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Artificial intelligence of things at the edge: Scalable and efficient distributed learning for massive scenarios., , , and . Comput. Commun., (May 2023)Federated Semi-Supervised Classification of Multimedia Flows for 3D Networks., , , , and . CoRR, (2022)A Novel Approach to Distributed Model Aggregation using Apache Kafka., , , , , and . FRAME@HPDC, page 33-36. ACM, (2022)How Generative Models Improve LOS Estimation in 6G Non-Terrestrial Networks., , , and . CoRR, (2023)A Federated Channel Modeling System using Generative Neural Networks., , , and . VTC2023-Spring, page 1-5. IEEE, (2023)PhD Forum Abstract: Efficient Computing and Communication Paradigms for Federated Learning Data Streams.. SMARTCOMP, page 410-411. IEEE, (2021)FedTCS: Federated Learning with Time-based Client Selection to Optimize Edge Resources., , , and . AI6G@WCCI, volume 3189 of CEUR Workshop Proceedings, CEUR-WS.org, (2022)Drivers Stress Identification in Real-World Driving Tasks., , and . PerCom Workshops, page 140-141. IEEE, (2022)AI-as-a-Service Toolkit for Human-Centered Intelligence in Autonomous Driving., , , , , , , , , and 4 other author(s). PerCom Workshops, page 91-93. IEEE, (2022)KafkaFed: Two-Tier Federated Learning Communication Architecture for Internet of Vehicles., , , and . PerCom Workshops, page 515-520. IEEE, (2022)