A Comprehensive Survey on Machine Learning for Networking: Evolution, Applications and Research Opportunities, JISA, vol.9, issue.1, 2018. ,
MAWILab: Combining Diverse Anomaly Detectors for Automated Anomaly Labeling and Performance Benchmarking, ACM CoNEXT, 2010. ,
URL : https://hal.archives-ouvertes.fr/ensl-00552071
Network security and anomaly detection with Big-DAMA, a big data analytics framework, IEEE CloudNet, 2017. ,
Anomaly Detection: A Survey, ACM Computing Surveys, vol.41, pp.1-15, 2009. ,
A survey of network anomaly detection techniques, Journal of Network and Computer Applications, vol.60, issue.C, pp.19-31, 2016. ,
A Survey of Anomaly Detection Methods in Networks, IEEE CNMT, 2009. ,
Ensemble-learning Approaches for Network Security and Anomaly Detection, ACM SIGCOMM Big-DAMA Workshop, 2017. ,
GML learning, a generic machine learning model for network measurements analysis, IEEE CNSM, 2017. ,
Super learning for anomaly detection in cellular networks, IEEE WiMob, 2017. ,
A streaming flow-based technique for traffic classification applied to 12+1 years of Internet traffic, Telecommunication Systems, vol.63, 2016. ,
Catching Up with the Data: Research Issues in Mining Data Streams, 2001. ,
The 8 requirements of real-time stream processing, ACM SIGMOD Record, vol.34, pp.42-47, 2005. ,
Mining massive data streams, 2005. ,
Issues in evaluation of stream learning algorithms, SIGKDD, 2009. ,
On evaluating stream learning algorithms, Machine learning, vol.90, pp.317-346, 2013. ,
Learning from streaming data with concept drift and imbalance: an overview, Progress in Artificial Intelligence, vol.1, pp.89-101, 2012. ,
MOA: Massive Online Analysis, Journal of Machine Learning Research, vol.11, pp.1601-1604, 2010. ,
Learning from Time-Changing Data with Adaptive Windowing, SIAM International Conference on Data Mining, 2007. ,
Efficient Online Evaluation of Big Data Stream Classifiers, ACM SIGKDD, 2015. ,
Mining high-speed data streams, ACM SIGKDD, 2000. ,
Adaptive random forests for evolving data stream classification, Machine Learning, vol.106, pp.1469-1495, 2017. ,
URL : https://hal.archives-ouvertes.fr/hal-01689026
A survey on concept drift adaptation, ACM CSUR, 2014. ,
The Nonstochastic Multiarmed Bandit Problem, SIAM Journal on Computing, vol.32, issue.1, pp.48-77, 2002. ,
Online Choice of Active Learning Algorithms, Journal of Machine Learning Research, vol.5, pp.255-291, 2004. ,
Active Learning by Learning, AAAI, 2015. ,
Clustering Based Active Learning for Evolving Data Streams, International Conference on Discovery Science, 2013. ,
Active and adaptive ensemble learning for online activity recognition from data streams, Knowledge-Based Systems, vol.138, pp.69-78, 2017. ,
Active Learning Literature Survey, 2010. ,
Stream-based Online Active Learning in a Contextual Multi-Armed Bandit Framework, 2016. ,
A Contextual Bandit Approach for Stream-Based Active Learning, 2017. ,
Learning from Delayed Rewards, 1989. ,
Active learning over evolving data streams using paired ensemble framework, ICACI, 2016. ,
Active Learning with Evolving Streaming Data, ECML PKDD, 2011. ,
Active Learning with Drifting Streaming Data, IEEE Transactions on Neural Networks and Learning Systems, vol.25, pp.27-39, 2014. ,
Continuous Inspection Schemes, Biometrika, vol.41, pp.100-115, 1954. ,