lee-man / federated-learningLinks
Related material on Federated Learning
☆26Updated 5 years ago
Alternatives and similar repositories for federated-learning
Users that are interested in federated-learning are comparing it to the libraries listed below
Sorting:
- Salvaging Federated Learning by Local Adaptation☆56Updated 11 months ago
- code for TPDS paper "Towards Fair and Privacy-Preserving Federated Deep Models"☆31Updated 3 years ago
- Attentive Federated Learning for Private NLM☆61Updated 11 months ago
- Code for paper "Interpret Federated Learning with Shapley Values"☆39Updated 6 years ago
- A curated list of resources dedicated to federated learning.☆104Updated 3 years ago
- ☆168Updated 7 years ago
- tf implementation of federated learning☆42Updated 6 years ago
- Code for "Differential Privacy Has Disparate Impact on Model Accuracy" NeurIPS'19☆34Updated 4 years ago
- Fedlearn支持前沿算法研发的Python工具库 | Fedlearn algorithm toolkit for researchers☆93Updated 3 years ago
- Bayesian Nonparametric Federated Learning of Neural Networks☆144Updated 6 years ago
- A Simulator for Privacy Preserving Federated Learning☆94Updated 4 years ago
- Differentially Private Optimization for PyTorch 👁🙅♀️☆186Updated 5 years ago
- Code for "Analyzing Federated Learning through an Adversarial Lens" https://arxiv.org/abs/1811.12470☆151Updated 2 years ago
- Differential Privacy Preservation in Deep Learning under Model Attacks☆135Updated 4 years ago
- Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data (https://arxiv.org/abs/16…☆44Updated 3 years ago
- Code for NIPS'2017 paper☆50Updated 5 years ago
- DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation☆16Updated 5 years ago
- Source code for paper "How to Backdoor Federated Learning" (https://arxiv.org/abs/1807.00459)☆299Updated 11 months ago
- simple Differential Privacy in PyTorch☆48Updated 5 years ago
- Federated Learning on XGBoost☆46Updated 5 years ago
- Curated notebooks on how to train neural networks using differential privacy and federated learning.☆68Updated 4 years ago
- ☆22Updated 6 years ago
- ☆72Updated last year
- vector quantization for stochastic gradient descent.☆35Updated 5 years ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆135Updated 2 years ago
- Federated Multi-Task Learning☆131Updated 6 years ago
- Credit Approval Classification Deep Learning Model using Differential Drivacy, Secure Multi-Party Computation, and Federated Learning☆23Updated 2 years ago
- Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)☆53Updated 6 years ago
- ☆26Updated 6 years ago
- Official implementation of "FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective"…☆84Updated 5 years ago