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Next to You: Monitoring Quality of Experience in Cellular Networks From the End-Devices.

, , , , , and . IEEE Trans. Network and Service Management, 13 (2): 181-196 (2016)

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IP mining: Extracting knowledge from the dynamics of the Internet addressing space., , and . ITC, page 1-9. IEEE, (2013)RAL: reinforcement active learning for network traffic monitoring and analysis., , and . SIGCOMM Posters and Demos, page 55-56. ACM, (2020)Mobile Web and App QoE Monitoring for ISPs - from Encrypted Traffic to Speed Index through Machine Learning., , , , , and . WMNC, page 40-47. IEEE, (2021)Looking for Network Latency Clusters in the LAC Region., and . LANCOMM@SIGCOMM, page 10-12. ACM, (2016)Diagnosing Device-Specific Anomalies in Cellular Networks., , , and . CoNEXT Student Workshop, page 18-20. ACM, (2014)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)Detecting and diagnosing anomalies in cellular networks using Random Neural Networks., , , and . IWCMC, page 351-356. IEEE, (2016)On the use of Sub-Space Clustering & Evidence Accumulation for traffic analysis & classification., , and . IWCMC, page 1016-1021. IEEE, (2011)YouTube all around: Characterizing YouTube from mobile and fixed-line network vantage points., , , , , and . EuCNC, page 1-5. IEEE, (2014)Network security and anomaly detection with Big-DAMA, a big data analytics framework., , , , and . CloudNet, page 16-22. IEEE, (2017)