REMISVFU: Federated Unlearning with Representation Misdirection
Published:Dec 11, 2025 07:05
•1 min read
•ArXiv
Analysis
This research explores federated unlearning in a vertical setting using a novel representation misdirection technique. The core concept likely focuses on how to remove or mitigate the impact of specific data points from a federated model while preserving its overall performance.
Key Takeaways
Reference
“The article's context indicates the research is published on ArXiv, suggesting a focus on academic novelty.”