Zachary B. Charles

Most-cited papers

Advances and Open Problems in Federated Learning
Peter Kairouz, H. B. McMahan, Brendan Avent, A. Bellet +55 more
2019Found. Trends Mach. Learn.9,929 citations Open access
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Adaptive Federated Optimization
Sashank J. Reddi, Zachary B. Charles, M. Zaheer, Zachary Garrett +4 more
2020International Conference on Learning Representations2,214 citations
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A Field Guide to Federated Optimization
Jianyu Wang, Zachary B. Charles, Zheng Xu, Gauri Joshi +49 more
2021arXiv.org497 citations
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ATOMO: Communication-efficient Learning via Atomic Sparsification
Hongyi Wang, Scott Sievert, Sheng-Chao Liu, Zachary B. Charles +2 more
2018Neural Information Processing Systems396 citations
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DRACO: Byzantine-resilient Distributed Training via Redundant Gradients
Lingjiao Chen, Hongyi Wang, Zachary B. Charles, Dimitris Papailiopoulos
2018International Conference on Machine Learning277 citations
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Stability and Generalization of Learning Algorithms that Converge to Global Optima
Zachary B. Charles, Dimitris Papailiopoulos
2017International Conference on Machine Learning200 citations
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DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation
Shashank Rajput, Hongyi Wang, Zachary B. Charles, Dimitris Papailiopoulos
2019Neural Information Processing Systems152 citations
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On Large-Cohort Training for Federated Learning
Zachary B. Charles, Zachary Garrett, Zhou-Yuan Huo, Sergei Shmulyian +1 more
2021Neural Information Processing Systems131 citations
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Convergence and Accuracy Trade-Offs in Federated Learning and Meta-Learning
Zachary B. Charles, Jakub Konecný
2021International Conference on Artificial Intelligence and Statistics94 citations
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Approximate Gradient Coding via Sparse Random Graphs
Zachary B. Charles, Dimitris Papailiopoulos, J. Ellenberg
2017arXiv.org92 citations
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ErasureHead: Distributed Gradient Descent without Delays Using Approximate Gradient Coding
Hongyi Wang, Zachary B. Charles, Dimitris Papailiopoulos
2019arXiv.org62 citations
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On the Outsized Importance of Learning Rates in Local Update Methods
Zachary B. Charles, Jakub Konecný
2020arXiv.org60 citations
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Motley: Benchmarking Heterogeneity and Personalization in Federated Learning
Shan-Shan Wu, Tian Li, Zachary B. Charles, Yu Xiao +3 more
2022arXiv.org59 citations Open access
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Local Adaptivity in Federated Learning: Convergence and Consistency
Jianyu Wang, Zheng Xu, Zachary Garrett, Zachary B. Charles +2 more
2021arXiv.org48 citations
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Does Data Augmentation Lead to Positive Margin?
Shashank Rajput, Zhili Feng, Zachary B. Charles, Po-Ling Loh +1 more
2019International Conference on Machine Learning38 citations
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Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning
Zachary B. Charles, Nicole Mitchell, Krishna Pillutla, Michael Reneer +1 more
2023Neural Information Processing Systems37 citations Open access
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Optimizing the Communication-Accuracy Trade-off in Federated Learning with Rate-Distortion Theory
Nicole Mitchell, Johannes Ball'e, Zachary B. Charles, Jakub Konecný
2022arXiv.org28 citations
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Gradient Coding Using the Stochastic Block Model
Zachary B. Charles, Dimitris Papailiopoulos
2018International Symposium on Information Theory26 citations
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Gradient Descent with Linearly Correlated Noise: Theory and Applications to Differential Privacy
Anastasia Koloskova, Ryan McKenna, Zachary B. Charles, J. Rush +1 more
2023Neural Information Processing Systems24 citations Open access
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Does Federated Dropout actually work?
Gary Cheng, Zachary B. Charles, Zachary Garrett, Keith Rush
20222022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)23 citations
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DRACO: Robust Distributed Training via Redundant Gradients
Lingjiao Chen, Hongyi Wang, Zachary B. Charles, Dimitris Papailiopoulos
2018International Conference on Machine Learning23 citations
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Convergence and Margin of Adversarial Training on Separable Data
Zachary B. Charles, Shashank Rajput, S. Wright, Dimitris Papailiopoulos
2019arXiv.org18 citations
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A Geometric Perspective on the Transferability of Adversarial Directions
Zachary B. Charles, Harrison Rosenberg, Dimitris Papailiopoulos
2018International Conference on Artificial Intelligence and Statistics18 citations
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Gradient Coding via the Stochastic Block Model
Zachary B. Charles, Dimitris Papailiopoulos
2018arXiv.org17 citations
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Federated Select: A Primitive for Communication- and Memory-Efficient Federated Learning
Zachary B. Charles, Kallista A. Bonawitz, Stanislav Chiknavaryan, H. B. McMahan +1 more
2022arXiv.org16 citations Open access
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SPARSE SUBSPACE CLUSTERING WITH MISSING AND CORRUPTED DATA
Zachary B. Charles, Amin Jalali, R. Willett
2017Data Science Workshop15 citations
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Improving the convergence of SGD through adaptive batch sizes
Scott Sievert, Zachary B. Charles
2019arXiv.org11 citations
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Iterated Vector Fields and Conservatism, with Applications to Federated Learning
Zachary B. Charles, Keith Rush
2021International Conference on Algorithmic Learning Theory9 citations
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Convergence of Gradient Descent with Linearly Correlated Noise and Applications to Differentially Private Learning
Anastasia Koloskova, Ryan McKenna, Zachary B. Charles, Keith Rush +1 more
2023arXiv.org7 citations Open access
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Distributions of the Number of Solutions to the Network Power Flow Equations
Alisha Zachariah, Zachary B. Charles, N. Boston, B. Lesieutre
2018International Symposium on Circuits and Systems7 citations
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Leveraging Function Space Aggregation for Federated Learning at Scale
Nikita Dhawan, Nicole Mitchell, Zachary B. Charles, Zachary Garrett +1 more
2023Trans. Mach. Learn. Res.5 citations
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Federated Automatic Differentiation
Keith Rush, Zachary B. Charles, Zachary Garrett
2023Journal of machine learning research3 citations Open access
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Efficiently finding all power flow solutions to tree networks
Alisha Zachariah, Zachary B. Charles
2017Allerton Conference on Communication, Control, and Computing2 citations
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A Rate-Distortion View on Model Updates
Nicole Mitchell, Johannes Ballé, Zachary B. Charles, Jakub Konecný
2023Tiny Papers @ ICLR0 citations
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Exploiting algebraic structure in global optimization and the Belgian chocolate problem
Zachary B. Charles, N. Boston
2017Journal of Global Optimization0 citations Open access
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Generating Random Factored Ideals in Number Fields
Zachary B. Charles
2016Mathematics of Computation0 citations
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