3 citations · 3 across the 4 of their papers we have counts for
5 papers
Weight-Informed Self-Explaining Clustering for Mixed-Type Tabular Data
Lehao Li, Qiang Huang, Yihao Ang +3
Clustering mixed-type tabular data is fundamental for exploratory analysis, yet remains challenging due to misaligned numerical-categorical representations, uneven and context-depe…
GegenNet: Spectral Convolutional Neural Networks for Link Sign Prediction in Signed Bipartite Graphs
Hewen Wang, Renchi Yang, Xiaokui Xiao
Given a signed bipartite graph (SBG) G with two disjoint node sets U and V, the goal of link sign prediction is to predict the signs of potential links connecting U and V based on…
Rethinking Link Prediction for Directed Graphs
Mingguo He, Yuhe Guo, Yanping Zheng +3
Link prediction for directed graphs is a crucial task with diverse real-world applications. Recent advances in embedding methods and Graph Neural Networks (GNNs) have shown promisi…
Effective Edge-wise Representation Learning in Edge-Attributed Bipartite Graphs
Hewen Wang, Renchi Yang, Xiaokui Xiao
Graph representation learning (GRL) is to encode graph elements into informative vector representations, which can be used in downstream tasks for analyzing graph-structured data a…
Fast Approximate CoSimRanks via Random Projections
Renchi Yang, Xiaokui Xiao
Given a graph with nodes and two nodes , the {\em CoSimRank} value quantifies the similarity between and based on graph topology. Compared to Sim…