JeffffffFu/Awesome-Differential-Privacy-and-Meachine-Learning

  • 类型:github
  • 标识:JeffffffFu/Awesome-Differential-Privacy-and-Meachine-Learning
  • 链接:https://github.com/JeffffffFu/Awesome-Differential-Privacy-and-Meachine-Learning
  • 主分类:risk
  • 形态:awesome
  • 分类:academic-writing
  • 学术复核时间:2026-08-11T22:01:03+08:00
  • 学术证据:anchor:systematic review; task:systematic-review:systematic review; task:systematic-review:系统综述
  • 学术判定:deterministic
  • 学术相关度:85
  • 能力分面:citation
  • 学术用途:systematic-review
  • 学术主任务:systematic-review
  • 学术阶段:evidence
  • 学术状态:accepted
  • 学术方向:summarize
  • Stars:388
  • 周增:+0
  • 语言:Python
  • 最近提交:2025-09-02
  • 简介:Differentially private federated learning: A systematic review (ACM Survey); Adap dp-fl: Differentially private federated learning with adaptive noise (TrustCom'2022)
  • 上次采集:2026-08-11
  • 首次采集:2026-08-04
  • 待LLM分类:否
  • 成熟度:research
  • 简介中文:差分隐私联邦学习系统综述(ACM Survey);Adap dp-fl:自适应噪声的差分隐私联邦学习(TrustCom'2022)
  • 场景:differential privacy、federated learning
  • 来源文件
  • [GitHub Search]