Federated Learning (FL) has recently arisen as a revolutionary approach to collaborative training Machine Learning models. According to this novel framework, multiple participants …
A Qammar, A Karim, H Ning, J Ding - 2022 - academia.edu
Federated learning (FL) is a promising framework for distributed machine learning that trains models without sharing local data while protecting privacy. FL exploits the concept of …
A Qammar, A Karim, H Ning, J Ding - Artificial Intelligence Review, 2023 - Springer
Federated learning (FL) is a promising framework for distributed machine learning that trains models without sharing local data while protecting privacy. FL exploits the concept of …
Y Tang, Y Zhang, T Niu, Z Li, Z Zhang… - … in Engineering & …, 2024 - cdn.techscience.cn
Federated Learning (FL), as an emergent paradigm in privacy-preserving machine learning, has garnered significant interest from scholars and engineers across both academic and …
Federated learning (FL) is a promising decentralized deep learning technology, which allows users to update models cooperatively without sharing their data. FL is reshaping …
Federated Learning (FL) has made an essential step towards enhancing the privacy of traditional model training. However, gaps in the conventional FL framework make it …
Q Attia, K Ahmad, N Huansheng - 2022 - dlib.phenikaa-uni.edu.vn
Federated learning (FL) is a promising framework for distributed machine learning that trains models without sharing local data while protecting privacy. FL exploits the concept of …
Z Cai, J Chen, Y Fan, Z Zheng, K Li - arXiv preprint arXiv:2403.00873, 2024 - arxiv.org
Federated learning (FL) is a distributed machine learning approach that protects user data privacy by training models locally on clients and aggregating them on a parameter server …
J Zhu, J Cao, D Saxena, S Jiang, H Ferradi - ACM Computing Surveys, 2023 - dl.acm.org
Federated learning is a privacy-preserving machine learning technique that trains models across multiple devices holding local data samples without exchanging them. There are …