1 citations · 2 across the 4 of their papers we have counts for
4 papers
Bayesian Layer Graph Convolutioanl Network for Hyperspetral Image Classification
Mingyang Zhang, Ziqi Di, Maoguo Gong +3
In recent years, research on hyperspectral image (HSI) classification has continuous progress on introducing deep network models, and recently the graph convolutional network (GCN)…
Towards Consistency and Complementarity: A Multiview Graph Information Bottleneck Approach
Xiaolong Fan, Maoguo Gong, Yue Wu +3
The empirical studies of Graph Neural Networks (GNNs) broadly take the original node feature and adjacency relationship as singleview input, ignoring the rich information of multip…
ADDS: Adaptive Differentiable Sampling for Robust Multi-Party Learning
Maoguo Gong, Yuan Gao, Yue Wu +1
Distributed multi-party learning provides an effective approach for training a joint model with scattered data under legal and practical constraints. However, due to the quagmire o…
Multi-Party Dual Learning
Maoguo Gong, Yuan Gao, Yu Xie +3
The performance of machine learning algorithms heavily relies on the availability of a large amount of training data. However, in reality, data usually reside in distributed partie…