1 citations · 2 across the 8 of their papers we have counts for
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Probabilistic Guarantees for Practical LIA Loop Invariant Automation
Ashish Kumar, Jilaun Zhang, Saeid Tizpaz-Niari +1
Despite the crucial need for formal safety and security verification of programs, discovering loop invariants remains a significant challenge. Static analysis is a primary techniqu…
NeuFair: Neural Network Fairness Repair with Dropout
Vishnu Asutosh Dasu, Ashish Kumar, Saeid Tizpaz-Niari +1
This paper investigates neuron dropout as a post-processing bias mitigation for deep neural networks (DNNs). Neural-driven software solutions are increasingly applied in socially c…
FairLay-ML: Intuitive Debugging of Fairness in Data-Driven Social-Critical Software
Normen Yu, Luciana Carreon, Gang Tan +1
Data-driven software solutions have significantly been used in critical domains with significant socio-economic, legal, and ethical implications. The rapid adoptions of data-driven…