ลงชื่อเข้าใช้
ข้อมูลเชิงลึก - Privacy-Preserving Synthetic Data Generation
Efficient Privacy-Preserving Synthetic Data Generation for Tabular Data Sharing
ϵ-PrivateSMOTE is a novel strategy that combines synthetic data generation via noise-induced interpolation with Differential Privacy principles to efficiently safeguard against re-identification and linkage attacks, particularly for high-risk cases.
Knowledge Infusion in Privacy-Preserving Synthetic Data Generation: The KIPPS Framework
The KIPPS framework enhances privacy-preserving synthetic data generation by incorporating domain knowledge from Knowledge Graphs to address challenges related to data diversity, complexity, and domain-specific constraints.
เกี่ยวกับ
ผลิตภัณฑ์ | แหล่งข้อมูล
© 2024 by Linnk AI