2 papers
cs.LG2026
S2O: Enhancing Adversarial Training with Second-Order Statistics of Weights
Gaojie Jin, Xinping Yi, Wei Huang +2
Adversarial training has emerged as a highly effective way to improve the robustness of deep neural networks (DNNs). It is typically conceptualized as a min-max optimization proble…
cs.LG2024
Adversarial Training for Graph Neural Networks via Graph Subspace Energy Optimization
Ganlin Liu, Ziling Liang, Xiaowei Huang +2
Despite impressive capability in learning over graph-structured data, graph neural networks (GNN) suffer from adversarial topology perturbation in both training and inference phase…