOI":"10.1145\/3159652.3159732"},{"key":"e_1_3_2_2_52_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449901"},{"key":"e_1_3_2_2_53_1","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3412128"},{"key":"e_1_3_2_2_54_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531948"},{"key":"e_1_3_2_2_55_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539597.3570474"},{"key":"e_1_3_2_2_56_1","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553527"},{"key":"e_1_3_2_2_57_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-00958-7_5"},{"key":"e_1_3_2_2_58_1","volume-title":"International Conference on Machine Learning. PMLR, 4199--4208","author":"Zoghi Masrour","year":"2017","unstructured":"Masrour Zoghi, Tomas Tunys, Mohammad Ghavamzadeh, Branislav Kveton, Csaba Szepesvari, and Zheng Wen. 2017. Online learning to rank in stochastic click models. In International Conference on Machine Learning. PMLR, 4199--4208. io"}],"event":{"name":"WWW '24: The ACM Web Conference 2024","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"],"location":"Singapore Singapore","acronym":"WWW '24"},"container-title":["Proceedings of the ACM Web Conference 2024"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3589334.3645487","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3589334.3645487","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:25:11Z","timestamp":1755822311000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3589334.3645487"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,13]]},"references-count":58,"alternative-id":["10.1145\/3589334.3645487","10.1145\/3589334"],"URL":"https:\/\/doi.org\/10.1145\/3589334.3645487","relation":{},"subject":[],"published":{"date-parts":[[2024,5,13]]},"assertion":[{"value":"2024-05-13","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}