Shixuan Zhou

Progressive Adversarial Multi-View Alignment for Unsupervised Embedded Feature Selection with Linear Complexity

Standard unsupervised multi-view feature selection (UMFS) methods for large datasets exhibit limitations in modeling the competition between cross-view alignment and intra-view diversity, resulting in suboptimal solutions and expensive computational costs. This challenge is exacerbated by the divers