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A Modular Machine Learning System for Flow-Level Traffic Classification in Large Networks.

, , , , , and . ACM Trans. Knowl. Discov. Data, 6 (1): 4:1-4:34 (2012)

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Identifying diverse usage behaviors of smartphone apps., , , , , and . Internet Measurement Conference, page 329-344. ACM, (2011)Internet Traffic Identification using Machine Learning., , and . GLOBECOM, IEEE, (2006)Offline/realtime traffic classification using semi-supervised learning., , , , and . Perform. Evaluation, 64 (9-12): 1194-1213 (2007)HTTP in the home: it is not just about PCs., , and . Comput. Commun. Rev., 41 (1): 90-95 (2011)Monitoring quality-of-experience for operational cellular networks using machine-to-machine traffic., , , , , and . INFOCOM, page 1-9. IEEE, (2017)Detecting and localizing end-to-end performance degradation for cellular data services., , , , , and . INFOCOM, page 1-9. IEEE, (2016)Detecting and Localizing End-to-End Performance Degradation for Cellular Data Services., , , , , and . SIGMETRICS, page 459-460. ACM, (2015)Traffic classification using clustering algorithms., , and . MineNet, page 281-286. ACM, (2006)Understanding the impact of network dynamics on mobile video user engagement., , , , , and . SIGMETRICS, page 367-379. ACM, (2014)Fair and optimal resource allocation for LTE multicast (eMBMS): Group partitioning and dynamics., , , , , and . INFOCOM, page 1266-1274. IEEE, (2015)