9 citations · 16 across the 7 of their papers we have counts for
7 papers
Pair-Centric Graph Rewiring for Over-Squashing via Optimal Transport-Guided Communication Alignment
Yan Wang, Chuan-Xian Ren
Message-passing neural networks (MPNNs) often struggle when task-relevant information is distributed across distant regions of a graph, since local propagation must compress remote…
Locality-aware Private Class Identification for Domain Adaptation with Extreme Label Shift
Chuan-Xian Ren, Cheng-Jun Guo, Hong Yan
Domain adaptation aims to transfer knowledge from a labeled source domain to an unlabeled target domain with different distributions. In real-world scenarios, the label spaces of t…
Partial Domain Adaptation via Importance Sampling-based Shift Correction
Cheng-Jun Guo, Chuan-Xian Ren, You-Wei Luo +2
Partial domain adaptation (PDA) is a challenging task in real-world machine learning scenarios. It aims to transfer knowledge from a labeled source domain to a related unlabeled ta…
Soft-Masked Semi-Dual Optimal Transport for Partial Domain Adaptation
Yi-Ming Zhai, Chuan-Xian Ren, Hong Yan
Visual domain adaptation aims to learn discriminative and domain-invariant representation for an unlabeled target domain by leveraging knowledge from a labeled source domain. Parti…
COD: Learning Conditional Invariant Representation for Domain Adaptation Regression
Hao-Ran Yang, Chuan-Xian Ren, You-Wei Luo
Aiming to generalize the label knowledge from a source domain with continuous outputs to an unlabeled target domain, Domain Adaptation Regression (DAR) is developed for complex pra…
Geometric Understanding of Discriminability and Transferability for Visual Domain Adaptation
You-Wei Luo, Chuan-Xian Ren, Xiao-Lin Xu +1
To overcome the restriction of identical distribution assumption, invariant representation learning for unsupervised domain adaptation (UDA) has made significant advances in comput…
When Invariant Representation Learning Meets Label Shift: Insufficiency and Theoretical Insights
You-Wei Luo, Chuan-Xian Ren
As a crucial step toward real-world learning scenarios with changing environments, dataset shift theory and invariant representation learning algorithm have been extensively studie…