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Drift Models and Classification in Presence of Latency and Drift.

, and . LWA, page 65-72. Fakultät für Informatik, Otto-von-Guericke-Universität Magdeburg, (2011)

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Online Clustering of High-Dimensional Trajectories under Concept Drift., , and . ECML/PKDD (2), volume 6912 of Lecture Notes in Computer Science, page 261-276. Springer, (2011)Clustering-Based Optimised Probabilistic Active Learning (COPAL)., , and . Discovery Science, volume 9356 of Lecture Notes in Computer Science, page 101-115. Springer, (2015)Temporal Aspects of Stream Active Learning, , and . (2016)Toward optimal probabilistic active learning using a Bayesian approach, , , , , and . Machine Learning, 110 (6): 1199--1231 (2021)Advanced Topics on Data Stream Mining: Part II. Mining Multiple Streams, , and . Tutorial at the 23rd Europ. Conf. on Machine Learning and16th Europ. Conf. on Principles and Practice ofKnowledge Discovery in Databases (ECML PKDD\'12), (24-28 09 2012)Are Some Brain Injury Patients Improving More Than Others?, , , , , and . Brain Informatics and Health, volume 8609 of Lecture Notes in Computer Science, page 376-387. Springer, (2014)Learning from monitoring unlabelled data under large verification latency, and . (2016)Temporal density extrapolation using a dynamic basis approach., , and . Data Min. Knowl. Discov., 33 (5): 1323-1356 (2019)Classification in Presence of Drift and Latency., and . ICDM Workshops, page 596-603. IEEE Computer Society, (2011)Partitioner Trees for Classification: A New Ensemble Method., and . Applications of Supervised and Unsupervised Ensemble Methods, volume 245 of Studies in Computational Intelligence, Springer, (2009)