Követés
Ananda Theertha Suresh
Ananda Theertha Suresh
Google Research, New York
E-mail megerősítve itt: google.com - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
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
72332021
Federated learning: Strategies for improving communication efficiency
J Konečný, HB McMahan, FX Yu, P Richtárik, AT Suresh, D Bacon
arXiv preprint arXiv:1610.05492, 2016
61752016
Scaffold: Stochastic controlled averaging for federated learning
SP Karimireddy, S Kale, M Mohri, S Reddi, S Stich, AT Suresh
International conference on machine learning, 5132-5143, 2020
33872020
Agnostic federated learning
M Mohri, G Sivek, AT Suresh
International conference on machine learning, 4615-4625, 2019
11182019
Can you really backdoor federated learning?
Z Sun, P Kairouz, AT Suresh, HB McMahan
arXiv preprint arXiv:1911.07963, 2019
7292019
Three approaches for personalization with applications to federated learning
Y Mansour, M Mohri, J Ro, AT Suresh
arXiv preprint arXiv:2002.10619, 2020
7072020
cpSGD: Communication-efficient and differentially-private distributed SGD
N Agarwal, AT Suresh, FXX Yu, S Kumar, B McMahan
Advances in Neural Information Processing Systems 31, 2018
5632018
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
4172021
Distributed mean estimation with limited communication
AT Suresh, XY Felix, S Kumar, HB McMahan
International conference on machine learning, 3329-3337, 2017
4042017
Breaking the centralized barrier for cross-device federated learning
SP Karimireddy, M Jaggi, S Kale, M Mohri, S Reddi, SU Stich, AT Suresh
Advances in Neural Information Processing Systems 34, 28663-28676, 2021
332*2021
Remember what you want to forget: Algorithms for machine unlearning
A Sekhari, J Acharya, G Kamath, AT Suresh
Advances in Neural Information Processing Systems 34, 18075-18086, 2021
3052021
Scaffold: Stochastic controlled averaging for on-device federated learning
SP Karimireddy, S Kale, M Mohri, SJ Reddi, SU Stich, AT Suresh
arXiv preprint arXiv:1910.06378 2 (6), 2019
2972019
Fedboost: A communication-efficient algorithm for federated learning
J Hamer, M Mohri, AT Suresh
International Conference on Machine Learning, 3973-3983, 2020
2642020
Orthogonal random features
XY Felix, AT Suresh, KM Choromanski, DN Holtmann-Rice, S Kumar
Advances in Neural Information Processing Systems, 1975-1983, 2016
259*2016
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
2272021
Optimal prediction of the number of unseen species
A Orlitsky, AT Suresh, Y Wu
Proceedings of the National Academy of Sciences 113 (47), 13283-13288, 2016
1542016
On learning distributions from their samples
S Kamath, A Orlitsky, D Pichapati, AT Suresh
Conference on Learning Theory, 1066-1100, 2015
1472015
Adaclip: Adaptive clipping for private sgd
V Pichapati, AT Suresh, FX Yu, SJ Reddi, S Kumar
arXiv preprint arXiv:1908.07643, 2019
1452019
Model-powered conditional independence test
R Sen, AT Suresh, K Shanmugam, AG Dimakis, S Shakkottai
Advances in neural information processing systems 30, 2017
1112017
Competitive distribution estimation: Why is good-turing good
A Orlitsky, AT Suresh
Advances in Neural Information Processing Systems 28, 2015
1062015
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Cikkek 1–20