3 papers
cs.LG2026
Theoretically and Practically Efficient Resistance Distance Computation on Large Graphs
Yichun Yang, Longlong Lin, Rong-Hua Li +2
The computation of resistance distance is pivotal in a wide range of graph analysis applications, including graph clustering, link prediction, and graph neural networks. Despite it…
cs.DS2025
Improved Algorithms for Effective Resistance Computation on Graphs
Yichun Yang, Rong-Hua Li, Meihao Liao +1
Effective Resistance (ER) is a fundamental tool in various graph learning tasks. In this paper, we address the problem of efficiently approximating ER on a graph $\mathcal{G}=(\mat…
cs.LG2024
Scaling Up Graph Propagation Computation on Large Graphs: A Local Chebyshev Approximation Approach
Yichun Yang, Rong-Hua Li, Meihao Liao +2
Graph propagation (GP) computation plays a crucial role in graph data analysis, supporting various applications such as graph node similarity queries, graph node ranking, graph clu…