nogrady / PPML
Privacy Preserving Machine Learning (Manning Early Access Program)
☆32Updated 2 years ago
Alternatives and similar repositories for PPML:
Users that are interested in PPML are comparing it to the libraries listed below
- SAP Security Research sample code to reproduce the research done in our paper "Comparing local and central differential privacy using mem…☆16Updated 8 months ago
- Differentially Private Generative Adversarial Networks for Time Series, Continuous, and Discrete Open Data☆33Updated 6 years ago
- TensorFlow World 2019 Tutorial: Privacy-Preserving Machine Learning with TF Encrypted & PySyft☆46Updated last year
- Credit Approval Classification Deep Learning Model using Differential Drivacy, Secure Multi-Party Computation, and Federated Learning☆24Updated 2 years ago
- Course Material for the Tutorial on Privacy Enhancing Technologies and PPML☆12Updated 3 years ago
- ☆43Updated 3 years ago
- This work combines differential privacy and multi-party computation protocol to achieve distributed machine learning.☆26Updated 4 years ago
- Curated notebooks on how to train neural networks using differential privacy and federated learning.☆66Updated 4 years ago
- A Simulator for Privacy Preserving Federated Learning☆92Updated 4 years ago
- ☆10Updated last year
- DP-FTRL from "Practical and Private (Deep) Learning without Sampling or Shuffling" for centralized training.☆26Updated 5 months ago
- ☆44Updated 2 years ago
- Privacy-preserving XGBoost Inference☆48Updated last year
- Code for "Differential Privacy Has Disparate Impact on Model Accuracy" NeurIPS'19☆35Updated 3 years ago
- Privacy-preserving federated learning is distributed machine learning where multiple collaborators train a model through protected gradi…☆27Updated 3 years ago
- ☆32Updated last year
- ☆23Updated last year
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆130Updated 2 years ago
- Related material on Federated Learning☆26Updated 4 years ago
- Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data (https://arxiv.org/abs/16…☆42Updated 3 years ago
- Privacy Preserving Convolutional Neural Network using Homomorphic Encryption for secure inference☆48Updated 3 years ago
- Naive implementation of basic Differential-Privacy framework and algorithms☆47Updated 2 years ago
- Federated k-means clustering algorithm implementation and proof of concept.☆27Updated 3 years ago
- federated-learning☆79Updated 2 years ago
- Dopamine: Differentially Private Federated Learning on Medical Data (AAAI - PPAI)☆72Updated 3 years ago
- An Efficient Learning Framework For Federated XGBoostUsing Secret Sharing And Distributed Optimization☆30Updated 3 years ago
- UCLANesl - NIST Differential Privacy Challenge (Match 3)☆23Updated 5 years ago
- Differential private machine learning☆184Updated 2 years ago
- Federated Learning on XGBoost☆46Updated 5 years ago