Blockchain-empowered federated learning: Challenges, solutions, and future directions
Federated learning is a privacy-preserving machine learning technique that trains models
across multiple devices holding local data samples without exchanging them. There are …
across multiple devices holding local data samples without exchanging them. There are …
A review of applications in federated learning
L Li, Y Fan, M Tse, KY Lin - Computers & Industrial Engineering, 2020 - Elsevier
Federated Learning (FL) is a collaboratively decentralized privacy-preserving technology to
overcome challenges of data silos and data sensibility. Exactly what research is carrying the …
overcome challenges of data silos and data sensibility. Exactly what research is carrying the …
Towards personalized federated learning
In parallel with the rapid adoption of artificial intelligence (AI) empowered by advances in AI
research, there has been growing awareness and concerns of data privacy. Recent …
research, there has been growing awareness and concerns of data privacy. Recent …
Lightweight blockchain-empowered secure and efficient federated edge learning
Federated Learning (FL) has emerged as a privacy-preserving distributed Machine Learning
paradigm, which collaboratively trains a shared global model across a number of end …
paradigm, which collaboratively trains a shared global model across a number of end …
A review of secure federated learning: privacy leakage threats, protection technologies, challenges and future directions
L Ge, H Li, X Wang, Z Wang - Neurocomputing, 2023 - Elsevier
Advances in the new generation of Internet of Things (IoT) technology are propelling the
growth of intelligent industrial applications worldwide. Simultaneously, widespread adoption …
growth of intelligent industrial applications worldwide. Simultaneously, widespread adoption …
[HTML][HTML] Fedmed: A federated learning framework for language modeling
X Wu, Z Liang, J Wang - Sensors, 2020 - mdpi.com
Federated learning (FL) is a privacy-preserving technique for training a vast amount of
decentralized data and making inferences on mobile devices. As a typical language …
decentralized data and making inferences on mobile devices. As a typical language …
How to prevent the poor performance clients for personalized federated learning?
Personalized federated learning (pFL) collaboratively trains personalized models, which
provides a customized model solution for individual clients in the presence of …
provides a customized model solution for individual clients in the presence of …
Uncertainty-aware aggregation for federated open set domain adaptation
Z Qin, L Yang, F Gao, Q Hu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Open set domain adaptation (OSDA) methods have been proposed to leverage the
difference between the source and target domains, as well as to recognize the known and …
difference between the source and target domains, as well as to recognize the known and …
[HTML][HTML] Individualised responsible artificial intelligence for home-based rehabilitation
Socioeconomic reasons post-COVID-19 demand unsupervised home-based rehabilitation
and, specifically, artificial ambient intelligence with individualisation to support engagement …
and, specifically, artificial ambient intelligence with individualisation to support engagement …