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Block size, parallelism and predictive performance: finding the sweet spot in distributed learning., , , , и . Int. J. Parallel Emergent Distributed Syst., 39 (3): 379-398 (мая 2024)A Conversational Interface for interacting with Machine Learning models., , , , и . XAILA@ICAIL, том 3168 из CEUR Workshop Proceedings, CEUR-WS.org, (2021)Optimizing Model Training in Interactive Learning Scenarios., , , и . WorldCIST (1), том 1365 из Advances in Intelligent Systems and Computing, стр. 156-165. Springer, (2021)Using meta-learning to predict performance metrics in machine learning problems., , , и . Expert Syst. J. Knowl. Eng., (2023)A multiple criteria approach for constructing a pandemic impact assessment composite indicator: The case of Covid-19 in Portugal., , , , , , , и . CoRR, (2021)Algorithm Recommendation and Performance Prediction Using Meta-Learning., , , , и . Int. J. Neural Syst., 33 (3): 2350011:1-2350011:16 (марта 2023)Continuously Learning from User Feedback., , , , , и . WorldCIST (1), том 468 из Lecture Notes in Networks and Systems, стр. 579-588. Springer, (2022)Explainable Decision Tree on Smart Human Mobility., , , , и . Intelligent Environments (Workshops), том 31 из Ambient Intelligence and Smart Environments, стр. 325-334. IOS Press, (2022)A multiple criteria approach for building a pandemic impact assessment composite indicator: The case of COVID-19 in Portugal., , , , , , , и . Eur. J. Oper. Res., 309 (2): 795-818 (сентября 2023)Optimizing Instance Selection Strategies in Interactive Machine Learning: An Application to Fraud Detection., , и . HIS, том 1375 из Advances in Intelligent Systems and Computing, стр. 124-133. Springer, (2020)