1.2k citations · 4.2k across the 61 of their papers we have counts for
Showing 2021 · cs.LGShow all
3 papers · 2 filters
cs.LG2021★ 4 cited
Understanding Structural Vulnerability in Graph Convolutional Networks
Liang Chen, Jintang Li, Qibiao Peng +3
Recent studies have shown that Graph Convolutional Networks (GCNs) are vulnerable to adversarial attacks on the graph structure. Although multiple works have been proposed to impro…
cs.LG2021★ 130 cited
A Decentralized Federated Learning Framework via Committee Mechanism with Convergence Guarantee
Chunjiang Che, Xiaoli Li, Chuan Chen +2
Federated learning allows multiple participants to collaboratively train an efficient model without exposing data privacy. However, this distributed machine learning training metho…
cs.LG2021★ 11 cited
FedGL: Federated Graph Learning Framework with Global Self-Supervision
Chuan Chen, Weibo Hu, Ziyue Xu +1
Graph data are ubiquitous in the real world. Graph learning (GL) tries to mine and analyze graph data so that valuable information can be discovered. Existing GL methods are design…