241 citations · 861 across the 54 of their papers we have counts for
5 papers · 1 filter
Characterizing Adversarial Examples Based on Spatial Consistency Information for Semantic Segmentation
Chaowei Xiao, Ruizhi Deng, Bo Li +3
Deep Neural Networks (DNNs) have been widely applied in various recognition tasks. However, recently DNNs have been shown to be vulnerable against adversarial examples, which can m…
Recycled ADMM: Improve Privacy and Accuracy with Less Computation in Distributed Algorithms
Xueru Zhang, Mohammad Mahdi Khalili, Mingyan Liu
Alternating direction method of multiplier (ADMM) is a powerful method to solve decentralized convex optimization problems. In distributed settings, each node performs computation…
MeshAdv: Adversarial Meshes for Visual Recognition
Chaowei Xiao, Dawei Yang, Bo Li +2
Highly expressive models such as deep neural networks (DNNs) have been widely applied to various applications. However, recent studies show that DNNs are vulnerable to adversarial…
Spatially Transformed Adversarial Examples
Chaowei Xiao, Jun-Yan Zhu, Bo Li +3
Recent studies show that widely used deep neural networks (DNNs) are vulnerable to carefully crafted adversarial examples. Many advanced algorithms have been proposed to generate a…
Generating Adversarial Examples with Adversarial Networks
Chaowei Xiao, Bo Li, Jun-Yan Zhu +3
Deep neural networks (DNNs) have been found to be vulnerable to adversarial examples resulting from adding small-magnitude perturbations to inputs. Such adversarial examples can mi…