49 citations · 60 across the 11 of their papers we have counts for
4 papers · 1 filter
FairQuant: Certifying and Quantifying Fairness of Deep Neural Networks
Brian Hyeongseok Kim, Jingbo Wang, Chao Wang
We propose a method for formally certifying and quantifying individual fairness of deep neural networks (DNN). Individual fairness guarantees that any two individuals who are ident…
Certifying the Fairness of KNN in the Presence of Dataset Bias
Yannan Li, Jingbo Wang, Chao Wang
We propose a method for certifying the fairness of the classification result of a widely used supervised learning algorithm, the k-nearest neighbors (KNN), under the assumption tha…
NeuroDiff: Scalable Differential Verification of Neural Networks using Fine-Grained Approximation
Brandon Paulsen, Jingbo Wang, Jiawei Wang +1
As neural networks make their way into safety-critical systems, where misbehavior can lead to catastrophes, there is a growing interest in certifying the equivalence of two structu…
ReluDiff: Differential Verification of Deep Neural Networks
Brandon Paulsen, Jingbo Wang, Chao Wang
As deep neural networks are increasingly being deployed in practice, their efficiency has become an important issue. While there are compression techniques for reducing the network…