In this paper, we present an advanced intrusion detection system that leverages federated learning (FL) and deep learning (DL) techniques to check whether attacks occur or not on SDN. FL has been employed as a collaborative learning technique, enabling various data planes to conduct local ...
原文链接:https://arxiv.org/abs/1910.01991 发表:IEEE Transactions on Neural Networks and Learning Systems2021 code: https://github.com/felisat/clustered-federated-learning 编辑:古月 目的:传统联邦学习中,存在这个假设: 训练一组模型,使得所有得到用户都能满足最小化风险函数的目标: 假设1 但是,显然这种假...
Federated Learning (FL) is currently the most widely adopted framework for collaborative training of (deep) machine learning models under privacy constraints. Albeit it's popularity, it has been observed that Federated Learning yields suboptimal results if the local clients' data distributions diverge....
写不出论文了,兴趣使然地开一个论文笔记系列,不知道毕业的时候能写到多少篇(苦笑)。论文名称'Clustered federated learning: Model-Agnostic distributed multi-Task optimization under privacy constrain
Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints - felisat/clustered-federated-learning
The 2021 Federated Tumor Segmentation (FeTS) challenge provides clinically acquired multi-institutional magnetic resonance imaging (MRI) scans from patients with brain cancer and aims to compare federated learning models. In this work, we propose a travelling model that visits each collaborator site up...
Federated Learning for Long-term Forecasting of Electricity Consumption towards a Carbon-neutral Future 2022, 2022 7th International Conference on Intelligent Computing and Signal Processing, ICSP 2022 View all citing articles on Scopus © 2022 The Author(s). Published by Elsevier Ltd. ...
Hence many research networks such as OHDSI and PCORnet have adopted a federated model in which patient-level data are stored at local institutions and often only aggregated information are shared across sites5,6,7. Second, data from different sites are often heterogeneous with respect to patient ...
Yoo, E., Ko, H. & Pack, S. Fuzzy clustered federated learning algorithm for solar power generation forecasting.IEEE Trans. Emerg. Top. Comput.10(4), 2092–2098 (2022). ArticleGoogle Scholar Yu, L.et al.Application of a novel time-delayed power-driven grey model to forecast photovoltaic...
This post illustrates how to build federated, hub-and-spoke model registries, where multiple spoke accounts use the SageMaker Model Registry from a hub account to register their model package groups and versions. The following diagram illustrates two possible patterns: a pus...