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Deep Reinforcement Learning and Graph Neural Networks for Efficient Resource Allocation in 5G Networks.

, , , and . LATINCOM, page 1-6. IEEE, (2022)

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Machine-Learning Based Approaches for Anomaly Detection and Classification in Cellular Networks., , and . TMA, IFIP, (2016)DeepSec meets RawPower - Deep Learning for Detection of Network Attacks Using Raw Representations., , and . SIGMETRICS Perform. Evaluation Rev., 46 (3): 147-150 (2018)Two Decades of AI4NETS - AI/ML for Data Networks: Challenges & Research Directions.. NOMS, page 1-6. IEEE, (2020)White Paper on Crowdsourced Network and QoE Measurements - Definitions, Use Cases and Challenges., , , , , , , , , and 6 other author(s). CoRR, (2020)Understanding HTTP Traffic and CDN Behavior from the Eyes of a Mobile ISP., , and . PAM, volume 8362 of Lecture Notes in Computer Science, page 268-271. Springer, (2014)Network security and anomaly detection with Big-DAMA, a big data analytics framework., , , , and . CloudNet, page 16-22. IEEE, (2017)YouTube all around: Characterizing YouTube from mobile and fixed-line network vantage points., , , , , and . EuCNC, page 1-5. IEEE, (2014)On the use of Sub-Space Clustering & Evidence Accumulation for traffic analysis & classification., , and . IWCMC, page 1016-1021. IEEE, (2011)Detecting and diagnosing anomalies in cellular networks using Random Neural Networks., , , and . IWCMC, page 351-356. IEEE, (2016)Quality of Experience in Cloud services: Survey and measurements., and . Comput. Networks, (2014)