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Meta-ADD: A meta-learning based pre-trained model for concept drift active detection.

, , , , , and . Inf. Sci., (2022)

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Efficient class incremental learning for multi-label classification of evolving data streams., , , and . IJCNN, page 2093-2099. IEEE, (2014)Detecting group concept drift from multiple data streams., , , , , and . Pattern Recognit., (2023)Depth and Width Adaption of DNN for Data Stream Classification with Concept Drifts., , and . IDEAL, volume 14404 of Lecture Notes in Computer Science, page 406-417. Springer, (2023)A multi-objective particle swarm optimization data scheduling algorithm for peer-to-peer video streaming., , , and . ICNC-FSKD, page 278-285. IEEE, (2017)Predicting Learning Effect by Learner's Behavior in MOOCs., , , , and . IDEAL, volume 10585 of Lecture Notes in Computer Science, page 524-533. Springer, (2017)A Fast Algorithm for Clustering with MapReduce., , , , and . ISNN (1), volume 7951 of Lecture Notes in Computer Science, page 532-538. Springer, (2013)Semi-supervised Classification of Data Streams Based on Adaptive Density Peak Clustering., , and . ICONIP (2), volume 12533 of Lecture Notes in Computer Science, page 639-650. Springer, (2020)Semi-supervised Classification on Data Streams with Recurring Concept Drift Based on Conformal Prediction., , , and . ICONIP (15), volume 1969 of Communications in Computer and Information Science, page 355-366. Springer, (2023)Drift Detection for Multi-label Data Streams Based on Label Grouping and Entropy., , , and . ICDM Workshops, page 724-731. IEEE Computer Society, (2014)Multi-source Domain Adaptation for Face Recognition., , , and . ICPR, page 1349-1354. IEEE Computer Society, (2018)