most citedCommunity Detection in the Multi-View Stochastic Block Model

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2026

Misclassification Rate and Privacy-Utility Trade-offs in Graph Convolutional Networks via Subsampling Stability

Yexin Zhang, Zhongtian Ma, Qiaosheng Zhang +1

We study differential privacy (DP) in Graph Convolutional Networks (GCNs) through the framework of \textit{subsampling stability}. We derive upper bounds on the misclassification r…

cs.LG2026

Gating and Learnable Temperature for Graph Attention Mechanisms

Zhongtian Ma, Hao Wu, Yexin Zhang +3

Graph attention networks learn neighbor importance through data-dependent coefficients, but standard layers lack explicit control over unreliable feature dimensions and use fixed s…

cs.LG2024

Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models

Zhongtian Ma, Qiaosheng Zhang, Bocheng Zhou +3

Despite the growing popularity of graph attention mechanisms, their theoretical understanding remains limited. This paper aims to explore the conditions under which these mechanism…

cs.SI2024★ 1 cited

Community Detection in the Multi-View Stochastic Block Model

Yexin Zhang, Zhongtian Ma, Qiaosheng Zhang +2

This paper considers the problem of community detection on multiple potentially correlated graphs from an information-theoretical perspective. We first put forth a random graph mod…

cs.LG2024

Matrix Completion with Hypergraphs:Sharp Thresholds and Efficient Algorithms

Zhongtian Ma, Qiaosheng Zhang, Zhen Wang

This paper considers the problem of completing a rating matrix based on sub-sampled matrix entries as well as observed social graphs and hypergraphs. We show that there exists a \e…