3 papers
cs.CV2024
E2MPL:An Enduring and Efficient Meta Prompt Learning Framework for Few-shot Unsupervised Domain Adaptation
Wanqi Yang, Haoran Wang, Lei Wang +3
Few-shot unsupervised domain adaptation (FS-UDA) leverages a limited amount of labeled data from a source domain to enable accurate classification in an unlabeled target domain. De…
cs.CV2024
Multi-level Reliable Guidance for Unpaired Multi-view Clustering
Like Xin, Wanqi Yang, Lei Wang +1
In this thesis, we address the challenging problem of unpaired multi-view clustering (UMC), which aims to achieve effective joint clustering using unpaired samples observed across…
cs.CV2024
Unpaired Multi-view Clustering via Reliable View Guidance
Like Xin, Wanqi Yang, Lei Wang +1
This paper focuses on unpaired multi-view clustering (UMC), a challenging problem where paired observed samples are unavailable across multiple views. The goal is to perform effect…