Tensorial multiview low-rank high-order graph learning for context-enhanced domain adaptation

Chenyang Zhu, Lanlan Zhang, Weibin Luo, Guangqi Jiang, Qian Wang

Abstract: Highlights•Introduces Tensorial Multiview Low-Rank High-Order Graph Learning for enhanced UDA.•Leverages augmented masking techniques for robust domain-invariant feature generation.•Construct high-order graph with inter-view consistency and inter-class separability.•Demonstrates superior domain alignment and generalization across diverse domains.