3 papers
cs.LG2025
Structure-Attribute Transformations with Markov Chain Boost Graph Domain Adaptation
Zhen Liu, Yongtao Zhang, Shaobo Ren +1
Graph domain adaptation has gained significant attention in label-scarce scenarios across different graph domains. Traditional approaches to graph domain adaptation primarily focus…
cs.LG2025
Data Skeleton Learning: Scalable Active Clustering with Sparse Graph Structures
Wen-Bo Xie, Xun Fu, Bin Chen +6
In this work, we focus on the efficiency and scalability of pairwise constraint-based active clustering, crucial for processing large-scale data in applications such as data mining…
cs.LG2024
Large Language Models Meet Graph Neural Networks: A Perspective of Graph Mining
Yuxin You, Zhen Liu, Xiangchao Wen +2
Graph mining is an important area in data mining and machine learning that involves extracting valuable information from graph-structured data. In recent years, significant progres…