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Extrapolation for Large-batch Training in Deep Learning

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Byzantine Fault-Tolerance in Federated Local SGD Under 2f-Redundancy

Nirupam Gupta

In this article, we study the problem of Byzantine fault-tolerance in a federated optimization setting, where there is a group of agents communicating with a centralized coordinator. We allow up to

f

Byzantine-faulty agents, which may not follow a prescr ...

Piscataway2023

Extrapolation for Large-batch Training in Deep Learning

Graph Chatbot

Chat with Graph Search

Understanding generalization and robustness in modern deep learning

On the Generalization of Stochastic Gradient Descent with Momentum

Revisiting Character-level Adversarial Attacks for Language Models

Universal and adaptive methods for robust stochastic optimization

Deep Learning Generalization with Limited and Noisy Labels

Robust Collaborative Learning with Linear Gradient Overhead

End-to-End Learning for Stochastic Optimization: A Bayesian Perspective

Communication-efficient distributed training of machine learning models

Phenomenological theory of variational quantum ground-state preparation

Byzantine Fault-Tolerance in Federated Local SGD Under 2f-Redundancy

On the Generalization of Stochastic Gradient Descent with Momentum

Deep Learning Generalization with Limited and Noisy Labels

Byzantine Fault-Tolerance in Federated Local SGD Under 2f-Redundancy

Universal and adaptive methods for robust stochastic optimization

Communication-efficient distributed training of machine learning models

Understanding generalization and robustness in modern deep learning

Revisiting Character-level Adversarial Attacks for Language Models

End-to-End Learning for Stochastic Optimization: A Bayesian Perspective

Phenomenological theory of variational quantum ground-state preparation

Robust Collaborative Learning with Linear Gradient Overhead