Dynamic Sampling and Selective Masking for Communication-Efficient Federated Learning

Preserving user privacy for machine learning: Local differential privacy or federated machine learning

Original

Huadi Zheng, Haibo Hu, and Ziyang Han · 2003

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Federated learning: Strategies for improving communication efficiency

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Jakub Konečnỳ, H Brendan McMahan, Felix X Yu, Peter Richtárik, Ananda Theertha Suresh, and Dave Bacon · 2016

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Communication-efficient learning of deep networks from decentralized data

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H Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, et al · 2016

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Towards federated learning at scale: System design

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Keith Bonawitz, Hubert Eichner, Wolfgang Grieskamp, Dzmitry Huba, Alex Ingerman, Vladimir Ivanov, Chloe Kiddon, Jakub Konecny, Stefano Mazzocchi, H Brendan McMahan, et al · 2019

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Learning private neural language modeling with attentive aggregation

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Private federated learning with domain adaptation

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Daniel Peterson, Pallika Kanani, and Virendra J. Marathe · 2019

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Robust and communication-efficient federated learning from non-iid data

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A joint learning and communications framework for federated learning over wireless networks

Mingzhe Chen, Zhaohui Yang, Walid Saad, Changchuan Yin, H Vincent Poor, and Shuguang Cui · 2020

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FedBoost: A Communication-Efficient Algorithm for Federated Learning

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Decentralized knowledge acquisition for mobile internet applications

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A secure federated transfer learning framework

Yang Liu, Yan Kang, Chaoping Xing, Tianjian Chen, and Qiang Yang · 2020

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FedPAQ: A communication-efficient federated learning method with periodic averaging and quantization

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FetchSGD: Communication-efficient federated learning with sketching

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Energy efficient federated learning over wireless communication networks

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