1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CR2026
Privacy-Preserving Robustness Verification for Neural Networks
Nianyun Song, Xiaokun Luan, Yu Guo +3
Neural network verification and data privacy are inherently in tension: verification demands full access to model parameters and input data, yet both are increasingly restricted by…
cs.LG2020★ 1 cited
Global Robustness Verification Networks
Weidi Sun, Yuteng Lu, Xiyue Zhang +2
The wide deployment of deep neural networks, though achieving great success in many domains, has severe safety and reliability concerns. Existing adversarial attack generation and…
cs.SE2016★ 1 cited
Towards Concolic Testing for Hybrid Systems
Pingfan Kong, Yi Li, Xiaohong Chen +3
Hybrid systems exhibit both continuous and discrete behavior. Analyzing hybrid systems is known to be hard. Inspired by the idea of concolic testing (of programs), we investigate w…