An effective cost-sensitive sparse online learning framework for imbalanced streaming data classification and its application to online anomaly detection-Reference-Cited by-同舟云学术

An effective cost-sensitive sparse online learning framework for imbalanced streaming data classification and its application to online anomaly detection

Published:2022-09-16 Issue:1 Volume:65 Page:59-87
ISSN:0219-1377
Container-title:Knowledge and Information Systems
language:en
Short-container-title:Knowl Inf Syst

Author:

Chen Zhong^ORCID,Sheng Victor^ORCID,Edwards Andrea,Zhang Kun^ORCID

Funder

Army Research Office

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Hardware and Architecture,Human-Computer Interaction,Information Systems,Software

Link

https://link.springer.com/content/pdf/10.1007/s10115-022-01745-x.pdf

Reference42 articles.

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3. Duchi J, Singer Y (2009) Efficient online and batch learning using forward backward splitting. J Mach Learn Res 10:2899–2934

4. Langford J, Li L, Zhang T (2009) Sparse online learning via truncated gradient. In: Proceedings of advances in neural information processing systems, pp 905–912

5. Zhang Q, Zhang P, Long G, Ding W, Zhang C, Wu X (2015) Towards mining trapezoidal data streams. In: IEEE international conference on data mining, pp 1111–1116

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