Heterogeneous federated learning: State-of-the-art and research challenges
Federated learning (FL) has drawn increasing attention owing to its potential use in large-
scale industrial applications. Existing FL works mainly focus on model homogeneous …
scale industrial applications. Existing FL works mainly focus on model homogeneous …
Federated learning review: Fundamentals, enabling technologies, and future applications
Federated Learning (FL) has been foundational in improving the performance of a wide
range of applications since it was first introduced by Google. Some of the most prominent …
range of applications since it was first introduced by Google. Some of the most prominent …
Blockchain-based federated learning for securing internet of things: A comprehensive survey
The Internet of Things (IoT) ecosystem connects physical devices to the internet, offering
significant advantages in agility, responsiveness, and potential environmental benefits. The …
significant advantages in agility, responsiveness, and potential environmental benefits. The …
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 …
Federated semi-supervised learning for COVID region segmentation in chest CT using multi-national data from China, Italy, Japan
The recent outbreak of Coronavirus Disease 2019 (COVID-19) has led to urgent needs for
reliable diagnosis and management of SARS-CoV-2 infection. The current guideline is using …
reliable diagnosis and management of SARS-CoV-2 infection. The current guideline is using …
Fedproc: Prototypical contrastive federated learning on non-iid data
Federated learning (FL) enables multiple clients to jointly train high-performance deep
learning models while maintaining the training data locally. However, it is challenging to …
learning models while maintaining the training data locally. However, it is challenging to …
Collaborative unsupervised visual representation learning from decentralized data
Unsupervised representation learning has achieved outstanding performances using
centralized data available on the Internet. However, the increasing awareness of privacy …
centralized data available on the Internet. However, the increasing awareness of privacy …
Divergence-aware federated self-supervised learning
Self-supervised learning (SSL) is capable of learning remarkable representations from
centrally available data. Recent works further implement federated learning with SSL to …
centrally available data. Recent works further implement federated learning with SSL to …
Federated unsupervised representation learning
To leverage the enormous amount of unlabeled data on distributed edge devices, we
formulate a new problem in federated learning called federated unsupervised …
formulate a new problem in federated learning called federated unsupervised …
Federated learning and its role in the privacy preservation of IoT devices
Federated learning (FL) is a cutting-edge artificial intelligence approach. It is a decentralized
problem-solving technique that allows users to train using massive data. Unprocessed …
problem-solving technique that allows users to train using massive data. Unprocessed …