Ngā tūemi rite

• A Unified Learn-to-Distort-Data Framework for Privacy-Utility Trade-off in Trustworthy Federated Learning
  mā: Zhang, Xiaojin, me ētahi atu.
  I whakaputaina: (2024)
• Deciphering the Interplay between Attack and Protection Complexity in Privacy-Preserving Federated Learning
  mā: Zhang, Xiaojin, me ētahi atu.
  I whakaputaina: (2025)
• A Game-theoretic Framework for Privacy-preserving Federated Learning
  mā: Zhang, Xiaojin, me ētahi atu.
  I whakaputaina: (2023)
• Theoretical Analysis of Privacy Leakage in Trustworthy Federated Learning: A Perspective from Linear Algebra and Optimization Theory
  mā: Zhang, Xiaojin, me ētahi atu.
  I whakaputaina: (2024)
• Towards Privacy-Preserving Data-Driven Education: The Potential of Federated Learning
  mā: Khalil, Mohammad, me ētahi atu.
  I whakaputaina: (2025)