Ngā tūemi rite

• United We Defend: Collaborative Membership Inference Defenses in Federated Learning
  mā: Bai, Li, me ētahi atu.
  I whakaputaina: (2026)
• A Sample-Level Evaluation and Generative Framework for Model Inversion Attacks
  mā: Li, Haoyang, me ētahi atu.
  I whakaputaina: (2025)
• Toward Efficient Inference Attacks: Shadow Model Sharing via Mixture-of-Experts
  mā: Bai, Li, me ētahi atu.
  I whakaputaina: (2025)
• PriPL-Tree: Accurate Range Query for Arbitrary Distribution under Local Differential Privacy
  mā: Wang, Leixia, me ētahi atu.
  I whakaputaina: (2024)
• AdvSGM: Differentially Private Graph Learning via Adversarial Skip-gram Model
  mā: Zhang, Sen, me ētahi atu.
  I whakaputaina: (2025)