Tingjin Luo

Theory-Driven Label-Specific Representation for Incomplete Multi-View Multi-Label Learning

Multi-view multi-label learning typically suffers from dual data incompleteness due to limitations in feature storage and annotation costs. The interplay of heterogeneous features, numerous labels, and missing information significantly degrades model performance. To tackle the complex yet highly practical challenges, w...