Следене
Zachary Charles
Zachary Charles
Research Scientist, Google
Потвърден имейл адрес: google.com - Начална страница
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Позовавания
Година
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
17402021
Adaptive federated optimization
S Reddi, Z Charles, M Zaheer, Z Garrett, K Rush, J Konečný, S Kumar, ...
arXiv preprint arXiv:2003.00295, 2020
2992020
Atomo: Communication-efficient learning via atomic sparsification
H Wang, S Sievert, S Liu, Z Charles, D Papailiopoulos, S Wright
Advances in Neural Information Processing Systems 31, 2018
2102018
Draco: Byzantine-resilient distributed training via redundant gradients
L Chen, H Wang, Z Charles, D Papailiopoulos
International Conference on Machine Learning, 903-912, 2018
177*2018
Stability and generalization of learning algorithms that converge to global optima
Z Charles, D Papailiopoulos
International conference on machine learning, 745-754, 2018
762018
Approximate gradient coding via sparse random graphs
Z Charles, D Papailiopoulos, J Ellenberg
arXiv preprint arXiv:1711.06771, 2017
622017
DETOX: A redundancy-based framework for faster and more robust gradient aggregation
S Rajput, H Wang, Z Charles, D Papailiopoulos
Advances in Neural Information Processing Systems 32, 2019
602019
Gradient coding using the stochastic block model
Z Charles, D Papailiopoulos
2018 IEEE International Symposium on Information Theory (ISIT), 1998-2002, 2018
35*2018
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
351912
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
332021
Erasurehead: Distributed gradient descent without delays using approximate gradient coding
H Wang, Z Charles, D Papailiopoulos
arXiv preprint arXiv:1901.09671, 2019
322019
Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, et al. A field guide to federated optimization
J Wang, Z Charles, Z Xu, G Joshi, HB McMahan
arXiv preprint arXiv:2107.06917 1 (8), 2021
292021
On the outsized importance of learning rates in local update methods
Z Charles, J Konečný
arXiv preprint arXiv:2007.00878, 2020
272020
Does data augmentation lead to positive margin?
S Rajput, Z Feng, Z Charles, PL Loh, D Papailiopoulos
International Conference on Machine Learning, 5321-5330, 2019
222019
A geometric perspective on the transferability of adversarial directions
Z Charles, H Rosenberg, D Papailiopoulos
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
162019
Convergence and accuracy trade-offs in federated learning and meta-learning
Z Charles, J Konečný
International Conference on Artificial Intelligence and Statistics, 2575-2583, 2021
142021
Sparse subspace clustering with missing and corrupted data
Z Charles, A Jalali, R Willett
2018 IEEE Data Science Workshop (DSW), 180-184, 2018
132018
Nonpositive eigenvalues of hollow, symmetric, nonnegative matrices
ZB Charles, M Farber, CR Johnson, L Kennedy-Shaffer
SIAM Journal on Matrix Analysis and Applications 34 (3), 1384-1400, 2013
132013
On large-cohort training for federated learning
Z Charles, Z Garrett, Z Huo, S Shmulyian, V Smith
Advances in Neural Information Processing Systems 34, 2021
102021
Convergence and margin of adversarial training on separable data
Z Charles, S Rajput, S Wright, D Papailiopoulos
arXiv preprint arXiv:1905.09209, 2019
102019
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