google-research / DP-FTRLLinks
DP-FTRL from "Practical and Private (Deep) Learning without Sampling or Shuffling" for centralized training.
☆35Updated 6 months ago
Alternatives and similar repositories for DP-FTRL
Users that are interested in DP-FTRL are comparing it to the libraries listed below
Sorting:
- A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.☆75Updated last year
- Fast, memory-efficient, scalable optimization of deep learning with differential privacy☆135Updated last week
- Privacy Preserving Vertical Federated Learning☆221Updated 2 years ago
- ☆15Updated 2 years ago
- Federated Learning Simulator (FLSim) is a flexible, standalone core library that simulates FL settings with a minimal, easy-to-use API. F…☆265Updated last year
- ☆80Updated 3 years ago
- Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"☆32Updated 3 years ago
- Privacy attacks on Split Learning☆42Updated 4 years ago
- Algorithms for Privacy-Preserving Machine Learning in JAX☆135Updated 2 weeks ago
- A Simulator for Privacy Preserving Federated Learning☆96Updated 4 years ago
- autodp: A flexible and easy-to-use package for differential privacy☆278Updated 2 years ago
- Code repo for the paper "Privacy-aware Compression for Federated Data Analysis".☆19Updated 2 years ago
- PyTorch for benchmarking communication-efficient distributed SGD optimization algorithms☆78Updated 4 years ago
- Simplicial-FL to manage client device heterogeneity in Federated Learning☆22Updated 2 years ago
- Byzantine-resilient distributed SGD with TensorFlow.☆40Updated 4 years ago
- Federated Learning Framework Benchmark (UniFed)☆49Updated 2 years ago
- This repo implements several algorithms for learning with differential privacy.☆111Updated 3 years ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆135Updated 3 years ago
- simple Differential Privacy in PyTorch☆49Updated 5 years ago
- Breaching privacy in federated learning scenarios for vision and text☆311Updated 4 months ago
- [CCS 2021] "DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation" by Boxin Wang*, Fan Wu*, Yunhui Long…☆36Updated 3 years ago
- Robust aggregation for federated learning with the RFA algorithm.☆52Updated 3 years ago
- [NeurIPS 2022] JAX/Haiku implementation of "On Privacy and Personalization in Cross-Silo Federated Learning"☆27Updated 2 years ago
- ☆27Updated 3 years ago
- Code for Auditing DPSGD☆37Updated 3 years ago
- A codebase that makes differentially private training of transformers easy.☆181Updated 3 years ago
- Amortized version of the differentially private SGD algorithm published in "Deep Learning with Differential Privacy" by Abadi et al. Enfo…☆43Updated last year
- ☆47Updated last year
- A library for running membership inference attacks against ML models☆152Updated 3 years ago
- ☆55Updated 2 years ago