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Badih Ghazi
Badih Ghazi
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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
65512021
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
2072021
Deep learning with label differential privacy
B Ghazi, N Golowich, R Kumar, P Manurangsi, C Zhang
Advances in neural information processing systems 34, 27131-27145, 2021
1632021
Large-scale differentially private BERT
R Anil, B Ghazi, V Gupta, R Kumar, P Manurangsi
arXiv preprint arXiv:2108.01624, 2021
1372021
Sample-optimal average-case sparse fourier transform in two dimensions
B Ghazi, H Hassanieh, P Indyk, D Katabi, E Price, L Shi
2013 51st Annual Allerton Conference on Communication, Control, and …, 2013
1142013
Scalable and differentially private distributed aggregation in the shuffled model
B Ghazi, R Pagh, A Velingker
arXiv preprint arXiv:1906.08320, 2019
1112019
On the power of multiple anonymous messages: Frequency estimation and selection in the shuffle model of differential privacy
B Ghazi, N Golowich, R Kumar, R Pagh, A Velingker
Annual International Conference on the Theory and Applications of …, 2021
1022021
Advances and open problems in federated learning. arXiv 2019
P Kairouz, HB McMahan, B Avent, A Bellet, M Bennis, AN Bhagoji, ...
arXiv preprint arXiv:1912.04977, 1912
681912
Private aggregation from fewer anonymous messages
B Ghazi, P Manurangsi, R Pagh, A Velingker
Advances in Cryptology–EUROCRYPT 2020: 39th Annual International Conference …, 2020
602020
Differentially private clustering: Tight approximation ratios
B Ghazi, R Kumar, P Manurangsi
Advances in Neural Information Processing Systems 33, 4040-4054, 2020
582020
Pure differentially private summation from anonymous messages
B Ghazi, N Golowich, R Kumar, P Manurangsi, R Pagh, A Velingker
arXiv preprint arXiv:2002.01919, 2020
502020
Private counting from anonymous messages: Near-optimal accuracy with vanishing communication overhead
B Ghazi, R Kumar, P Manurangsi, R Pagh
International Conference on Machine Learning, 3505-3514, 2020
482020
User-level differentially private learning via correlated sampling
B Ghazi, R Kumar, P Manurangsi
Advances in Neural Information Processing Systems 34, 20172-20184, 2021
462021
Differentially private aggregation in the shuffle model: Almost central accuracy in almost a single message
B Ghazi, R Kumar, P Manurangsi, R Pagh, A Sinha
International Conference on Machine Learning, 3692-3701, 2021
382021
Decidability of non-interactive simulation of joint distributions
B Ghazi, P Kamath, M Sudan
2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS …, 2016
382016
Connect the dots: Tighter discrete approximations of privacy loss distributions
V Doroshenko, B Ghazi, P Kamath, R Kumar, P Manurangsi
arXiv preprint arXiv:2207.04380, 2022
372022
Locally private k-means in one round
A Chang, B Ghazi, R Kumar, P Manurangsi
International conference on machine learning, 1441-1451, 2021
352021
On distributed differential privacy and counting distinct elements
L Chen, B Ghazi, R Kumar, P Manurangsi
arXiv preprint arXiv:2009.09604, 2020
322020
Distributed, private, sparse histograms in the two-server model
J Bell, A Gascon, B Ghazi, R Kumar, P Manurangsi, M Raykova, ...
Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications …, 2022
302022
Sample-efficient proper PAC learning with approximate differential privacy
B Ghazi, N Golowich, R Kumar, P Manurangsi
Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing …, 2021
302021
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