A state-of-the-art survey on solving non-IID data in Federated Learning
Published 2022 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
A state-of-the-art survey on solving non-IID data in Federated Learning
Authors
Keywords
-
Journal
Future Generation Computer Systems-The International Journal of eScience
Volume 135, Issue -, Pages 244-258
Publisher
Elsevier BV
Online
2022-05-07
DOI
10.1016/j.future.2022.05.003
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Local Epochs Inefficiency Caused by Device Heterogeneity in Federated Learning
- (2022) Yan Zeng et al. WIRELESS COMMUNICATIONS & MOBILE COMPUTING
- A survey on federated learning
- (2021) Chen Zhang et al. KNOWLEDGE-BASED SYSTEMS
- From federated learning to federated neural architecture search: a survey
- (2021) Hangyu Zhu et al. Complex & Intelligent Systems
- A Comprehensive Survey of Privacy-preserving Federated Learning
- (2021) Xuefei Yin et al. ACM COMPUTING SURVEYS
- Towards asynchronous federated learning based threat detection: A DC-Adam approach
- (2021) Pu Tian et al. COMPUTERS & SECURITY
- FedSA: A Semi-Asynchronous Federated Learning Mechanism in Heterogeneous Edge Computing
- (2021) Qianpiao Ma et al. IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
- Federated learning on non-IID data: A survey
- (2021) Hangyu Zhu et al. NEUROCOMPUTING
- A Survey on Federated Learning for Resource-Constrained IoT Devices
- (2021) Ahmed Imteaj et al. IEEE Internet of Things Journal
- Preserving Data Privacy via Federated Learning: Challenges and Solutions
- (2020) Zengpeng Li et al. IEEE Consumer Electronics Magazine
- A Sustainable Incentive Scheme for Federated Learning
- (2020) Han Yu et al. IEEE INTELLIGENT SYSTEMS
- Preserving User Privacy for Machine Learning: Local Differential Privacy or Federated Machine Learning?
- (2020) Huadi Zheng et al. IEEE INTELLIGENT SYSTEMS
- Towards Efficient Scheduling of Federated Mobile Devices Under Computational and Statistical Heterogeneity
- (2020) Cong Wang et al. IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
- A Survey on Federated Learning: The Journey From Centralized to Distributed On-Site Learning and Beyond
- (2020) Sawsan Abdulrahman et al. IEEE Internet of Things Journal
- Federated Machine Learning
- (2019) Qiang Yang et al. ACM Transactions on Intelligent Systems and Technology
- Adaptive Federated Learning in Resource Constrained Edge Computing Systems
- (2019) Shiqiang Wang et al. IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
- In-Edge AI: Intelligentizing Mobile Edge Computing, Caching and Communication by Federated Learning
- (2019) Xiaofei Wang et al. IEEE NETWORK
- Communication-Efficient Federated Learning for Wireless Edge Intelligence in IoT
- (2019) Jed Mills et al. IEEE Internet of Things Journal
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started