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Implicit feedback is widely leveraged in recommender systems since it is easy to collect and provides weak supervision signals.
Correlation and causation
Sewall Wright · 1921
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An overview of bilevel optimization
Benoît Colson, Patrice Marcotte, and Gilles Savard · 2007
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Collaborative filtering for implicit feedback datasets
Yifan Hu, Yehuda Koren, and Chris Volinsky · 2008
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One-class collaborative filtering
Rong Pan, Yunhong Zhou, Bin Cao, Nathan N Liu, Rajan Lukose, Martin Scholz, and Qiang Yang · 2008
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Matrix factorization techniques for recommender systems
Yehuda Koren, Robert Bell, and Chris Volinsky · 2009
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Mind the gaps: weighting the unknown in large-scale one-class collaborative filtering
Rong Pan and Martin Scholz · 2009
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Training and testing of recommender systems on data missing not at random
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Bpr: Bayesian personalized ranking from implicit feedback
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Evaluation of recommendations: rating-prediction and ranking
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Probabilistic matrix factorization with non-random missing data
José Miguel Hernández-Lobato, Neil Houlsby, and Zoubin Ghahramani · 2014
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Dawen Liang, Laurent Charlin, and David M Blei · 2016
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Unbiased offline recommender evaluation for missing-not-at-random implicit feedback
Longqi Yang, Yin Cui, Yuan Xuan, Chenyang Wang, Serge Belongie, and Deborah Estrin · 2018
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Neural graph collaborative filtering
Xiang Wang, Xiangnan He, Meng Wang, Fuli Feng, and Tat-Seng Chua · 2019
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Doubly robust joint learning for recommendation on data missing not at random
Xiaojie Wang, Rui Zhang, Yu Sun, and Jianzhong Qi · 2019
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Probabilistic metric learning with adaptive margin for top-k recommendation
Chen Ma, Liheng Ma, Yingxue Zhang, Ruiming Tang, Xue Liu, and Mark Coates · 2020
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Unbiased recommender learning from missing-not-at-random implicit feedback
Yuta Saito, Suguru Yaginuma, Yuta Nishino, Hayato Sakata, and Kazuhide Nakata · 2020
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Causal inference for recommender systems
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Tobias Schnabel, Adith Swaminathan, Ashudeep Singh, Navin Chandak, and Thorsten Joachims · 2016
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Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu, and Tat-Seng Chua · 2017
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Hsiang-Fu Yu, Mikhail Bilenko, and Chih-Jen Lin · 2017
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Unbiased implicit recommendation and propensity estimation via combinational joint learning
Ziwei Zhu, Yun He, Yin Zhang, and James Caverlee · 2020
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Do we really need gold samples for sample weighting under label noise?
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Correcting exposure bias for link recommendation
Shantanu Gupta, Hao Wang, Zachary C Lipton, and Yuyang Wang · 2021
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