L Sun, J Qian, X Chen - arXiv preprint arXiv:2007.15789, 2020 - arxiv.org
Train machine learning models on sensitive user data has raised increasing privacy concerns in many areas. Federated learning is a popular approach for privacy protection …
Federated learning (FL) allows to train a massive amount of data privately due to its decentralized structure. Stochastic gradient descent (SGD) is commonly used for FL due to …
C Wang, X Wu, G Liu, T Deng, K Peng… - Digital Communications …, 2022 - Elsevier
Federated Learning (FL) is a new computing paradigm in privacy-preserving Machine Learning (ML), where the ML model is trained in a decentralized manner by the clients …
R Hu, Y Guo, Y Gong - IEEE Transactions on Mobile Computing, 2023 - ieeexplore.ieee.org
Federated learning (FL) that enables edge devices to collaboratively learn a shared model while keeping their training data locally has received great attention recently and can protect …
X Yang, W Huang, M Ye - Advances in Neural Information …, 2023 - proceedings.neurips.cc
Personalized federated learning with differential privacy has been considered a feasible solution to address non-IID distribution of data and privacy leakage risks. However, current …
Federated Learning (FL) is a promising machine learning paradigm that enables the analyzer to train a model without collecting users' raw data. To ensure users' privacy …
Local differential privacy (LDP) is a recently proposed privacy standard for collecting and analyzing data, which has been used, eg, in the Chrome browser, iOS and macOS. In LDP …
Z He, L Wang, Z Cai - IEEE Internet of Things Journal, 2023 - ieeexplore.ieee.org
The Internet of Things (IoT) is penetrating many aspects of our daily life with the proliferation of artificial intelligence applications. Federated learning (FL) has emerged as a promising …
X Gu, M Li, L Xiong, Y Cao - 2020 IEEE 36th International …, 2020 - ieeexplore.ieee.org
Local Differential Privacy (LDP) provides provable privacy protection for data collection without the assumption of the trusted data server. In the real-world scenario, different data …