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 …
Recent advances on federated learning for cybersecurity and cybersecurity for federated learning for internet of things
Decentralized paradigm in the field of cybersecurity and machine learning (ML) for the
emerging Internet of Things (IoT) has gained a lot of attention from the government …
emerging Internet of Things (IoT) has gained a lot of attention from the government …
A state-of-the-art survey on solving non-iid data in federated learning
Federated Learning (FL) proposed in recent years has received significant attention from
researchers in that it can enable multiple clients to cooperatively train global models without …
researchers in that it can enable multiple clients to cooperatively train global models without …
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 …
Ditto: Fair and robust federated learning through personalization
Fairness and robustness are two important concerns for federated learning systems. In this
work, we identify that robustness to data and model poisoning attacks and fairness …
work, we identify that robustness to data and model poisoning attacks and fairness …
Fedproto: Federated prototype learning across heterogeneous clients
Heterogeneity across clients in federated learning (FL) usually hinders the optimization
convergence and generalization performance when the aggregation of clients' knowledge …
convergence and generalization performance when the aggregation of clients' knowledge …
Federated machine learning: Survey, multi-level classification, desirable criteria and future directions in communication and networking systems
The communication and networking field is hungry for machine learning decision-making
solutions to replace the traditional model-driven approaches that proved to be not rich …
solutions to replace the traditional model-driven approaches that proved to be not rich …
A survey on security and privacy of federated learning
Federated learning (FL) is a new breed of Artificial Intelligence (AI) that builds upon
decentralized data and training that brings learning to the edge or directly on-device. FL is a …
decentralized data and training that brings learning to the edge or directly on-device. FL is a …
Federated multi-task learning under a mixture of distributions
The increasing size of data generated by smartphones and IoT devices motivated the
development of Federated Learning (FL), a framework for on-device collaborative training of …
development of Federated Learning (FL), a framework for on-device collaborative training of …