Benzer Materyaller

• Tight Differential Privacy Guarantees for the Shuffle Model with $k$-Randomized Response
  Yazar:: Biswas, Sayan, ve diğerleri
  Baskı/Yayın Bilgisi: (2022)
• Protection against Source Inference Attacks in Federated Learning
  Yazar:: Athanasiou, Andreas, ve diğerleri
  Baskı/Yayın Bilgisi: (2026)
• Protection against Source Inference Attacks in Federated Learning using Unary Encoding and Shuffling
  Yazar:: Athanasiou, Andreas, ve diğerleri
  Baskı/Yayın Bilgisi: (2024)
• Metric Privacy in Federated Learning for Medical Imaging: Improving Convergence and Preventing Client Inference Attacks
  Yazar:: Díaz, Judith Sáinz-Pardo, ve diğerleri
  Baskı/Yayın Bilgisi: (2025)
• Jeffrey's update rule as a minimizer of Kullback-Leibler divergence
  Yazar:: Pinzón, Carlos, ve diğerleri
  Baskı/Yayın Bilgisi: (2025)