Federated Machine Learning Outperforms Centralized Machine Learning for Fraud Detection: Evidence From 284,807 Real-World Transactions [Abstract]
Samuel Sambasivam
- Published
- Publisher
- Informing Science Institute
- Journal / collection
- InSITE Conference
- Research area
- AI & compute
- Source type
- Conference paper
- DOI
- 10.28945/5800
The original publisher provides the full text and its access options.
Cite this source
Samuel Sambasivam. Federated Machine Learning Outperforms Centralized Machine Learning for Fraud Detection: Evidence From 284,807 Real-World Transactions [Abstract]. InSITE Conference. 2026. https://doi.org/10.28945/5800