22 citations · 53 across the 7 of their papers we have counts for
7 papers
Collaborate to Adapt: Source-Free Graph Domain Adaptation via Bi-directional Adaptation
Zhen Zhang, Meihan Liu, Anhui Wang +4
Unsupervised Graph Domain Adaptation (UGDA) has emerged as a practical solution to transfer knowledge from a label-rich source graph to a completely unlabelled target graph. Howeve…
Rethinking Propagation for Unsupervised Graph Domain Adaptation
Meihan Liu, Zeyu Fang, Zhen Zhang +4
Unsupervised Graph Domain Adaptation (UGDA) aims to transfer knowledge from a labelled source graph to an unlabelled target graph in order to address the distribution shifts betwee…
Sequence-Based Target Coin Prediction for Cryptocurrency Pump-and-Dump
Sihao Hu, Zhen Zhang, Shengliang Lu +2
With the proliferation of pump-and-dump schemes (P&Ds) in the cryptocurrency market, it becomes imperative to detect such fraudulent activities in advance to alert potentially susc…
Semi-Supervised Hypothesis Transfer for Source-Free Domain Adaptation
Ning Ma, Jiajun Bu, Lixian Lu +4
Domain Adaptation has been widely used to deal with the distribution shift in vision, language, multimedia etc. Most domain adaptation methods learn domain-invariant features with…
Uncertainty-Guided Mixup for Semi-Supervised Domain Adaptation without Source Data
Ning Ma, Jiajun Bu, Zhen Zhang +1
Present domain adaptation methods usually perform explicit representation alignment by simultaneously accessing the source data and target data. However, the source data are not al…
Cyclic Label Propagation for Graph Semi-supervised Learning
Zhao Li, Yixin Liu, Zhen Zhang +3
Graph neural networks (GNNs) have emerged as effective approaches for graph analysis, especially in the scenario of semi-supervised learning. Despite its success, GNN often suffers…
Adaptive-Step Graph Meta-Learner for Few-Shot Graph Classification
Ning Ma, Jiajun Bu, Jieyu Yang +5
Graph classification aims to extract accurate information from graph-structured data for classification and is becoming more and more important in graph learning community. Althoug…