Guest Editorial: Special Issue on Stream Learning

Jie LU, Joao GAMA, Xin YAO, Leandro MINKU

Research output: Journal PublicationsEditorial/Preface (Journal)


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. © 2012 IEEE.
Original languageEnglish
Pages (from-to)6683-6685
Number of pages3
JournalIEEE Transactions on Neural Networks and Learning Systems
Issue number10
Publication statusPublished - Oct 2023
Externally publishedYes


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