Related references
Note: Only part of the references are listed.Adaptive Batch Size for Federated Learning in Resource-Constrained Edge Computing
Zhenguo Ma et al.
IEEE TRANSACTIONS ON MOBILE COMPUTING (2023)
Optimal User-Edge Assignment in Hierarchical Federated Learning Based on Statistical Properties and Network Topology Constraints
Naram Mhaisen et al.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING (2022)
Accelerating DNN Training in Wireless Federated Edge Learning Systems
Jinke Ren et al.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS (2021)
Self-Balancing Federated Learning With Global Imbalanced Data in Mobile Systems
Moming Duan et al.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS (2021)
A Joint Learning and Communications Framework for Federated Learning Over Wireless Networks
Mingzhe Chen et al.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS (2021)
SAFA: A Semi-Asynchronous Protocol for Fast Federated Learning With Low Overhead
Wentai Wu et al.
IEEE TRANSACTIONS ON COMPUTERS (2021)
A Hierarchical Blockchain-Enabled Federated Learning Algorithm for Knowledge Sharing in Internet of Vehicles
Haoye Chai et al.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2021)
To Talk or to Work: Flexible Communication Compression for Energy Efficient Federated Learning over Heterogeneous Mobile Edge Devices
Liang Li et al.
IEEE CONFERENCE ON COMPUTER COMMUNICATIONS (IEEE INFOCOM 2021) (2021)
Resource-Efficient and Convergence-Preserving Online Participant Selection in Federated Learning
Yibo Jin et al.
2020 IEEE 40TH INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING SYSTEMS (ICDCS) (2020)
Offloading Dependent Tasks in Mobile Edge Computing with Service Caching
Gongming Zhao et al.
IEEE INFOCOM 2020 - IEEE CONFERENCE ON COMPUTER COMMUNICATIONS (2020)
Network-Aware Optimization of Distributed Learning for Fog Computing
Yuwei Tu et al.
IEEE INFOCOM 2020 - IEEE CONFERENCE ON COMPUTER COMMUNICATIONS (2020)
HFEL: Joint Edge Association and Resource Allocation for Cost-Efficient Hierarchical Federated Edge Learning
Siqi Luo et al.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS (2020)
Convergence of Edge Computing and Deep Learning: A Comprehensive Survey
Xiaofei Wang et al.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS (2020)
Federated Learning for Edge Networks: Resource Optimization and Incentive Mechanism
Latif U. Khan et al.
IEEE COMMUNICATIONS MAGAZINE (2020)
Federated Machine Learning: Concept and Applications
Qiang Yang et al.
ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY (2019)
Learning IoT in Edge: Deep Learning for the Internet of Things with Edge Computing
He Li et al.
IEEE NETWORK (2018)
LinkForecast: Cellular Link Bandwidth Prediction in LTE Networks
Chaoqun Yue et al.
IEEE TRANSACTIONS ON MOBILE COMPUTING (2018)
Edge Computing: Vision and Challenges
Weisong Shi et al.
IEEE INTERNET OF THINGS JOURNAL (2016)
Privacy and Big Data
Brian M. Gaff et al.
COMPUTER (2014)
Fast computation of Bipartite graph matching
Francesc Serratosa
PATTERN RECOGNITION LETTERS (2014)
Predictable 802.11 Packet Delivery from Wireless Channel Measurements
Daniel Halperin et al.
ACM SIGCOMM COMPUTER COMMUNICATION REVIEW (2010)
Frequency-sensitive competitive learning for scalable balanced clustering on high-dimensional hyperspheres
A Banerjee et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS (2004)