Ambrish Rawat
Ambrish Rawat
Senior Research Scientist, IBM Research
Verified email at - Homepage
Cited by
Cited by
Adversarial Robustness Toolbox v1. 0.0
MI Nicolae, M Sinn, MN Tran, B Buesser, A Rawat, M Wistuba, ...
arXiv preprint arXiv:1807.01069, 2018
A survey on neural architecture search
M Wistuba, A Rawat, T Pedapati
arXiv preprint arXiv:1905.01392, 2019
Efficient defenses against adversarial attacks
V Zantedeschi, MI Nicolae, A Rawat
Proceedings of the 10th ACM workshop on artificial intelligence and security …, 2017
Ibm federated learning: an enterprise framework white paper v0. 1
H Ludwig, N Baracaldo, G Thomas, Y Zhou, A Anwar, S Rajamoni, Y Ong, ...
arXiv preprint arXiv:2007.10987, 2020
Federated unlearning: How to efficiently erase a client in fl?
A Halimi, S Kadhe, A Rawat, N Baracaldo
arXiv preprint arXiv:2207.05521, 2022
Adversarial phenomenon in the eyes of Bayesian deep learning
A Rawat, M Wistuba, MI Nicolae
arXiv preprint arXiv:1711.08244, 2017
FAT: Federated Adversarial Training
G Zizzo, A Rawat, M Sinn, B Buesser
arXiv preprint arXiv:2012.01791, 2020
Adversarial Robustness Toolbox v1. 0.0. arXiv 2018
MI Nicolae, M Sinn, MN Tran, B Buesser, A Rawat, M Wistuba, ...
arXiv preprint arXiv:1807.01069, 1807
Survey on Automated End-to-End Data Science
D Bouneffouf, C Aggarwal, H Samulowitz, B Buesser, T Hoang, ...
2020 International Joint Conference on Neural Networks (IJCNN), 1-9, 2020
Non-parametric estimation of jensen-shannon divergence in generative adversarial network training
M Sinn, A Rawat
International Conference on Artificial Intelligence and Statistics, 642-651, 2018
The devil is in the GAN: backdoor attacks and defenses in deep generative models
A Rawat, K Levacher, M Sinn
European Symposium on Research in Computer Security, 776-783, 2022
Searching for machine learning pipelines using a context-free grammar
R Marinescu, A Kishimoto, P Ram, A Rawat, M Wistuba, PP Palmes, ...
Proceedings of the AAAI Conference on Artificial Intelligence 35 (10), 8902-8911, 2021
Open-world visual recognition using knowledge graphs
V Lonij, A Rawat, MI Nicolae
arXiv preprint arXiv:1708.08310, 2017
Towards an accountable and reproducible federated learning: A FactSheets approach
N Baracaldo, A Anwar, M Purcell, A Rawat, M Sinn, B Altakrouri, D Balta, ...
arXiv preprint arXiv:2202.12443, 2022
Certified federated adversarial training
G Zizzo, A Rawat, M Sinn, S Maffeis, C Hankin
arXiv preprint arXiv:2112.10525, 2021
Protecting a machine learning model
NM Tran, M Sinn, A Rawat, MI Nicolae, M Wistuba
US Patent 11,036,857, 2021
Machine learning platform for extreme scale computing on compressed IoT data
S Tirupathi, D Salwala, G Zizzo, A Rawat, M Purcell, SK Jensen, ...
2022 IEEE International Conference on Big Data (Big Data), 3179-3185, 2022
Learning input preprocessing to harden machine learning models
NM Tran, M Sinn, MI Nicolae, M Wistuba, A Rawat, B Buesser
US Patent 11,681,796, 2023
Bandit limited discrepancy search and application to machine learning pipeline optimization
A Kishimoto, D Bouneffouf, R Marinescu, P Ram, A Rawat, M Wistuba, ...
Proceedings of the AAAI Conference on Artificial Intelligence 36 (9), 10228 …, 2022
Fairsisa: Ensemble post-processing to improve fairness of unlearning in llms
SR Kadhe, A Halimi, A Rawat, N Baracaldo
arXiv preprint arXiv:2312.07420, 2023
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