49 citations · 139 across the 20 of their papers we have counts for
21 papers
Complete the Missing Half: Augmenting Aggregation Filtering with Diversification for Graph Convolutional Neural Networks
Sitao Luan, Mingde Zhao, Chenqing Hua +2
The core operation of current Graph Neural Networks (GNNs) is the aggregation enabled by the graph Laplacian or message passing, which filters the neighborhood information of nodes…
Complete the Missing Half: Augmenting Aggregation Filtering with Diversification for Graph Convolutional Networks
Sitao Luan, Mingde Zhao, Chenqing Hua +2
The core operation of current Graph Neural Networks (GNNs) is the aggregation enabled by the graph Laplacian or message passing, which filters the neighborhood node information. Th…
Training Matters: Unlocking Potentials of Deeper Graph Convolutional Neural Networks
Sitao Luan, Mingde Zhao, Xiao-Wen Chang +1
The performance limit of Graph Convolutional Networks (GCNs) and the fact that we cannot stack more of them to increase the performance, which we usually do for other deep learning…
Revisit Policy Optimization in Matrix Form
Sitao Luan, Xiao-Wen Chang, Doina Precup
In tabular case, when the reward and environment dynamics are known, policy evaluation can be written as , where is t…
Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks
Sitao Luan, Mingde Zhao, Xiao-Wen Chang +1
Recently, neural network based approaches have achieved significant improvement for solving large, complex, graph-structured problems. However, their bottlenecks still need to be a…
Improved Upper Bounds on the Hermite and KZ Constants
Jinming Wen, Xiao-Wen Chang, Jian Weng
The Korkine-Zolotareff (KZ) reduction is a widely used lattice reduction strategy in communications and cryptography. The Hermite constant, which is a vital constant of lattice, ha…