Resource Allocation for Federated Learning With Highly Distorted Model

Resource Allocation for Federated Learning With Highly Distorted Model

Information loss has emerged and escalated as the information bottleneck of a deep encryption model surpasses the entropy of the data and reduces the data reconstruction efficiency at the decoder (i.e., lossy compression and high data encryption). Therefore, existing communication-effective federate...

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Bibliographic Details
Main Authors: Ryu Junewoo, Nguyen Xuan Tung, Minh-Duong Nguyen, Quang-Vinh do, Won-Joo Hwang
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Communication efficiency
data encryption
federated learning
IoT
resource allocation
Online Access:https://ieeexplore.ieee.org/document/10946888/
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