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Found 5 papers, 2 papers with code
Wireless Ad Hoc Federated Learning: A Fully Distributed Cooperative Machine Learning
Federated learning has allowed training of a global model by aggregating local models trained on local nodes.
Reinforcement Learning Based Optimal Camera Placement for Depth Observation of Indoor Scenes
The experimental results indicate that the proposed system outperforms seven out of ten test scenes in obtaining lower depth observation error.
Decentralized Deep Learning for Multi-Access Edge Computing: A Survey on Communication Efficiency and Trustworthiness
Wider coverage and a better solution to a latency reduction in 5G necessitate its combination with multi-access edge computing (MEC) technology.
Adaptive Intrusion Detection in the Networking of Large-Scale LANs with Segmented Federated Learning
We propose Segmented-Federated Learning (Segmented-FL), where by employing periodic local model evaluation and network segmentation, we aim to bring similar network environments to the same group.
Intrusion Detection with Segmented Federated Learning for Large-Scale Multiple LANs
In this research, a segmented federated learning is proposed, different from a collaborative learning based on single global model in a traditional federated learning model, it keeps multiple global models which allow each segment of participants to conduct collaborative learning separately and rearranges the segmentation of participants dynamically as well.
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Network Intrusion Detection
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