4 citations · 11 across the 6 of their papers we have counts for
6 papers
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…
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…
Human-guided Robot Behavior Learning: A GAN-assisted Preference-based Reinforcement Learning Approach
Huixin Zhan, Feng Tao, Yongcan Cao
Human demonstrations can provide trustful samples to train reinforcement learning algorithms for robots to learn complex behaviors in real-world environments. However, obtaining su…
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…
Relationship Explainable Multi-objective Optimization Via Vector Value Function Based Reinforcement Learning
Huixin Zhan, Yongcan Cao
Solving multi-objective optimization problems is important in various applications where users are interested in obtaining optimal policies subject to multiple, yet often conflicti…
Relationship Explainable Multi-objective Reinforcement Learning with Semantic Explainability Generation
Huixin Zhan, Yongcan Cao
Solving multi-objective optimization problems is important in various applications where users are interested in obtaining optimal policies subject to multiple, yet often conflicti…