117 citations · 129 across the 5 of their papers we have counts for
5 papers
Scaling Model Checking for DNN Analysis via State-Space Reduction and Input Segmentation (Extended Version)
Mahum Naseer, Osman Hasan, Muhammad Shafique
Owing to their remarkable learning capabilities and performance in real-world applications, the use of machine learning systems based on Neural Networks (NNs) has been continuously…
Poster: Link between Bias, Node Sensitivity and Long-Tail Distribution in trained DNNs
Mahum Naseer, Muhammad Shafique
Owing to their remarkable learning (and relearning) capabilities, deep neural networks (DNNs) find use in numerous real-world applications. However, the learning of these data-driv…
UnbiasedNets: A Dataset Diversification Framework for Robustness Bias Alleviation in Neural Networks
Mahum Naseer, Bharath Srinivas Prabakaran, Osman Hasan +1
Performance of trained neural network (NN) models, in terms of testing accuracy, has improved remarkably over the past several years, especially with the advent of deep learning. H…
Robust Machine Learning Systems: Challenges, Current Trends, Perspectives, and the Road Ahead
Muhammad Shafique, Mahum Naseer, Theocharis Theocharides +4
Machine Learning (ML) techniques have been rapidly adopted by smart Cyber-Physical Systems (CPS) and Internet-of-Things (IoT) due to their powerful decision-making capabilities. Ho…
FANNet: Formal Analysis of Noise Tolerance, Training Bias and Input Sensitivity in Neural Networks
Mahum Naseer, Mishal Fatima Minhas, Faiq Khalid +3
With a constant improvement in the network architectures and training methodologies, Neural Networks (NNs) are increasingly being deployed in real-world Machine Learning systems. H…