Federated Learning(FL) is a popular privacy-preserving machine learning paradigm that enables the creation of a robust centralized model without sacrificing the privacy of clients' data. FL has a wide range of applications, but it does not integrate the idea of...Muhammad, Adil...
3.3.1SQL extension for RDF The emergence of the Semantic Web is enabling new approaches to federated data queries. RDF promotes universally grounded identifiers for data, allowing the SPARQL query language for RDF to perform joins across different data sources. There is no standard SQL extension to...
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
A Novel Federated Learning Framework Based on Trust Evaluation in Internet of Vehicles With the continuous progress of the society, Intelligent Connected Vehicles (ICVs) in Internet of Vehicles (IoVs) continuously generate a large amount of d... NA Wan,D Wang - Ad-hoc & sensor wireless...
In the realm of deep learning applications, researchers have explored various aspects of anomaly detection models, as summarized by Chalapathy et al. [9]. Furthermore, Yin et al. [10] introduced an enhanced mobile edge computing solution that combines federated learning with the CNN algorithm. ...
invokehttp procedure 13. federated planning federated planning 13.1. federated planning 13.2. planning overview 13.3. example query 13.4. subquery optimization 13.5. xquery optimization 13.6. partial results 13.7. federated optimizations federated optimizations...
Guo K, Chen T, Ren S, Li N, Hu M, Kang J (2022) Federated learning empowered real-time medical data processing method for smart healthcare. IEEE/ACM Trans Comput Biol Bioinform Guo K, Shen C, Hu B, Hu M, Kui X (2022) RSNet: relation separation network for few-shot similar class...
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...