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On ranking via sorting by estimated expected utility.

, и . NeurIPS, (2020)

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Clément Grimal

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Fairness-Aware Learning for Continuous Attributes and Treatments., , и . ICML, том 97 из Proceedings of Machine Learning Research, стр. 4382-4391. PMLR, (2019)Neural Generative Models for Global Optimization with Gradients., , , и . CoRR, (2018)Do Not Mask What You Do Not Need to Mask: A Parser-Free Virtual Try-On., , и . ECCV (20), том 12365 из Lecture Notes in Computer Science, стр. 619-635. Springer, (2020)On ranking via sorting by estimated expected utility., и . NeurIPS, (2020)Pure Exploration and Regret Minimization in Matching Bandits., , , , и . ICML, том 139 из Proceedings of Machine Learning Research, стр. 9434-9442. PMLR, (2021)Bridging the gap between regret minimization and best arm identification, with application to A/B tests., , , и . AISTATS, том 89 из Proceedings of Machine Learning Research, стр. 1988-1996. PMLR, (2019)Wasserstein Learning of Determinantal Point Processes., , , , и . CoRR, (2020)Jointly Efficient and Optimal Algorithms for Logistic Bandits., , , и . AISTATS, том 151 из Proceedings of Machine Learning Research, стр. 546-580. PMLR, (2022)A Technical Note on Non-Stationary Parametric Bandits: Existing Mistakes and Preliminary Solutions., , , и . ALT, том 132 из Proceedings of Machine Learning Research, стр. 619-626. PMLR, (2021)Strategic Arms with Side Communication Prevail Over Low-Regret MAB Algorithms., , и . CoRR, (2024)