has been cited by the following article(s):
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[1]
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Fed-GTopK: Expediting In-Network Federated Learning by Transmitting Global Top Model Updates
IEEE Transactions on Networking,
2026
DOI:10.1109/TON.2026.3666116
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[2]
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Expediting In-Network Federated Learning by Voting-Based Consensus Model Compression
IEEE INFOCOM 2024 - IEEE Conference on Computer Communications,
2024
DOI:10.1109/INFOCOM52122.2024.10621376
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[3]
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Fed-CVLC: Compressing Federated Learning Communications with Variable-Length Codes
IEEE INFOCOM 2024 - IEEE Conference on Computer Communications,
2024
DOI:10.1109/INFOCOM52122.2024.10621361
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[4]
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Method for Evaluating the Quality of Service Characteristic of a Packet Access Network for IoT Devices
2021 IEEE 4th International Conference on Advanced Information and Communication Technologies (AICT),
2021
DOI:10.1109/AICT52120.2021.9628912
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[5]
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Impact of Variable MTU Size of Voice Packet To Reduce Packet Loss In Bandwidth Constraint Military Network
2019 IEEE 5th International Conference for Convergence in Technology (I2CT),
2019
DOI:10.1109/I2CT45611.2019.9033868
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[6]
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International Conference on Wireless, Intelligent, and Distributed Environment for Communication
Lecture Notes on Data Engineering and Communications Technologies,
2018
DOI:10.1007/978-3-319-75626-4_10
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[7]
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Design of Data Harvesting System with Radio Frequency Modules for Monitoring Performance of Solar Cells
2018 International Electronics Symposium on Engineering Technology and Applications (IES-ETA),
2018
DOI:10.1109/ELECSYM.2018.8615457
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