Multi-label classification with weak labels by learning label correlation and label regularization

In conventional multi-label learning, each training instance is associated with multiple available labels. Nevertheless, real-world objects usually exhibit more sophisticated properties such as abundant irrelevant features, incomplete labels, noisy labels, as well as class imbalance. Unfortunately,...

Ausführliche Beschreibung