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Mahum Naseer
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Robust machine learning systems: Challenges, current trends, perspectives, and the road ahead
M Shafique, M Naseer, T Theocharides, C Kyrkou, O Mutlu, L Orosa, ...
IEEE Design & Test 37 (2), 30-57, 2020
1192020
Fannet: Formal analysis of noise tolerance, training bias and input sensitivity in neural networks
M Naseer, MF Minhas, F Khalid, MA Hanif, O Hasan, M Shafique
2020 design, automation & test in Europe conference & exhibition (date), 666-669, 2020
172020
UnbiasedNets: a dataset diversification framework for robustness bias alleviation in neural networks
M Naseer, BS Prabakaran, O Hasan, M Shafique
Machine Learning, 1-28, 2023
32023
A formal approach to identifying the impact of noise on neural networks
IT Bhatti, M Naseer, M Shafique, O Hasan
Communications of the ACM 65 (11), 70-73, 2022
32022
Formal verification of ECCs for memories using ACL2
M Naseer, W Ahmad, O Hasan
Journal of Electronic Testing 36 (5), 643-663, 2020
22020
Robust Machine Learning Systems: Challenges, Current Trends, Perspectives, and the Road Ahead.—2020.—
MSMNT Theocharides
URL: https://ieeexplore. ieee. org/document/8979377, 0
2
Scaling Model Checking for DNN Analysis via State-Space Reduction and Input Segmentation (Extended Version)
M Naseer, O Hasan, M Shafique
arXiv preprint arXiv:2306.17323, 2023
2023
Poster: Link between Bias, Node Sensitivity and Long-Tail Distribution in trained DNNs
M Naseer, M Shafique
2023 IEEE Conference on Software Testing, Verification and Validation (ICST …, 2023
2023
Considering the Impact of Noise on Machine Learning Accuracy
M Naseer, IT Bhatti, O Hasan, M Shafique
Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing …, 2023
2023
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