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Regression with n$\to$1 by Expert Knowledge Elicitation.

, , и . CoRR, (2016)

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Antonio Carlos Soares Pinto

Fares Martak

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Davide Soares da Silva

José Carvalho Soares

 

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Probabilistic Expert Knowledge Elicitation of Feature Relevances in Sparse Linear Regression., , , и . IAL@PKDD/ECML, том 1924 из CEUR Workshop Proceedings, стр. 64-66. CEUR-WS.org, (2017)Multi-Agent Best Arm Identification with Private Communications., , , и . ICML, том 202 из Proceedings of Machine Learning Research, стр. 29082-29102. PMLR, (2023)Secure Outsourcing of Multi-Armed Bandits., , , и . TrustCom, стр. 202-209. IEEE, (2020)Sequential Resource Allocation in Linear Stochastic Bandits . (Allocation séquentielle de ressources dans le modèle de bandit linéaire).. Lille University of Science and Technology, France, (2015)FeReD: Federated Reinforcement Learning in the DBMS., , , и . CIKM, стр. 4989-4993. ACM, (2022)Regression with n→1 by Expert Knowledge Elicitation., , и . ICMLA, стр. 734-739. IEEE Computer Society, (2016)Implementing Linear Bandits in Off-the-Shelf SQLite., , и . EDBT, стр. 2:388-2:392. OpenProceedings.org, (2022)Best-Arm Identification in Linear Bandits., , и . NIPS, стр. 828-836. (2014)Interactive Elicitation of Knowledge on Feature Relevance Improves Predictions in Small Data Sets., , , , , , , и . IUI, стр. 547-552. ACM, (2017)Samba: A System for Secure Federated Multi-Armed Bandits., , , , и . ICDE, стр. 3154-3157. IEEE, (2022)