Zachary Charles

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

2019 · arXiv (Cornell University)

To improve the resilience of distributed training to worst-case, or Byzantine node failures, several recent approaches have replaced gradient averaging with robust aggregation methods. Such techniques can have high computational costs, often quadratic in the …

Learning with User-Level Differential Privacy Under Fixed Compute Budgets

2025

We investigate practical and scalable algorithms for training machine learning models with user-level differential privacy (DP) in order to provably safeguard all the examples contributed by each user. Motivated by the application of large language …