Huangxy-Minel/System-Design-for-Federated-Learning

Paper list of federated learning: About system design

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This is a curated list of research papers focused on the system design aspects of Federated Learning. It provides researchers and practitioners with an organized overview of studies related to distributed computing frameworks, communication, and computational efficiency in both cross-silo and cross-device federated learning scenarios. The resource is ideal for those looking to understand the underlying infrastructure and performance considerations of federated machine learning.

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Use this if you are a researcher or system architect needing to explore foundational papers and recent advancements in optimizing the distributed computing frameworks, communication, and efficiency for federated learning systems.

Not ideal if you are looking for introductory material on federated learning algorithms or practical guides for implementing a federated learning model without a focus on system-level challenges.

distributed-machine-learning privacy-preserving-ai system-architecture computational-efficiency network-communication
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MIT

Last pushed

Apr 13, 2022

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