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Article
Dynamic principal projection for cost-sensitive online multi-label classification
We study multi-label classification (MLC) with three important real-world issues: online updating, label space dimension reduction (LSDR), and cost-sensitivity. Current MLC algorithms have not been designed to...
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Chapter and Conference Paper
Deep Generative Models for Weakly-Supervised Multi-Label Classification
In order to train learning models for multi-label classification (MLC), it is typically desirable to have a large amount of fully annotated multi-label data. Since such annotation process is in general costly,...
