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Iterated Vector Fields and Conservatism, with Applications to Federated Learning


Sep 08, 2021
Zachary Charles, Keith Rush


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A Field Guide to Federated Optimization


Jul 14, 2021
Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Aguera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horvath, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecny, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtarik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu


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On Large-Cohort Training for Federated Learning


Jun 15, 2021
Zachary Charles, Zachary Garrett, Zhouyuan Huo, Sergei Shmulyian, Virginia Smith


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Local Adaptivity in Federated Learning: Convergence and Consistency


Jun 04, 2021
Jianyu Wang, Zheng Xu, Zachary Garrett, Zachary Charles, Luyang Liu, Gauri Joshi


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Convergence and Accuracy Trade-Offs in Federated Learning and Meta-Learning


Mar 08, 2021
Zachary Charles, Jakub Konečný

* Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS) 2021. PMLR: Volume 130 

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On the Outsized Importance of Learning Rates in Local Update Methods


Jul 02, 2020
Zachary Charles, Jakub Konečný


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Adaptive Federated Optimization


Feb 29, 2020
Sashank Reddi, Zachary Charles, Manzil Zaheer, Zachary Garrett, Keith Rush, Jakub Konečný, Sanjiv Kumar, H. Brendan McMahan


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Advances and Open Problems in Federated Learning


Dec 10, 2019
Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Keith Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaid Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konečný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Mariana Raykova, Hang Qi, Daniel Ramage, Ramesh Raskar, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao


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Improving the convergence of SGD through adaptive batch sizes


Oct 18, 2019
Scott Sievert, Zachary Charles


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DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation


Jul 29, 2019
Shashank Rajput, Hongyi Wang, Zachary Charles, Dimitris Papailiopoulos


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Convergence and Margin of Adversarial Training on Separable Data


May 22, 2019
Zachary Charles, Shashank Rajput, Stephen Wright, Dimitris Papailiopoulos


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Does Data Augmentation Lead to Positive Margin?


May 08, 2019
Shashank Rajput, Zhili Feng, Zachary Charles, Po-Ling Loh, Dimitris Papailiopoulos

* ICML 2019 

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ErasureHead: Distributed Gradient Descent without Delays Using Approximate Gradient Coding


Jan 28, 2019
Hongyi Wang, Zachary Charles, Dimitris Papailiopoulos


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A Geometric Perspective on the Transferability of Adversarial Directions


Nov 08, 2018
Zachary Charles, Harrison Rosenberg, Dimitris Papailiopoulos


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ATOMO: Communication-efficient Learning via Atomic Sparsification


Jun 24, 2018
Hongyi Wang, Scott Sievert, Shengchao Liu, Zachary Charles, Dimitris Papailiopoulos, Stephen Wright


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DRACO: Byzantine-resilient Distributed Training via Redundant Gradients


Jun 22, 2018
Lingjiao Chen, Hongyi Wang, Zachary Charles, Dimitris Papailiopoulos

* Accepted by ICML 2018 

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Gradient Coding via the Stochastic Block Model


May 25, 2018
Zachary Charles, Dimitris Papailiopoulos


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Subspace Clustering with Missing and Corrupted Data


Jan 15, 2018
Zachary Charles, Amin Jalali, Rebecca Willett

* 31 pages, 2 figures 

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Approximate Gradient Coding via Sparse Random Graphs


Nov 17, 2017
Zachary Charles, Dimitris Papailiopoulos, Jordan Ellenberg


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Stability and Generalization of Learning Algorithms that Converge to Global Optima


Oct 23, 2017
Zachary Charles, Dimitris Papailiopoulos

* 27 pages, 5 figures 

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