[HTML][HTML] Model aggregation techniques in federated learning: A comprehensive survey
Federated learning (FL) is a distributed machine learning (ML) approach that enables
models to be trained on client devices while ensuring the privacy of user data. Model …
models to be trained on client devices while ensuring the privacy of user data. Model …
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 …
Hierarchical personalized federated learning over massive mobile edge computing networks
Personalized Federated Learning (PFL) is a new Federated Learning (FL) paradigm,
particularly tackling the heterogeneity issues brought by various mobile user equipments …
particularly tackling the heterogeneity issues brought by various mobile user equipments …
Ensemble distillation based adaptive quantization for supporting federated learning in wireless networks
Federated learning (FL) has become a promising technique for develo** intelligent
wireless networks. In traditional FL paradigms, local models are usually required to be …
wireless networks. In traditional FL paradigms, local models are usually required to be …
In-network computation for large-scale federated learning over wireless edge networks
Most conventional Federated Learning (FL) models are using a star network topology where
all users aggregate their local models at a single server (eg, a cloud server). That causes …
all users aggregate their local models at a single server (eg, a cloud server). That causes …
A Mixed Integer Linear Programming Formulation and Heuristics for Delay-Aware Neural Network Placement Problem in In-Network Learning
T Hara - 2024 - researchsquare.com
Abstract In-network learning (INL), which is one of the distributed machine learning (ML),
enables both learning and inference over a network by deploying small models representing …
enables both learning and inference over a network by deploying small models representing …
[CITATION][C] Kommunikations-und Aggregationsmethoden für das föderale Lernen
L Wulfert - Dissertation, Duisburg, Essen …