Zachary B. Charles

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A Geometric Perspective on the Transferability of Adversarial Directions pdf

Dimitris S. Papailiopoulos, Zachary B. Charles, Harrison Rosenberg, 2018, AISTATS.

Gradient Coding via the Stochastic Block Model pdf

Dimitris S. Papailiopoulos, Zachary B. Charles, 2018, ArXiv.

Generating Random Factored Ideals in Number Fields

Zachary B. Charles, 2016, Math. Comput..

Nonpositive Eigenvalues of Hollow, Symmetric, Nonnegative Matrices

Miriam Farber, Charles R. Johnson, Lee Kennedy-Shaffer, 2013, SIAM J. Matrix Anal. Appl..

ErasureHead: Distributed Gradient Descent without Delays Using Approximate Gradient Coding pdf

Dimitris S. Papailiopoulos, Hongyi Wang, Zachary B. Charles, 2019, ArXiv.

MOULTRIE OBSERVER This Page Made Possible By

Adrien Richard, Fred Charles, Rodrick Wallace, 2013 .

Stability and Generalization of Learning Algorithms that Converge to Global Optima

Dimitris S. Papailiopoulos, Zachary B. Charles, Dimitris Papailiopoulos, 2017, ICML.

DRACO: Robust Distributed Training via Redundant Gradients pdf

Dimitris S. Papailiopoulos, Hongyi Wang, Lingjiao Chen, 2018, ICML 2018.

Approximate Gradient Coding via Sparse Random Graphs pdf

Dimitris S. Papailiopoulos, Jordan S. Ellenberg, Zachary B. Charles, 2017, ArXiv.

ATOMO: Communication-efficient Learning via Atomic Sparsification

Dimitris S. Papailiopoulos, Stephen Wright, Scott Sievert, 2018, NeurIPS.

Gradient Coding Using the Stochastic Block Model

Dimitris S. Papailiopoulos, Zachary B. Charles, 2018, 2018 IEEE International Symposium on Information Theory (ISIT).

Nonpositive eigenvalues of the adjacency matrix and lower bounds for Laplacian eigenvalues

Miriam Farber, Charles R. Johnson, Lee Kennedy-Shaffer, 2011, Discret. Math..

DRACO: Byzantine-resilient Distributed Training via Redundant Gradients

Dimitris S. Papailiopoulos, Hongyi Wang, Lingjiao Chen, 2018, ICML.

Advances and Open Problems in Federated Learning pdf

Richard Nock, Zaïd Harchaoui, David Evans, 2019, Found. Trends Mach. Learn..

On the Outsized Importance of Learning Rates in Local Update Methods pdf

Jakub Konecný, Zachary Charles, Zachary B. Charles, 2020, ArXiv.

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

Hongyi Wang, Dimitris Papailiopoulos, Zachary Charles, 2019, NeurIPS.

Subspace Clustering with Missing and Corrupted Data

Rebecca Willett, Amin Jalali, Zachary B. Charles, 2017 .

Motley: Benchmarking Heterogeneity and Personalization in Federated Learning

Zachary B. Charles, Virginia Smith, Zheng Xu, 2022, 2206.09262.

Motley: Benchmarking Heterogeneity and Personalization in Federated Learning

Zachary B. Charles, Virginia Smith, Zheng Xu, 2022, ArXiv.

Motley: Benchmarking Heterogeneity and Personalization in Federated Learning

Zachary B. Charles, Virginia Smith, Zheng Xu, 2022, ArXiv.

Motley: Benchmarking Heterogeneity and Personalization in Federated Learning

Zachary B. Charles, Virginia Smith, Zheng Xu, 2022, ArXiv.

Optimizing the Communication-Accuracy Trade-off in Federated Learning with Rate-Distortion Theory

Zachary B. Charles, Jakub Konecný, Nicole Mitchell, 2022, ArXiv.

Convergence of Gradient Descent with Linearly Correlated Noise and Applications to Differentially Private Learning

Zachary B. Charles, Anastasia Koloskova, Keith Rush, 2023, ArXiv.

A Field Guide to Federated Optimization pdf

Suhas Diggavi, Ameet Talwalkar, Tara Javidi, 2021, ArXiv.

Adaptive Federated Optimization pdf

Manzil Zaheer, Sashank J. Reddi, Jakub Konecný, 2020, ICLR.

Does Data Augmentation Lead to Positive Margin?

Po-Ling Loh, Zhili Feng, Dimitris Papailiopoulos, 2019, ICML.

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

Jakub Konecný, Zachary B. Charles, Zachary Charles, 2021, AISTATS.

On Large-Cohort Training for Federated Learning pdf

Virginia Smith, Zhouyuan Huo, Zachary B. Charles, 2021, NeurIPS.

Federated Automatic Differentiation

Zachary B. Charles, Zachary Garrett, Keith Rush, 2023, ArXiv.

Does Federated Dropout actually work?

Zachary B. Charles, Zachary Garrett, Keith Rush, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

Local Adaptivity in Federated Learning: Convergence and Consistency pdf

Gauri Joshi, Zachary B. Charles, Zachary Garrett, 2021, ArXiv.

Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning

Zachary B. Charles, Zachary Garrett, Krishna Pillutla, 2023, ArXiv.

Iterated Vector Fields and Conservatism, with Applications to Federated Learning pdf

Zachary B. Charles, Keith Rush, Zachary Charles, 2021, ALT.

Convergence and Margin of Adversarial Training on Separable Data pdf

Stephen Wright, Dimitris Papailiopoulos, Shashank Rajput, 2019, ArXiv.

Improving the convergence of SGD through adaptive batch sizes

Zachary B. Charles, Scott Sievert, 2019, arXiv.org.

Federated Select: A Primitive for Communication- and Memory-Efficient Federated Learning

Zachary B. Charles, Kallista A. Bonawitz, H. B. McMahan, 2022, ArXiv.