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Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach.

, , , , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 6987-6998. PMLR, (2020)

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RecSim: A Configurable Simulation Platform for Recommender Systems, , , , , , , and . (2019)cite arxiv:1909.04847.Differentiable Meta-Learning in Contextual Bandits., , , , , and . CoRR, (2020)Equitable Partitions of Concave Free Energies., and . UAI, page 602-611. AUAI Press, (2015)Planning and Learning with Stochastic Action Sets., , , , , , and . IJCAI, page 4674-4682. ijcai.org, (2018)Content Prompting: Modeling Content Provider Dynamics to Improve User Welfare in Recommender Ecosystems., , and . CoRR, (2023)RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystems., , , , , , , , , and . CoRR, (2021)Towards Content Provider Aware Recommender Systems: A Simulation Study on the Interplay between User and Provider Utilities., , , , , , , , and . WWW, page 3872-3883. ACM / IW3C2, (2021)RELOOP: A Python-Embedded Declarative Language for Relational Optimization., , , , and . AAAI Workshop: Declarative Learning Based Programming, volume WS-16-07 of AAAI Technical Report, AAAI Press, (2016)978-1-57735-759-9.Differentiable Meta-Learning of Bandit Policies., , , , , and . NeurIPS, (2020)Extracting Events from Spatial Time Series, , , , and . 14th International Conference on Information Visualisation, IV 2010, 26-29 July 2010, London, UK, page 48--53. (2010)