3 papers
cs.LG2024
The Transferability of Downsamped Sparse Graph Convolutional Networks
Qinji Shu, Hang Sheng, Feng Ji +2
To accelerate the training of graph convolutional networks (GCNs) on real-world large-scale sparse graphs, downsampling methods are commonly employed as a preprocessing step. Howev…
eess.SP2022
Sampling of Correlated Bandlimited Continuous Signals by Joint Time-vertex Graph Fourier Transform
Zhongyi Ni, Feng Ji, Hang Sheng +2
When sampling multiple signals, the correlation between the signals can be exploited to reduce the overall number of samples. In this paper, we study the sampling theory of multipl…
eess.SP2020
Sampling Theory of Bandlimited Continuous-Time Graph Signals
Feng Ji, Hui Feng, Hang Sheng +1
A continuous-time graph signal can be viewed as a time series of graph signals. It generalizes both the classical continuous-time signal and ordinary graph signal. Therefore, such…