5 papers
Fast counting and sampling for ferromagnetic two-spin systems
Weiming Feng, Heng Guo, Yichun Yang
We introduce two new models equivalent to ferromagnetic two-spin systems: a weighted subgraph model and a random cluster type model. Using these new connections, we obtain an effic…
An Exponential Lower Bound for Spectral Density Estimation on Unweighted Graphs
Pan Peng, Yuyang Wang, Joy Qiping Yang +1
We study lower bounds for estimating the spectral density of the normalized adjacency matrix of a graph. Previously, Cohen-Steiner et al. [KDD 2018] proposed an algorithm for $\var…
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…
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…
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…