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Ananda Theertha Suresh
Ananda Theertha Suresh
Senior Research Scientist, Google New York
Bestätigte E-Mail-Adresse bei google.com - Startseite
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Zitiert von
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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
48402021
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
46512016
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
21182020
Agnostic federated learning
M Mohri, G Sivek, AT Suresh
International Conference on Machine Learning, 4615-4625, 2019
8592019
Can you really backdoor federated learning?
Z Sun, P Kairouz, AT Suresh, HB McMahan
arXiv preprint arXiv:1911.07963, 2019
5062019
Three approaches for personalization with applications to federated learning
Y Mansour, M Mohri, J Ro, AT Suresh
arXiv preprint arXiv:2002.10619, 2020
5002020
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
4612018
Distributed mean estimation with limited communication
AT Suresh, XY Felix, S Kumar, HB McMahan
International conference on machine learning, 3329-3337, 2017
3402017
Orthogonal random features
XY Felix, AT Suresh, KM Choromanski, DN Holtmann-Rice, S Kumar
Advances in Neural Information Processing Systems, 1975-1983, 2016
230*2016
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
216*2021
Fedboost: A communication-efficient algorithm for federated learning
J Hamer, M Mohri, AT Suresh
International Conference on Machine Learning, 3973-3983, 2020
1892020
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
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
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
1472021
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
1422016
On learning distributions from their samples
S Kamath, A Orlitsky, D Pichapati, AT Suresh
Conference on Learning Theory, 1066-1100, 2015
1262015
Adaclip: Adaptive clipping for private sgd
V Pichapati, AT Suresh, FX Yu, SJ Reddi, S Kumar
arXiv preprint arXiv:1908.07643, 2019
1102019
Competitive distribution estimation: Why is good-turing good
A Orlitsky, AT Suresh
Advances in Neural Information Processing Systems 28, 2015
992015
Near-optimal-sample estimators for spherical gaussian mixtures
AT Suresh, A Orlitsky, J Acharya, A Jafarpour
Advances in Neural Information Processing Systems 27, 2014
952014
Model-powered conditional independence test
R Sen, AT Suresh, K Shanmugam, AG Dimakis, S Shakkottai
Advances in neural information processing systems 30, 2017
912017
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