6 citations · 8 across the 5 of their papers we have counts for
4 papers · 1 filter
Rethinking Client Drift in Federated Learning: A Logit Perspective
Yunlu Yan, Chun-Mei Feng, Mang Ye +5
Federated Learning (FL) enables multiple clients to collaboratively learn in a distributed way, allowing for privacy protection. However, the real-world non-IID data will lead to c…
Steering Graph Neural Networks with Pinning Control
Acong Zhang, Ping Li, Guanrong Chen
In the semi-supervised setting where labeled data are largely limited, it remains to be a big challenge for message passing based graph neural networks (GNNs) to learn feature repr…
Building Shortcuts between Distant Nodes with Biaffine Mapping for Graph Convolutional Networks
Acong Zhang, Jincheng Huang, Ping Li +1
Multiple recent studies show a paradox in graph convolutional networks (GCNs), that is, shallow architectures limit the capability of learning information from high-order neighbors…
Graph Kernels via Functional Embedding
Anshumali Shrivastava, Ping Li
We propose a representation of graph as a functional object derived from the power iteration of the underlying adjacency matrix. The proposed functional representation is a graph i…