Online reliable semi-supervised learning on evolving data streams

DOI10.1016/J.INS.2020.03.052zbMath1458.68184OpenAlexW3013371665MaRDI QIDQ2663578

Yanyan Li

Publication date: 19 April 2021

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2020.03.052

zbMATH Keywords

concept driftsemi-supervised learningevolving data streamsmicro-clusters

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05) Online algorithms; streaming algorithms (68W27)

Related Items (1)

Distributed dynamic online learning with differential privacy via path-length measurement

Uses Software

• MOA

Cites Work

• Unnamed Item
• Combining block-based and online methods in learning ensembles from concept drifting data streams
• A survey on concept drift adaptation
• Learning in Non-Stationary Environments

This page was built for publication: Online reliable semi-supervised learning on evolving data streams