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cs.IT2022
Fundamental Limits of Communication Efficiency for Model Aggregation in Distributed Learning: A Rate-Distortion Approach
Naifu Zhang, Meixia Tao, Jia Wang +1
One of the main focuses in distributed learning is communication efficiency, since model aggregation at each round of training can consist of millions to billions of parameters. Se…
cs.IT2021
Sum-Rate-Distortion Function for Indirect Multiterminal Source Coding in Federated Learning
Naifu Zhang, Meixia Tao, Jia Wang
One of the main focus in federated learning (FL) is the communication efficiency since a large number of participating edge devices send their updates to the edge server at each ro…