Jiachen-T-Wang / data-banzhaf

Related projects ⓘ

Alternatives and complementary repositories for data-banzhaf

• JialinMao / private_CNN
  ☆10Updated 2 years ago
• woodyx218 / opacus_global_clipping
  ☆13Updated last year
• lhfowl / robbing_the_fed
  ☆23Updated 2 years ago
• AI-secure / DataLens
  [CCS 2021] "DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation" by Boxin Wang*, Fan Wu*, Yunhui Long…
  ☆37Updated 2 years ago
• facebookresearch / label_dp_antipodes
  Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"
  ☆30Updated 2 years ago
• litian96 / AdaDPS
  Private Adaptive Optimization with Side Information (ICML '22)
  ☆16Updated 2 years ago
• yzeng58 / Improving-Fairness-via-Federated-Learning
  ☆12Updated last year
• inspire-group / MIAdefenseSELENA
  [USENIX Security 2022] Mitigating Membership Inference Attacks by Self-Distillation Through a Novel Ensemble Architecture
  ☆16Updated 2 years ago
• zhenglisec / Label-Only-MIA
  ☆19Updated last month
• ganeshdg95 / Leveraging-Adversarial-Examples-to-Quantify-Membership-Information-Leakage
  ☆19Updated last year
• alewarne / MachineUnlearning
  Code related to the paper "Machine Unlearning of Features and Labels"
  ☆68Updated 8 months ago
• DingfanChen / RelaxLoss
  Official implementation of "RelaxLoss: Defending Membership Inference Attacks without Losing Utility" (ICLR 2022)
  ☆45Updated 2 years ago
• meghdadk / SCRUB
  ☆38Updated 2 months ago
• microsoft / prv_accountant
  A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.
  ☆67Updated 8 months ago
• jagielski / auditing-dpsgd
  Code for Auditing DPSGD
  ☆35Updated 2 years ago
• kenziyuliu / private-cross-silo-fl
  [NeurIPS 2022] JAX/Haiku implementation of "On Privacy and Personalization in Cross-Silo Federated Learning"
  ☆25Updated last year
• jeremy43 / Private_kNN
  ☆24Updated 2 years ago
• dayu11 / Differentially-Private-Deep-Learning
  This repo implements several algorithms for learning with differential privacy.
  ☆101Updated last year
• DennisLiu2022 / Membership-Inference-Attacks-by-Exploiting-Loss-Trajectory
  ☆23Updated last year
• Jimmy-di / camouflage-poisoning
  Camouflage poisoning via machine unlearning
  ☆15Updated last year
• krishnap25 / simplicial-fl
  Simplicial-FL to manage client device heterogeneity in Federated Learning
  ☆21Updated last year
• MinChen00 / UnlearningLeaks
  Official implementation of "When Machine Unlearning Jeopardizes Privacy" (ACM CCS 2021)
  ☆46Updated 2 years ago
• google-research / public-data-in-dpfl
  ☆22Updated last year
• AI-secure / Shapley-Study
  [CVPR 2021] Scalability vs. Utility: Do We Have to Sacrifice One for the Other in Data Importance Quantification?
  ☆31Updated 3 years ago
• wanglun1996 / secure-robust-federated-learning
  ☆53Updated last year
• AISafety-HKUST / stable_backdoor_purification
  Stable Backdoor Purification (NeurIPS 2023 & 2024)
  ☆23Updated this week
• illidanlab / inversion-influence-function
  Official codes for "Understanding Deep Gradient Leakage via Inversion Influence Functions", NeurIPS 2023
  ☆15Updated last year
• OPTML-Group / Unlearn-Sparse
  [NeurIPS23 (Spotlight)] "Model Sparsity Can Simplify Machine Unlearning" by Jinghan Jia*, Jiancheng Liu*, Parikshit Ram, Yuguang Yao, Gao…
  ☆62Updated 7 months ago
• facebookresearch / certified-removal
  Certified Removal from Machine Learning Models
  ☆63Updated 3 years ago
• shrezaei / MI-Attack
  ☆32Updated 2 months ago