DistributedML / TorMLLinks
A collaborative machine learning framework that operates through Tor.
☆13Updated 5 years ago
Alternatives and similar repositories for TorML
Users that are interested in TorML are comparing it to the libraries listed below
Sorting:
- A ledger for private and secure peer to peer machine learning☆109Updated 2 years ago
- Statistical Counterexample Detector for Differential Privacy☆28Updated last year
- ☆38Updated 3 years ago
- ☆19Updated 4 years ago
- A Simulator for Privacy Preserving Federated Learning☆96Updated 4 years ago
- This work combines differential privacy and multi-party computation protocol to achieve distributed machine learning.☆26Updated 5 years ago
- Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data (https://arxiv.org/abs/16…☆45Updated 3 years ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆135Updated 2 years ago
- autodp: A flexible and easy-to-use package for differential privacy☆275Updated last year
- Code for "Differential Privacy Has Disparate Impact on Model Accuracy" NeurIPS'19☆33Updated 4 years ago
- Byzantine-resilient distributed SGD with TensorFlow.☆40Updated 4 years ago
- Integration of SplitNN for vertically partitioned data with OpenMined's PySyft☆27Updated 5 years ago
- Code for Canonne-Kamath-Steinke paper https://arxiv.org/abs/2004.00010☆61Updated 5 years ago
- Federated gradient boosted decision tree learning☆68Updated 2 years ago
- ☆34Updated 2 years ago
- Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)☆54Updated 6 years ago
- Privacy attacks on Split Learning☆42Updated 3 years ago
- ☆13Updated 2 years ago
- ☆80Updated 3 years ago
- Secure collaborative training and inference for XGBoost.☆105Updated 3 years ago
- A library for running membership inference attacks against ML models☆150Updated 2 years ago
- Privacy Preserving Vertical Federated Learning☆219Updated 2 years ago
- A machine-learning-based tool for discovering differential privacy violations in black-box algorithms.☆24Updated 3 years ago
- Implementation of membership inference and model inversion attacks, extracting training data information from an ML model. Benchmarking …☆103Updated 6 years ago
- Analytic calibration for differential privacy with Gaussian perturbations☆50Updated 7 years ago
- Privacy preserving vertical federated learning for tree-based models☆29Updated 3 years ago
- A curated list of resources for privacy-preserving machine learning☆148Updated 4 years ago
- Federated Learning on XGBoost☆46Updated 6 years ago
- A sybil-resilient distributed learning protocol.☆104Updated last month
- Privacy-preserving Deep Learning based on homomorphic encryption (HE)☆34Updated 3 years ago