2 papers
cs.LG2025
Noise May Contain Transferable Knowledge: Understanding Semi-supervised Heterogeneous Domain Adaptation from an Empirical Perspective
Yuan Yao, Xiaopu Zhang, Yu Zhang +2
Semi-supervised heterogeneous domain adaptation (SHDA) addresses learning across domains with distinct feature representations and distributions, where source samples are labeled w…
cs.CV2023
A Unified Framework for Unsupervised Domain Adaptation based on Instance Weighting
Jinjing Zhu, Feiyang Ye, Qiao Xiao +3
Despite the progress made in domain adaptation, solving Unsupervised Domain Adaptation (UDA) problems with a general method under complex conditions caused by label shifts between…