google-research / label-dp

Related projects ⓘ

Alternatives and complementary repositories for label-dp

• google-deepmind / informed_adversary_mnist_reconstruction
  ☆16Updated 2 years ago
• google-deepmind / jax_privacy
  Algorithms for Privacy-Preserving Machine Learning in JAX
  ☆89Updated 5 months ago
• sarus-tech / dp-xgboost
  ☆23Updated 10 months ago
• google-research / dp-imagenet
  ☆36Updated 2 years ago
• MadryLab / datamodels
  ☆22Updated last year
• microsoft / prv_accountant
  A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.
  ☆70Updated 9 months ago
• ftramer / Handcrafted-DP
  ☆79Updated 2 years ago
• TheSalon / fast-dpsgd
  Code for fast dpsgd implementations in JAX/TF
  ☆58Updated 2 years ago
• facebookresearch / tan
  Computationally friendly hyper-parameter search with DP-SGD
  ☆22Updated 2 years ago
• google-research / public-data-in-dpfl
  ☆22Updated last year
• ebagdasa / differential-privacy-vs-fairness
  Code for "Differential Privacy Has Disparate Impact on Model Accuracy" NeurIPS'19
  ☆34Updated 3 years ago
• MadryLab / modeldiff
  ModelDiff: A Framework for Comparing Learning Algorithms
  ☆53Updated last year
• spliew / shuffgauss
  ☆10Updated last year
• AnonymousNIPS2019 / DeepnetHessian
  The Full Spectrum of Deepnet Hessians at Scale: Dynamics with SGD Training and Sample Size
  ☆17Updated 5 years ago
• facebookresearch / bounding_data_reconstruction
  Repo for the paper "Bounding Training Data Reconstruction in Private (Deep) Learning".
  ☆10Updated last year
• facebookresearch / label_dp_antipodes
  Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"
  ☆30Updated 2 years ago
• alshedivat / fedpa
  Federated posterior averaging implemented in JAX
  ☆49Updated last year
• google-research / DP-FTRL
  DP-FTRL from "Practical and Private (Deep) Learning without Sampling or Shuffling" for centralized training.
  ☆25Updated 3 months ago
• facebookresearch / Opacus-lab
  Research and experimental code related to Opacus, an open-source library for training PyTorch models with Differential Privacy
  ☆17Updated last month
• MadryLab / failure-directions
  Distilling Model Failures as Directions in Latent Space
  ☆45Updated last year
• tml-epfl / sgd-sparse-features
  SGD with large step sizes learns sparse features [ICML 2023]
  ☆32Updated last year
• facebookresearch / dp_compression
  Code repo for the paper "Privacy-aware Compression for Federated Data Analysis".
  ☆16Updated last year
• dayu11 / Gradient-Embedding-Perturbation
  ☆27Updated last year
• mmalekzadeh / privacy-preserving-bandits
  Privacy-Preserving Bandits (MLSys'20)
  ☆22Updated last year
• jagielski / auditing-dpsgd
  Code for Auditing DPSGD
  ☆35Updated 2 years ago
• js-d / sim_metric
  ☆35Updated last year
• MadryLab / DebuggableDeepNetworks
  ☆37Updated 3 years ago
• ethz-spylab / realistic-adv-examples
  Code for the paper "Evading Black-box Classifiers Without Breaking Eggs" [SaTML 2024]
  ☆19Updated 7 months ago
• lxuechen / private-transformers
  A codebase that makes differentially private training of transformers easy.
  ☆159Updated last year
• twistedcubic / coin-press
  [NeurIPS 2020] Simple and practical private mean and covariance estimation.
  ☆33Updated 4 years ago