Addressing Skewed Heterogeneity via Federated Prototype Rectification With Personalization
Federated learning (FL) is an efficient framework designed to facilitate collaborative model
training across multiple distributed devices while preserving user data privacy. A significant …
training across multiple distributed devices while preserving user data privacy. A significant …
[HTML][HTML] Preventing harm to the rare in combating the malicious: A filtering-and-voting framework with adaptive aggregation in federated learning
The distributed nature of Federated Learning (FL) introduces security vulnerabilities and
issues related to the heterogeneous distribution of data. Traditional FL aggregation …
issues related to the heterogeneous distribution of data. Traditional FL aggregation …
Smart Contract Vulnerability Detection Based on Generative Adversarial Networks and Graph Matching Networks
With Blockchain technology's tamper-proof and decentralized characteristics, smart
contracts have been developed rapidly for wide application in critical areas, eg, the Internet …
contracts have been developed rapidly for wide application in critical areas, eg, the Internet …