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Guest Editorial: Special Issue on Stream Learning

delete2023-10-01
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OA
AI
J
Jie Lü *
J
João Gama
X
Xin Yao
L
Leandro L. Minku
DOI:10.1109/TNNLS.2023.3304146delete
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摘要

摘要

En 中文
In recent years, learning from streaming data, commonly known as stream learning, has enjoyed tremendous growth and shown a wealth of development at both the conceptual and application levels. Stream learning is highly visible in both the machine learning and data science fields and has become a hot new direction in research. Advancements in stream learning include learning with concept drift detection, that includes whether a drift has occurred; understanding where, when, and how a drift occurs; adaptation by actively or passively updating models; and online learning, active learning, incremental learning, and reinforcement learning in data streaming situations.
Keyword:
Special issues and sections
Streaming media
Learning systems
Reinforcement learning

期刊

IEEE Transactions on Neural Networks and Learning Systems 封面图
IEEE Transactions on Neural Networks and Learning Systems
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University of Birmingham
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