Global and local attention-based multi-label learning with missing labels

DOI10.1016/j.ins.2022.02.022OpenAlexW4213049311MaRDI QIDQ6118634

Fan Min, Kun Qian, Yu-sheng Cheng

Publication date: 28 February 2024

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

Full work available at URL: https://doi.org/10.1016/j.ins.2022.02.022

zbMATH Keywords

multi-label learninglocal featuresmissing labelattention mechanismlabel correlationglobal features

Mathematics Subject Classification ID

Computational learning theory (68Q32) Measures of association (correlation, canonical correlation, etc.) (62H20) Learning and adaptive systems in artificial intelligence (68T05) Computing methodologies for image processing (68U10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Cites Work

• Unnamed Item
• Multi-label learning with missing labels using mixed dependency graphs
• Improving multi-label classification with missing labels by learning label-specific features
• Manopt, a Matlab toolbox for optimization on manifolds
• Encyclopedia of Machine Learning and Data Mining

This page was built for publication: Global and local attention-based multi-label learning with missing labels