Artificial Intelligence
联邦迁移学习
Federated Transfer LearningA distributed machine learning approach that enables model training across decentralized edge devices or servers holding local data samples, without exchanging them, while leveraging transfer learning techniques to improve performance on target tasks. / 一种分布式机器学习方法，允许在持有本地数据样本的去中心化边缘设备或服务器上进行模型训练，且无需交换数据，同时利用迁移学习技术来提高目标任务的性能。
- Knowledge type
- 实际应用
- First proposed or discovered
- Proposer
- Turkey Farm member
- Creator
- 农场主
- Last updated
- 2026-10-17 16:02:25
Sub-knowledge points
Communication-efficient Federated LearningTransfer Learning for IoT Security
Higher-order knowledge points
Main parameters and performance indicators
Communication Efficiency: Optimization of data transmission overheadReal-time Inference: Low-latency detection capabilities
Open problems
No unresolved problem recorded yet
Related literature
ranked by community starsCommunication-efficient Federated Transfer Learning for real-time intrusion detection in agricultural IoT systemsOpen source
Related products and links
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Creation and modification trail
1 recordsRecord title: Federated Transfer Learning.
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