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Federated Learning of Explainable Artificial Intelligence Models for Predicting Parkinson's Disease Progression.

, , , , and . xAI (1), volume 1901 of Communications in Computer and Information Science, page 630-648. Springer, (2023)

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Mining the Stream of News for City Areas Profiling: a Case Study for the City of Rome., , , , , and . SMARTCOMP, page 317-322. IEEE, (2021)A News-Based Framework for Uncovering and Tracking City Area Profiles: Assessment in Covid-19 Setting., , , , , and . ACM Trans. Knowl. Discov. Data, 16 (6): 125:1-125:29 (2022)Fed-XAI: Federated Learning of Explainable Artificial Intelligence Models., , , , , , and . XAI.it@AI*IA, volume 3277 of CEUR Workshop Proceedings, page 104-117. CEUR-WS.org, (2022)Federated Learning of Explainable Artificial Intelligence Models for Predicting Parkinson's Disease Progression., , , , and . xAI (1), volume 1901 of Communications in Computer and Information Science, page 630-648. Springer, (2023)Increasing Accuracy and Explainability in Fuzzy Regression Trees: An Experimental Analysis., , , , and . FUZZ-IEEE, page 1-8. IEEE, (2022)Federated Learning of Explainable Artificial Intelligence Models: A Proof-of-Concept for Video-streaming Quality Forecasting in B5G/6G networks., , , , , , and . xAI (Late-breaking Work, Demos, Doctoral Consortium), volume 3554 of CEUR Workshop Proceedings, page 164-168. CEUR-WS.org, (2023)A federated fuzzy c-means clustering algorithm., , , , and . WILF, volume 3074 of CEUR Workshop Proceedings, CEUR-WS.org, (2021)Experimental Assessment of Heterogeneous Fuzzy Regression Trees., , , , , and . IJCCI, page 376-384. SCITEPRESS, (2023)Hoeffding Regression Trees for Forecasting Quality of Experience in B5G/6G Networks., , , , and . OLUD@WCCI, volume 3380 of CEUR Workshop Proceedings, CEUR-WS.org, (2022)Towards Trustworthy AI for QoE prediction in B5G/6G Networks., , , , , , , and . AI6G@WCCI, volume 3189 of CEUR Workshop Proceedings, CEUR-WS.org, (2022)