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Enhancing Virtual Sensors to deal with Missing Values and Low Sampling Rates., , , , and . MobileCloud, page 39-44. IEEE, (2023)Hypertuming GRU Neural Networks for Edge Resource Usage Prediction., , , , , and . ISCC, page 1-8. IEEE, (2021)Automated and Reproducible Application Traces Generation for IoT Applications., , , , , , and . Q2SWinet, page 17-24. ACM, (2021)Mapping of Quality of Service Requirements to Resource Demands for IaaS., , , , , , , , and . CLOSER, page 263-270. SciTePress, (2019)Sentiment Analysis using Word-Graphs., , , , and . WIMS, page 22:1-22:9. ACM, (2016)User Association and Behavioral Characterization during Task Offloading at the Edge., , , , , and . MeditCom, page 70-75. IEEE, (2021)Multi-Agent Deep Reinforcement Learning for Weighted Multi-Path Routing., , , , and . FRAME@HPDC, page 7-11. ACM, (2023)Inter-operability and Orchestration in Heterogeneous Cloud/Edge Resources: The ACCORDION Vision., , , , , , , , , and 7 other author(s). FRAME@HPDC, page 9-14. ACM, (2021)Next Position Prediction using LSTM Neural Networks., , , , and . SETN, page 232-240. ACM, (2020)A Deep Learning Approach for IoT Traffic Multi-Classification in a Smart-City Scenario., , and . IEEE Access, (2022)