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Peter Kairouz
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Advances and open problems in federated learning
P Kairouz, HB McMahan, B Avent, A Bellet, M Bennis, AN Bhagoji, ...
Foundations and Trends® in Machine Learning 14 (1–2), 1-210, 2021
48352021
The composition theorem for differential privacy
P Kairouz, S Oh, P Viswanath
IEEE Transactions on Information Theory 63 (6), 4037-4049, 2017
6802017
Extremal mechanisms for local differential privacy
P Kairouz, S Oh, P Viswanath
The Journal of Machine Learning Research 17 (1), 492-542, 2016
6002016
Can you really backdoor federated learning?
Z Sun, P Kairouz, AT Suresh, HB McMahan
arXiv preprint arXiv:1911.07963, 2019
4952019
Discrete distribution estimation under local privacy
P Kairouz, K Bonawitz, D Ramage
International Conference on Machine Learning, 2436-2444, 2016
3442016
Dp-cgan: Differentially private synthetic data and label generation
R Torkzadehmahani, P Kairouz, B Paten
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
2132019
A general approach to adding differential privacy to iterative training procedures
HB McMahan, G Andrew, U Erlingsson, S Chien, I Mironov, N Papernot, ...
arXiv preprint arXiv:1812.06210, 2018
1942018
Back to the drawing board: A critical evaluation of poisoning attacks on production federated learning
V Shejwalkar, A Houmansadr, P Kairouz, D Ramage
2022 IEEE Symposium on Security and Privacy (SP), 1354-1371, 2022
1782022
A field guide to federated optimization
J Wang, Z Charles, Z Xu, G Joshi, HB McMahan, M Al-Shedivat, G Andrew, ...
arXiv preprint arXiv:2107.06917, 2021
1782021
Generative models for effective ML on private, decentralized datasets
S Augenstein, HB McMahan, D Ramage, S Ramaswamy, P Kairouz, ...
arXiv preprint arXiv:1911.06679, 2019
1752019
The staircase mechanism in differential privacy
Q Geng, P Kairouz, S Oh, P Viswanath
IEEE Journal of Selected Topics in Signal Processing 9 (7), 1176-1184, 2015
1722015
The distributed discrete gaussian mechanism for federated learning with secure aggregation
P Kairouz, Z Liu, T Steinke
International Conference on Machine Learning, 5201-5212, 2021
1712021
Context-aware generative adversarial privacy
C Huang, P Kairouz, X Chen, L Sankar, R Rajagopal
Entropy 19 (12), 656, 2017
1602017
Shuffled model of differential privacy in federated learning
A Girgis, D Data, S Diggavi, P Kairouz, AT Suresh
International Conference on Artificial Intelligence and Statistics, 2521-2529, 2021
1492021
Mariana Raykova, Dawn Song, Weikang Song, Sebastian U
P Kairouz, HB McMahan, B Avent, A Bellet, M Bennis, AN Bhagoji, ...
Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth …, 2021
1222021
Breaking the communication-privacy-accuracy trilemma
WN Chen, P Kairouz, A Ozgur
Advances in Neural Information Processing Systems 33, 3312-3324, 2020
1062020
Practical and private (deep) learning without sampling or shuffling
P Kairouz, B McMahan, S Song, O Thakkar, A Thakurta, Z Xu
International Conference on Machine Learning, 5213-5225, 2021
1052021
Federated heavy hitters discovery with differential privacy
W Zhu, P Kairouz, B McMahan, H Sun, W Li
International Conference on Artificial Intelligence and Statistics, 3837-3847, 2020
982020
The skellam mechanism for differentially private federated learning
N Agarwal, P Kairouz, Z Liu
Advances in Neural Information Processing Systems 34, 5052-5064, 2021
792021
Privacy-first health research with federated learning
A Sadilek, L Liu, D Nguyen, M Kamruzzaman, S Serghiou, B Rader, ...
NPJ digital medicine 4 (1), 132, 2021
742021
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