Federated Feature Selection for Horizontal Federated Learning in IoT Networks-Reference-Cited by-同舟云学术

Federated Feature Selection for Horizontal Federated Learning in IoT Networks

Published:2023-06-01 Issue:11 Volume:10 Page:10095-10112
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Zhang Xunzheng¹^ORCID,Mavromatis Alex¹^ORCID,Vafeas Antonis¹,Nejabati Reza¹^ORCID,Simeonidou Dimitra¹^ORCID

Affiliation:

1. High Performance Networks Group, Smart Internet Lab, School of Computer Science, Electrical and Electronic Engineering, and Engineering Maths, Faculty of Engineering, University of Bristol, Bristol, U.K.

Funder

U.K. DCMS funded Project Future RAN: O-RANOS

U.K. DCMS 2022 UK5G Proteus Research Project

China Scholarship Council

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/6488907/10128761/10017376.pdf?arnumber=10017376

Reference55 articles.

1. Federated Learning for Internet of Things: A Comprehensive Survey

2. The feature selection bias problem in relation to high-dimensional gene data

3. A Survey on Federated Learning for Resource-Constrained IoT Devices

4. Federated Learning for Internet of Things: Recent Advances, Taxonomy, and Open Challenges

5. End-to-End Evaluation of Federated Learning and Split Learning for Internet of Things

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