4 citations · 11 across the 6 of their papers we have counts for
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cs.LG2023
Privacy-Preserving Representation Learning for Text-Attributed Networks with Simplicial Complexes
Huixin Zhan, Victor S. Sheng
Although recent network representation learning (NRL) works in text-attributed networks demonstrated superior performance for various graph inference tasks, learning network repres…
cs.LG2023★ 1 cited
Measuring the Privacy Leakage via Graph Reconstruction Attacks on Simplicial Neural Networks (Student Abstract)
Huixin Zhan, Kun Zhang, Keyi Lu +1
In this paper, we measure the privacy leakage via studying whether graph representations can be inverted to recover the graph used to generate them via graph reconstruction attack…
cs.LG2019
Deep Model Compression Via Two-Stage Deep Reinforcement Learning
Huixin Zhan, Wei-Ming Lin, Yongcan Cao
Besides accuracy, the model size of convolutional neural networks (CNN) models is another important factor considering limited hardware resources in practical applications. For exa…