[HTML][HTML] 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 …
Communication-efficient distributed deep learning: A comprehensive survey
Distributed deep learning (DL) has become prevalent in recent years to reduce training time
by leveraging multiple computing devices (eg, GPUs/TPUs) due to larger models and …
by leveraging multiple computing devices (eg, GPUs/TPUs) due to larger models and …
Fedml: A research library and benchmark for federated machine learning
Federated learning (FL) is a rapidly growing research field in machine learning. However,
existing FL libraries cannot adequately support diverse algorithmic development; …
existing FL libraries cannot adequately support diverse algorithmic development; …
Gossipfl: A decentralized federated learning framework with sparsified and adaptive communication
Recently, federated learning (FL) techniques have enabled multiple users to train machine
learning models collaboratively without data sharing. However, existing FL algorithms suffer …
learning models collaboratively without data sharing. However, existing FL algorithms suffer …
Decentralized federated learning: A survey and perspective
Federated learning (FL) has been gaining attention for its ability to share knowledge while
maintaining user data, protecting privacy, increasing learning efficiency, and reducing …
maintaining user data, protecting privacy, increasing learning efficiency, and reducing …
Decentralised learning in federated deployment environments: A system-level survey
Decentralised learning is attracting more and more interest because it embodies the
principles of data minimisation and focused data collection, while favouring the transparency …
principles of data minimisation and focused data collection, while favouring the transparency …
Accelerating decentralized federated learning in heterogeneous edge computing
In edge computing (EC), federated learning (FL) enables massive devices to collaboratively
train AI models without exposing local data. In order to avoid the possible bottleneck of the …
train AI models without exposing local data. In order to avoid the possible bottleneck of the …
Decentralized federated learning for UAV networks: Architecture, challenges, and opportunities
Unmanned aerial vehicles (UAVs), or drones, are envisioned to support extensive
applications in next-generation wireless networks in both civil and military fields …
applications in next-generation wireless networks in both civil and military fields …
A review of federated learning in intrusion detection systems for iot
Intrusion detection systems are evolving into intelligent systems that perform data analysis
searching for anomalies in their environment. The development of deep learning …
searching for anomalies in their environment. The development of deep learning …
Fusionai: Decentralized training and deploying llms with massive consumer-level gpus
The rapid growth of memory and computation requirements of large language models
(LLMs) has outpaced the development of hardware, hindering people who lack large-scale …
(LLMs) has outpaced the development of hardware, hindering people who lack large-scale …