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Chapter and Conference Paper
Towards Cost-Sensitive Learning for Real-World Applications
Many research work in cost-sensitive learning focused on binary class problems and assumed that the costs are precise. But real-world applications often have multiple classes and the costs cannot be obtained p...
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Chapter and Conference Paper
Crest: Cluster-based Representation Enrichment for Short Text Classification
Text classification has gained research interests for decades. Many techniques have been developed and have demonstrated very good classification accuracies in various applications. Recently, the popularity of...
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Article
Binary relevance for multi-label learning: an overview
Multi-label learning deals with problems where each example is represented by a single instance while being associated with multiple class labels simultaneously. Binary relevance is arguably the most intuitive...
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Article
Transfer synthetic over-sampling for class-imbalance learning with limited minority class data
The problem of limited minority class data is encountered in many class imbalanced applications, but has received little attention. Synthetic over-sampling, as popular class-imbalance learning methods, could i...
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Article
Inhibition of perilipin 2 attenuates cerebral ischemia/reperfusion injury by blocking NLRP3 inflammasome activation both in vivo and in vitro
Cerebral ischemia/reperfusion (CI/R) usually causes neuroinflammation within the central nervous system, further prompting irreversible cerebral dysfunction. Perilipin 2 (Plin2), a lipid droplet protein, has b...
