2.隐私异构性,用户数据隐私级别不同,有些是可以公开的,有些必须保护。3.模型异构性,客户端使用本地数据训练出的模型是异构的。在本文中作者提出HPFL模型(Hierarchical Personalized Federated Learning)用于在联邦学习中为不一致的客户端建模。 回到顶部(go to top) 算法 整体框架图如下 客户端设计 客户端主要负责两...
方法:1. 提出一个带有层次聚类(针对鲁棒性和公平的HAR)个性化的FL框架FedCHAR;通过聚类(利用用户之间的内在相似关系)提高模型性能的准确性、公平性、鲁棒性。 2. 提高FedCHAR的可扩展性:提出FedCHAR-DC一个可扩展和自适应的FL框架——动态聚类、自适应新客户端的加入、针对现实场景不断变化的数据集。 问题:1. ...
In this paper, we propose a novel client-server architecture framework, namely Hierarchical Personalized Federated Learning (HPFL) to serve federated learning in user modeling with inconsistent clients. In the framework, we first define hierarchical information to finely partition the data with privacy ...
For instance, on the CIFAR-100 dataset, FedFCD exhibited a significant improvement in average test accuracy by 6.83% compared to four outstanding personalized federated learning approaches. Furthermore, extended experiments confirm the robustness of FedFCD across various hyperparameter values....
Cheng, FedHAR: Semi-supervised online learning for personalized federated human activity recognition, IEEE Trans. Mob. Comput., vol. 22, no. 6, pp. 3318–3332, 2023. Crossref Google Scholar [8] V. Zeufack, D. Kim, D. Seo, and A. Lee, An unsupervised anomaly detection framework for...
Algorithms for Selecting the Optimum Dataset While Providing Personalized Privacy and Compensation to its Participants The privacy preserving microdata sharing literature has proposed several techniques that allow a database administrator to share a dataset in a privacy pre... R Kumar - 《International Jo...
Semantic-enhanced bayesian personalized explanation ranking AutoML: Automated machine learning FNN: Fuzzy neural network AHP: Analytic hierarchy process FNN-P: Processed training data FNN-R: Raw training data SVM +ELM+MK: Support vector machine and extreme learning machine based on modified k...
The presence of time-varying data heterogeneity and computational resource inadequacy among device clusters motivate four key parts of our methodology: (i) stratified UAV swarms of leader, worker, and coordinator UAVs, (ii) hierarchical nested personalized federated learning (HN-PFL), a distributed ...
Hierarchical Personalized Federated Learning for User Modeling The local user models trained with client records are heterogeneous which need flexible aggregation in the server. In this paper, we propose a novel client-server architecture framework, namely Hierarchical Personalized Federated Learning (HP.....
鈥擣ederated learning performance depends on the data distribution, presenting lower performance in scenarios where clients hold heterogeneous data. We pro... LACD Souza,G Camilo,MEM Campista,... 被引量: 0发表: 2023年 Hierarchical Personalized Federated Learning for User Modeling User modeling aims...