10 citations · 11 across the 5 of their papers we have counts for
5 papers
Mining Verdict Boundaries for Neural Network Verification
Jiawei Ren, Guanqin Zhang, Zhenya Zhang +1
Branch and Bound (BaB) aims to achieve complete verification of neural networks by adaptively partitioning the problem and applying off-the-shelf verifiers to subproblems. Its prob…
Knowledge Priors for Identity-Disentangled Open-Set Privacy-Preserving Video FER
Feng Xu, Xun Li, Lars Petersson +3
Facial expression recognition relies on facial data that inherently expose identity and thus raise significant privacy concerns. Current privacy-preserving methods typically fail i…
Efficient Neural Network Verification via Order Leading Exploration of Branch-and-Bound Trees
Guanqin Zhang, Kota Fukuda, Zhenya Zhang +4
The vulnerability of neural networks to adversarial perturbations has necessitated formal verification techniques that can rigorously certify the quality of neural networks. As the…
Adaptive Branch-and-Bound Tree Exploration for Neural Network Verification
Kota Fukuda, Guanqin Zhang, Zhenya Zhang +2
Formal verification is a rigorous approach that can provably ensure the quality of neural networks, and to date, Branch and Bound (BaB) is the state-of-the-art that performs verifi…
Does Your Neural Code Completion Model Use My Code? A Membership Inference Approach
Yao Wan, Guanghua Wan, Shijie Zhang +4
Recent years have witnessed significant progress in developing deep learning-based models for automated code completion. Although using source code in GitHub has been a common prac…