271 citations · 1.3k across the 60 of their papers we have counts for
6 papers · 1 filter
Efficient Directed Graph Sampling via Gershgorin Disc Alignment
Yuejiang Li, Hong Vicky Zhao, Gene Cheung
Graph sampling is the problem of choosing a node subset via sampling matrix to collect samples $\mathbf{y} = \mathbf{H} \mathbf{x} \in \mathbb…
Unsupervised Graph Spectral Feature Denoising for Crop Yield Prediction
Saghar Bagheri, Chinthaka Dinesh, Gene Cheung +1
Prediction of annual crop yields at a county granularity is important for national food production and price stability. In this paper, towards the goal of better crop yield predict…
Efficient Signed Graph Sampling via Balancing & Gershgorin Disc Perfect Alignment
Chinthaka Dinesh, Gene Cheung, Saghar Bagheri +1
A basic premise in graph signal processing (GSP) is that a graph encoding pairwise (anti-)correlations of the targeted signal as edge weights is exploited for graph filtering. Howe…
Manifold Graph Signal Restoration using Gradient Graph Laplacian Regularizer
Fei Chen, Gene Cheung, Xue Zhang
In the graph signal processing (GSP) literature, graph Laplacian regularizer (GLR) was used for signal restoration to promote piecewise smooth / constant reconstruction with respec…
Hybrid Model-based / Data-driven Graph Transform for Image Coding
Saghar Bagheri, Tam Thuc Do, Gene Cheung +1
Transform coding to sparsify signal representations remains crucial in an image compression pipeline. While the Karhunen-Loève transform (KLT) computed from an empirical covariance…
Sparse Graph Learning with Spectrum Prior for Deep Graph Convolutional Networks
Jin Zeng, Yang Liu, Gene Cheung +1
A graph convolutional network (GCN) employs a graph filtering kernel tailored for data with irregular structures. However, simply stacking more GCN layers does not improve performa…