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HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems
Posted by Mark Field in Computer Science & IT and Edge Computing

Machine Learning

Artificial Intelligence

Distributed, Parallel, and Cluster Computing

Split federated learning (SFL) has emerged as a promising paradigm to democratize machine learning (ML) on edge devices by enabling layer-wise model partitioning. However, existing SFL appro....
Joint Computation Offloading and Resource Allocation for Uncertain Maritime MEC ...
Posted by Mark Field in Computer Science & IT and Edge Computing

Artificial Intelligence

Signal Processing

The computation demands from the maritime Internet of Things (MIoT) increase rapidly in recent years, and the unmanned aerial vehicles (UAVs) and vessels based multi-access edge computing (M....
Topology-Aware Virtualization over Inter-Core Connected Neural Processing Units
Posted by Mark Field in Computer Science & IT and Edge Computing

Hardware Architecture

Distributed, Parallel, and Cluster Computing

With the rapid development of artificial intelligence (AI) applications, an emerging class of AI accelerators, termed Inter-core Connected Neural Processing Units (NPU), has been adopted in ....
FAuNO: Semi-Asynchronous Federated Reinforcement Learning Framework for Task Off ...
Posted by Mark Field in Computer Science & IT and Edge Computing

Artificial Intelligence

Machine Learning

Edge computing addresses the growing data demands of connected-device networks by placing computational resources closer to end users through decentralized infrastructures. This decentraliza....