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Joachims Thorsten Adith Swaminathan and Tobias Schnabel. \"Unbiased learning-to-rank with biased feedback.\" Proceedings of the tenth ACM international conference on web search and data mining. 2017.","key":"e_1_3_2_1_7_1","DOI":"10.1145\/3018661.3018699"},{"doi-asserted-by":"crossref","unstructured":"Kang Joseph DY and Joseph L. Schafer. \"Demystifying double robustness: A comparison of alternative strategies for estimating a population mean from incomplete data.\"\u00a0Statistical science\u00a022.4 (2007): 523-539.  Kang Joseph DY and Joseph L. Schafer. \"Demystifying double robustness: A comparison of alternative strategies for estimating a population mean from incomplete data.\"\u00a0Statistical science\u00a022.4 (2007): 523-539.","key":"e_1_3_2_1_8_1","DOI":"10.1214\/07-STS227"},{"key":"e_1_3_2_1_9_1","volume-title":"Affine corrections for unbiased learning to rank.\" Proceedings of the 29th ACM International Conference on Information & Knowledge Management","author":"Vardasbi Ali","year":"2020","unstructured":"Vardasbi , Ali , Harrie Oosterhuis , and Maarten de Rijke . \"When inverse propensity scoring does not work : Affine corrections for unbiased learning to rank.\" Proceedings of the 29th ACM International Conference on Information & Knowledge Management . 2020 . 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Qin Tao and Tie-Yan Liu. \"Introducing LETOR 4.0 datasets.\"\u00a0arXiv preprint arXiv: 1306. 2597\u00a0(2013).","key":"e_1_3_2_1_11_1"},{"key":"e_1_3_2_1_12_1","volume-title":"1-31","author":"Dato Domenico","year":"2016","unstructured":"Dato , Domenico , \"Fast ranking with additive ensembles of oblivious and non-oblivious regression trees.\"\u00a0 ACM Transactions on Information Systems (TOIS)\u00a035.2 ( 2016 ): 1-31 . Dato, Domenico, \"Fast ranking with additive ensembles of oblivious and non-oblivious regression trees.\"\u00a0ACM Transactions on Information Systems (TOIS)\u00a035.2 (2016): 1-31."},{"doi-asserted-by":"crossref","unstructured":"Saito Yuta. \"Doubly robust estimator for ranking metrics with post-click conversions.\"\u00a0Fourteenth ACM Conference on Recommender Systems. 2020.  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Saito Yuta \"Unbiased recommender learning from missing-not-at-random implicit feedback.\"\u00a0Proceedings of the 13th International Conference on Web Search and Data Mining. 2020.","key":"e_1_3_2_1_15_1","DOI":"10.1145\/3336191.3371783"},{"key":"e_1_3_2_1_16_1","volume-title":"Springer","author":"Bekker Jessa","year":"2019","unstructured":"Bekker , Jessa , Pieter Robberechts , and Jesse Davis . \" Beyond the selected completely at random assumption for learning from positive and unlabeled data.\"\u00a0Joint European Conference on Machine Learning and Knowledge Discovery in Databases . Springer , Cham , 2019 . Bekker, Jessa, Pieter Robberechts, and Jesse Davis. \"Beyond the selected completely at random assumption for learning from positive and unlabeled data.\"\u00a0Joint European Conference on Machine Learning and Knowledge Discovery in Databases. 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