Results 141 to 150 of about 17,541 (167)

Federated Regularization Learning: an Accurate and Safe Method for Federated Learning

2021 IEEE 3rd International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2021
Distributed machine learning (ML) and other related techniques such as federated learning are facing a high risk of information leakage. Differential privacy (DP) is commonly used to protect privacy. However, it suffers from low accuracy due to the unbalanced data distribution in federated learning and additional noise brought by DP itself.
Tianqi Su, Meiqi Wang, Zhongfeng Wang 0001   +2 more
openaire   +1 more source

A Survey on federated learning

2020 IEEE 16th International Conference on Control & Automation (ICCA), 2020
Federated learning (FL) is an emerging setting which implement machine learning in a distributed environment while protecting privacy. Research activities relating to FLhave grown at a fast rate recently in control. Exactly what activities have been carrying the research momentum forward is a question of interest to the research community.
Li Li 0008, Yuxi Fan, Kuo-Yi Lin
openaire   +1 more source

Utility-preserving Federated Learning

Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security, 2023
We investigate the concept of utility-preserving federated learning (UPFL) in the context of deep neural networks. We theoretically prove and experimentally validate that UPFL achieves the same accuracy as centralized training independent of the data distribution across the clients.
Reza Nasirigerdeh, Daniel Rueckert, Georgios Kaissis   +2 more
openaire   +2 more sources

Federated Learning of Things - Expanding the Heterogeneity in Federated Learning

Proceedings of the AAAI Symposium Series
The Internet of Things (IoT) has revolutionized how our devices are networked, connecting multiple aspects of our life from smart homes and wearables to smart cities and warehouses. IoT’s strength comes from the ever-expanding diverse heterogeneous sensors, applications, and concepts that are all centered around the core concept collecting and ...
openaire   +1 more source

Online Federated Learning

2021 60th IEEE Conference on Decision and Control (CDC), 2021
Aritra Mitra, Hamed Hassani, George J. Pappas   +2 more
openaire   +1 more source

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

IEEE Communications Surveys and Tutorials, 2021
Latif U Khan, Walid Saad, Zhu Han
exaly  

A Comprehensive Survey of Privacy-preserving Federated Learning

ACM Computing Surveys, 2022
Xuefei Yin, Yanming Zhu, Jiankun Hu
exaly  

A Systematic Literature Review on Federated Machine Learning

ACM Computing Surveys, 2022
Sin Kit Lo, Qinghua Lu, Chen Wang
exaly  

Blockchain-empowered Federated Learning: Challenges, Solutions, and Future Directions

ACM Computing Surveys, 2023
Juncen Zhu, Jiannong Cao, Divya Saxena   +2 more
exaly  

Federated learning on non-IID data: A survey

Neurocomputing, 2021
Hangyu Zhu, Jinjin Xu, Shiqing Liu
exaly