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 …
Distributed learning in wireless networks: Recent progress and future challenges
The next-generation of wireless networks will enable many machine learning (ML) tools and
applications to efficiently analyze various types of data collected by edge devices for …
applications to efficiently analyze various types of data collected by edge devices for …
Edge artificial intelligence for 6G: Vision, enabling technologies, and applications
The thriving of artificial intelligence (AI) applications is driving the further evolution of
wireless networks. It has been envisioned that 6G will be transformative and will …
wireless networks. It has been envisioned that 6G will be transformative and will …
Federated learning on non-IID data: A survey
Federated learning is an emerging distributed machine learning framework for privacy
preservation. However, models trained in federated learning usually have worse …
preservation. However, models trained in federated learning usually have worse …
[HTML][HTML] Federated learning for 6G: Applications, challenges, and opportunities
Standard machine-learning approaches involve the centralization of training data in a data
center, where centralized machine-learning algorithms can be applied for data analysis and …
center, where centralized machine-learning algorithms can be applied for data analysis and …
Federated-learning based privacy preservation and fraud-enabled blockchain IoMT system for healthcare
These days, the usage of machine-learning-enabled dynamic Internet of Medical Things
(IoMT) systems with multiple technologies for digital healthcare applications has been …
(IoMT) systems with multiple technologies for digital healthcare applications has been …
Computing in the sky: A survey on intelligent ubiquitous computing for uav-assisted 6g networks and industry 4.0/5.0
Unmanned Aerial Vehicles (UAVs) are increasingly being used in a high-computation
paradigm enabled with smart applications in the Beyond Fifth Generation (B5G) wireless …
paradigm enabled with smart applications in the Beyond Fifth Generation (B5G) wireless …
Fast-convergent federated learning
Federated learning has emerged recently as a promising solution for distributing machine
learning tasks through modern networks of mobile devices. Recent studies have obtained …
learning tasks through modern networks of mobile devices. Recent studies have obtained …
Topology-aware federated learning in edge computing: A comprehensive survey
The ultra-low latency requirements of 5G/6G applications and privacy constraints call for
distributed machine learning systems to be deployed at the edge. With its simple yet …
distributed machine learning systems to be deployed at the edge. With its simple yet …
Joint user association and resource allocation for wireless hierarchical federated learning with IID and non-IID data
In this work, hierarchical federated learning (HFL) over wireless multi-cell networks is
proposed for large-scale model training while preserving data privacy. However, the …
proposed for large-scale model training while preserving data privacy. However, the …