DynamicFL: Balancing Communication Dynamics and Client Manipulation for Federated Learning-Reference-Cited by-同舟云学术

DynamicFL: Balancing Communication Dynamics and Client Manipulation for Federated Learning

Published:2023-09-11 Issue: Volume: Page:
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Container-title:2023 20th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)
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Author:

Chen Bocheng¹,Ivanov Nikolay¹,Wang Guangjing¹,Yan Qiben¹

Affiliation:

1. Michigan State University,Computer Science & Engineering,East Lansing,USA

Funder

National Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10287388/10287413/10287430.pdf?arnumber=10287430

Reference44 articles.

1. Graph Learning for Interactive Threat Detection in Heterogeneous Smart Home Rule Data

2. Black-box queryefficient audio adversarial attack via split-second phoneme injection;guo;Proceedings of the 26th International Symposium on Research in Attacks Intrusions and Defenses,2023

3. Federated threat detection for smart home iot rules;wang;International Workshop on Federated Learning for Distributed Data Mining,2023

4. A Deep Learning Approach for Energy Efficient Computational Offloading in Mobile Edge Computing

5. Oort: Efficient Federated Learning via Guided Participant Selection;lai;Proceedings of USENIX OSDI,2021

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