6 citations · 9 across the 4 of their papers we have counts for
4 papers
A Tale of Two Approximations: Tightening Over-Approximation for DNN Robustness Verification via Under-Approximation
Zhiyi Xue, Si Liu, Zhaodi Zhang +2
The robustness of deep neural networks (DNNs) is crucial to the hosting system's reliability and security. Formal verification has been demonstrated to be effective in providing pr…
DETR with Additional Global Aggregation for Cross-domain Weakly Supervised Object Detection
Zongheng Tang, Yifan Sun, Si Liu +1
This paper presents a DETR-based method for cross-domain weakly supervised object detection (CDWSOD), aiming at adapting the detector from source to target domain through weak supe…
Boosting Verified Training for Robust Image Classifications via Abstraction
Zhaodi Zhang, Zhiyi Xue, Yang Chen +4
This paper proposes a novel, abstraction-based, certified training method for robust image classifiers. Via abstraction, all perturbed images are mapped into intervals before feedi…
Provably Tightest Linear Approximation for Robustness Verification of Sigmoid-like Neural Networks
Zhaodi Zhang, Yiting Wu, Si Liu +2
The robustness of deep neural networks is crucial to modern AI-enabled systems and should be formally verified. Sigmoid-like neural networks have been adopted in a wide range of ap…