Harnessing Wireless Channels for Scalable and Privacy-Preserving Federated Learning
Version 2 2024-06-06, 01:48
Version 1 2021-05-25, 09:03
journal contribution
posted on 2024-06-06, 01:48 authored by A Elgabli, Jihong ParkJihong Park, CB Issaid, M BennisHarnessing Wireless Channels for Scalable and Privacy-Preserving Federated Learning
History
Journal
IEEE Transactions on CommunicationsVolume
69Pagination
5194-5208Open access
- Yes
Link to full text
ISSN
0090-6778eISSN
1558-0857Language
EnglishPublication classification
C1 Refereed article in a scholarly journalIssue
8Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INCUsage metrics
Categories
Keywords
Science & TechnologyTechnologyEngineering, Electrical & ElectronicTelecommunicationsEngineeringConvergencePrivacyTime-varying channelsBandwidthPerturbation methodsConvex functionsWireless communicationAnalog federated ADMMdigital federated ADMMdistributed machine learningprivacytime-varying channelsCOMMUNICATION-EFFICIENTADAPTIVE MODULATIONDESIGNADMM4006 Communications engineering4606 Distributed computing and systems software
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC