Federated Learning Publications

Publications in Federated Learning

Explore the most influential research papers and scholarly works that have shaped Federated Learning. Use the concept filter below to focus on a specific sub-area of research.

Federated Learning

5.1K

Publications

360.5K

Citations

Showing yearly statistics from 2000-2026.

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	Year	Citations
Federated Machine Learning Qiang Yang, Yang Liu, Tianjian Chen, ACM Transactions on Intelligent Systems and Technology Artificial IntelligenceEngineeringMachine LearningData SciencePrivacy-preserving Techniques	2019	5.5K
Communication-Efficient Learning of Deep Networks from Decentralized Data H. Brendan McMahan, Eider Moore, Daniel Ramage, arXiv (Cornell University) Modern Mobile DevicesDecentralized Machine LearningMachine LearningData ScienceEngineering	2016	5.2K
Federated Learning: Challenges, Methods, and Future Directions IEEE Signal Processing Magazine Artificial IntelligenceEngineeringMachine LearningFederated StructureRemote Devices	2020	4.3K
Practical Secure Aggregation for Privacy-Preserving Machine Learning Keith Bonawitz, Vladimir Ivanov, Ben Kreuter, Privacy ProtectionFailure-robust ProtocolMachine LearningEngineeringInformation Security	2017	3.2K
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konečný, H. Brendan McMahan, Felix X. Yu, arXiv (Cornell University) EngineeringMachine LearningData ScienceEdge ComputingFederated Learning	2016	3K
Federated Learning in Mobile Edge Networks: A Comprehensive Survey Wei Yang Bryan Lim, Nguyen Cong Luong, Dinh Thai Hoang, IEEE Communications Surveys & Tutorials EngineeringMachine LearningEdge DeviceFederated StructureNetwork Analysis	2020	2.3K
Adaptive Federated Learning in Resource Constrained Edge Computing Systems Shiqiang Wang, Tiffany Tuor, Theodoros Salonidis, IEEE Journal on Selected Areas in Communications Cluster ComputingEngineeringMachine LearningDistributed AlgorithmsFederated Structure	2019	2.1K
Federated Learning with Non-IID Data Yue Zhao, Meng Li, Liangzhen Lai, arXiv (Cornell University) Artificial IntelligenceEngineeringMachine LearningFederated StructureData Science	2018	1.9K
SecureML: A System for Scalable Privacy-Preserving Machine Learning Payman Mohassel, Yupeng Zhang Hardware SecuritySecure Multi-party ComputationPrivacy ProtectionEngineeringMachine Learning	2017	1.8K
Federated Optimization: Distributed Machine Learning for On-Device Intelligence Jakub Konečný, H. Brendan McMahan, Daniel Ramage, arXiv (Cornell University) Artificial IntelligenceCluster ComputingEngineeringMachine LearningDistributed Algorithms	2016	1.7K
A survey on federated learning Chen Zhang, Yu Xie, Hang Bai, Knowledge-Based Systems Artificial IntelligenceEngineeringMachine LearningData ScienceFederated Learning	2021	1.6K
Privacy-Preserving Deep Learning via Additively Homomorphic Encryption Le Trieu Phong, Yoshinori Aono, Takuya Hayashi, IEEE Transactions on Information Forensics and Security Privacy ProtectionEngineeringMachine LearningInformation SecurityHardware Security	2017	1.6K

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