Multiclass imbalance is a challenging problem in real-world datasets, where certain classes
may have a low number of samples because they correspond to rare occurrences. To …

The imbalance issue significantly deteriorates the performance of classifiers. While
researchers proposed resampling methods to address this problem, it often struggles with …

While adversarial link information like the commonly used must-link and cannot-link
constraints on training data are available, the existing AUC maximization learning …

Class imbalance is one of the most significant difficulties in modern machine learning. This
is because of the inherent bias of standard classifiers toward favoring majority instances …

The primary objective of research concerning class imbalance problems revolves around
the generation of high-quality data for minority classes. Prior investigations have witnessed …

Abstract Language and society are a pair of covariance; language reflects the changes in
society, and the changes in society have an important impact on the language. The …