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Learn++.MT: A New Approach to Incremental Learning.

, , and . Multiple Classifier Systems, volume 3077 of Lecture Notes in Computer Science, page 52-61. Springer, (2004)

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Semi-supervised learning in initially labeled non-stationary environments with gradual drift., and . IJCNN, page 1-9. IEEE, (2012)Incremental Learning of Concept Drift from Streaming Imbalanced Data., and . IEEE Trans. Knowl. Data Eng., 25 (10): 2283-2301 (2013)Core support extraction for learning from initially labeled nonstationary environments using COMPOSE., , and . IJCNN, page 602-608. IEEE, (2014)Incremental Learning of Concept Drift in Nonstationary Environments., and . IEEE Trans. Neural Networks, 22 (10): 1517-1531 (2011)Adversarial Poisoning of Importance Weighting in Domain Adaptation., , and . SSCI, page 381-388. IEEE, (2018)Classification of Volatile Organic Compounds with Incremental SVMs and RBF Networks., , , and . ISCIS, volume 3733 of Lecture Notes in Computer Science, page 322-331. Springer, (2005)Can AdaBoost.M1 Learn Incrementally? A Comparison to Learn++ Under Different Combination Rules., , , and . ICANN (1), volume 4131 of Lecture Notes in Computer Science, page 254-263. Springer, (2006)An architecture for intelligent systems based on smart sensors., , , , and . IEEE Trans. Instrumentation and Measurement, 54 (4): 1612-1616 (2005)Learning in Nonstationary Environments: A Survey., , , and . IEEE Comput. Intell. Mag., 10 (4): 12-25 (2015)Information-theoretic approaches to SVM feature selection for metagenome read classification., , , , and . Comput. Biol. Chem., 35 (3): 199-209 (2011)