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cs.LG2026
Learning Domain Trajectories with Flow Matching for Gradual Domain Adaptation
Yubo Huang, Yushe Cao, Zixi Wang +4
Large distribution shifts remain a primary obstacle for domain generalization and unsupervised adaptation. Although gradual domain adaptation alleviates this difficulty by introduc…
cs.LG2025
Self-Training with Dynamic Weighting for Robust Gradual Domain Adaptation
Zixi Wang, Yushe Cao, Yubo Huang +4
In this paper, we propose a new method called Self-Training with Dynamic Weighting (STDW), which aims to enhance robustness in Gradual Domain Adaptation (GDA) by addressing the cha…
cs.LG2024
Imitating from auxiliary imperfect demonstrations via Adversarial Density Weighted Regression
Ziqi Zhang, Zifeng Zhuang, Jingzehua Xu +4
We propose a novel one-step supervised imitation learning (IL) framework called Adversarial Density Regression (ADR). This IL framework aims to correct the policy learned on unknow…