spliew / shuffgauss

Related projects ⓘ

Alternatives and complementary repositories for shuffgauss

• woodyx218 / opacus_global_clipping
  ☆13Updated last year
• woodyx218 / Deep-Learning-with-GDP-Pytorch
  Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"
  ☆31Updated 3 years ago
• facebookresearch / label_dp_antipodes
  Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"
  ☆30Updated 2 years ago
• google-research / public-data-in-dpfl
  ☆22Updated last year
• facebookresearch / dp_compression
  Code repo for the paper "Privacy-aware Compression for Federated Data Analysis".
  ☆16Updated last year
• DeRafael / CAFE
  ☆21Updated 3 years ago
• hharcolezi / multi-freq-ldpy
  Multiple Frequency Estimation Under Local Differential Privacy in Python
  ☆41Updated last year
• zitengsun / hadamard_response
  Hadamard Response: Communication efficient, sample optimal, linear time locally private learning of distributions
  ☆14Updated 4 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
• dayu11 / Gradient-Embedding-Perturbation
  ☆27Updated last year
• google-deepmind / informed_adversary_mnist_reconstruction
  ☆16Updated 2 years ago
• google-research / DP-FTRL
  DP-FTRL from "Practical and Private (Deep) Learning without Sampling or Shuffling" for centralized training.
  ☆25Updated 3 months ago
• lmunoz-gonzalez / Poisoning-Attacks-with-Back-gradient-Optimization
  Example of the attack described in the paper "Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization"
  ☆21Updated 5 years ago
• bargavj / EvaluatingDPML
  This project's goal is to evaluate the privacy leakage of differentially private machine learning models.
  ☆129Updated last year
• BorjaBalle / analytic-gaussian-mechanism
  Analytic calibration for differential privacy with Gaussian perturbations
  ☆44Updated 6 years ago
• BielStela / membership_inference
  Python package to create adversarial agents for membership inference attacks againts machine learning models
  ☆47Updated 5 years ago
• ebagdasa / pytorch-privacy
  simple Differential Privacy in PyTorch
  ☆48Updated 4 years ago
• jeremy313 / Soteria
  Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"
  ☆55Updated last year
• dayu11 / Differentially-Private-Deep-Learning
  This repo implements several algorithms for learning with differential privacy.
  ☆101Updated last year
• samuel-yeom / ml-privacy-csf18
  Code for the CSF 2018 paper "Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting"
  ☆38Updated 5 years ago
• jagielski / auditing-dpsgd
  Code for Auditing DPSGD
  ☆35Updated 2 years ago
• Lory94 / dp-GAN
  Differentially Private Generative Adversarial Networks for Time Series, Continuous, and Discrete Open Data
  ☆33Updated 5 years ago
• shrezaei / MI-Attack
  ☆32Updated 2 months ago
• awslabs / fast-differential-privacy
  Fast, memory-efficient, scalable optimization of deep learning with differential privacy
  ☆95Updated last month
• ganeshdg95 / Leveraging-Adversarial-Examples-to-Quantify-Membership-Information-Leakage
  ☆19Updated last year
• pasquini-dario / SplitNN_FSHA
  Privacy attacks on Split Learning
  ☆37Updated 2 years ago
• sarus-tech / dp-xgboost
  ☆23Updated 10 months ago
• ftramer / Handcrafted-DP
  ☆78Updated 2 years ago
• woodyx218 / Deep-Learning-with-GDP-Tensorflow
  Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"
  ☆47Updated 3 years ago
• IBM / discrete-gaussian-differential-privacy
  Code for Canonne-Kamath-Steinke paper https://arxiv.org/abs/2004.00010
  ☆59Updated 4 years ago