Unsupervised Representation Learning with Adaptive Multi-Order Structural Graph Fusion
High-dimensional unlabeled data often contain complex latent structures that are easily obscured by redundant features, noise, and unreliable neighborhood relationships. Although graph-based learning provides an effective means of preserving sample relationships, most existing methods mainly rely on first-order neighbo...