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Vikash Sehwag
Vikash Sehwag
Verified email at princeton.edu - Homepage
Title
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Cited by
Year
Robustbench: a standardized adversarial robustness benchmark
F Croce, M Andriushchenko, V Sehwag, E Debenedetti, N Flammarion, ...
arXiv preprint arXiv:2010.09670, 2020
1652020
Ssd: A unified framework for self-supervised outlier detection
V Sehwag, M Chiang, P Mittal
arXiv preprint arXiv:2103.12051, 2021
902021
Hydra: Pruning adversarially robust neural networks
V Sehwag, S Wang, P Mittal, S Jana
Advances in Neural Information Processing Systems 33, 19655-19666, 2020
802020
Fast-convergent federated learning
HT Nguyen, V Sehwag, S Hosseinalipour, CG Brinton, M Chiang, ...
IEEE Journal on Selected Areas in Communications 39 (1), 201-218, 2020
662020
{PatchGuard}: A Provably Robust Defense against Adversarial Patches via Small Receptive Fields and Masking
C Xiang, AN Bhagoji, V Sehwag, P Mittal
30th USENIX Security Symposium (USENIX Security 21), 2237-2254, 2021
422021
Analyzing the robustness of open-world machine learning
V Sehwag, AN Bhagoji, L Song, C Sitawarin, D Cullina, M Chiang, P Mittal
Proceedings of the 12th ACM Workshop on Artificial Intelligence and Security …, 2019
412019
Robust learning meets generative models: Can proxy distributions improve adversarial robustness?
V Sehwag, S Mahloujifar, T Handina, S Dai, C Xiang, M Chiang, P Mittal
arXiv preprint arXiv:2104.09425, 2021
31*2021
Towards compact and robust deep neural networks
V Sehwag, S Wang, P Mittal, S Jana
arXiv preprint arXiv:1906.06110, 2019
222019
TV-PUF: a fast lightweight analog physical unclonable function
V Sehwag, T Saha
2016 IEEE International Symposium on Nanoelectronic and Information Systems …, 2016
202016
On pruning adversarially robust neural networks
V Sehwag, S Wang, P Mittal, S Jana
142020
Time for a background check! uncovering the impact of background features on deep neural networks
V Sehwag, R Oak, M Chiang, P Mittal
arXiv preprint arXiv:2006.14077, 2020
132020
A parallel stochastic number generator with bit permutation networks
V Sehwag, N Prasad, I Chakrabarti
IEEE Transactions on Circuits and Systems II: Express Briefs 65 (2), 231-235, 2017
122017
A critical evaluation of open-world machine learning
L Song, V Sehwag, AN Bhagoji, P Mittal
arXiv preprint arXiv:2007.04391, 2020
112020
Not all pixels are born equal: An analysis of evasion attacks under locality constraints
V Sehwag, C Sitawarin, AN Bhagoji, A Mosenia, M Chiang, P Mittal
Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications …, 2018
72018
Better the devil you know: An analysis of evasion attacks using out-of-distribution adversarial examples
V Sehwag, AN Bhagoji, L Song, C Sitawarin, D Cullina, M Chiang, P Mittal
arXiv preprint arXiv:1905.01726, 2019
62019
Lower Bounds on Cross-Entropy Loss in the Presence of Test-time Adversaries
AN Bhagoji, D Cullina, V Sehwag, P Mittal
International Conference on Machine Learning, 863-873, 2021
32021
Variation aware performance analysis of tfets for low-voltage computing
V Sehwag, S Maji, M Sharad
2016 IEEE International Symposium on Nanoelectronic and Information Systems …, 2016
32016
Generating High Fidelity Data from Low-density Regions using Diffusion Models
V Sehwag, C Hazirbas, A Gordo, F Ozgenel, C Canton
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
22022
Embedding delay‐based physical unclonable functions in networks‐on‐chip
P Nagabhushanamgari, V Sehwag, I Chakrabarti, S Chattopadhyay
IET Circuits, Devices & Systems 15 (1), 27-41, 2021
12021
POSTER: Not All Pixels are Born Equal: An Analysis of Evasion Attacks under Locality Constraints. 18
V Sehwag, C Sitawarin, AN Bhagoji, A Mosenia, M Chiang, P Mittal
12018
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