3 papers
cs.LG2026
Optimization-Free Graph Embedding via Distributional Kernel for Community Detection
Shuaibin Song, Kai Ming Ting, Kaifeng Zhang +1
Neighborhood Aggregation Strategy (NAS) is a widely used approach in graph embedding, underpinning both Graph Neural Networks (GNNs) and Weisfeiler-Lehman (WL) methods. However, NA…
cs.LG2026
Rethinking Divisive Hierarchical Clustering from a Distributional Perspective
Kaifeng Zhang, Kai Ming Ting, Tianrun Liang +1
We uncover that current objective-based Divisive Hierarchical Clustering (DHC) methods produce a dendrogram that does not have three desired properties i.e., no unwarranted splitti…
stat.ML2026
Mass Distribution versus Density Distribution in the Context of Clustering
Kai Ming Ting, Ye Zhu, Hang Zhang +1
This paper investigates two fundamental descriptors of data, i.e., density distribution versus mass distribution, in the context of clustering. Density distribution has been the de…