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Should I (re)Learn or Should I Go(on)?: Stream Machine Learning for Adaptive Defense against Network Attacks.

, , and . MTD@CCS, page 79-88. ACM, (2019)

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A Large-scale Examination of "Socioeconomic" Fairness in Mobile Networks., , and . CoRR, (2023)Adaptive and Reinforcement Learning Approaches for Online Network Monitoring and Analysis., , , and . IEEE Trans. Netw. Serv. Manag., 18 (2): 1832-1849 (2021)pytorch-widedeep: A flexible package for multimodal deep learning., and . J. Open Source Softw., 8 (86): 5027 (June 2023)Hi-Clust: Unsupervised Analysis of Cloud Latency Measurements Through Hierarchical Clustering., , and . CloudNet, page 1-7. IEEE, (2018)Information Processing and Data Visualization in Networked Industrial Systems., , , , , , and . PIMRC, page 1-6. IEEE, (2021)Stream-based Machine Learning for Network Security and Anomaly Detection., and . Big-DAMA@SIGCOMM, page 1-7. ACM, (2018)HUMAN - Hierarchical Clustering for Unsupervised Anomaly Detection & Interpretation., , , and . NOF, page 132-140. IEEE, (2020)Should I (re)Learn or Should I Go(on)?: Stream Machine Learning for Adaptive Defense against Network Attacks., , and . MTD@CCS, page 79-88. ACM, (2019)A Large-scale Examination of "Socioeconomic" Fairness in Mobile Networks., , and . COMPASS, page 248-256. ACM, (2022)A Robust and Explainable Data-Driven Anomaly Detection Approach For Power Electronics., , , , , , and . SmartGridComm, page 296-301. IEEE, (2022)