xiyuanyang45 / DynamicPFLLinks
nips23-Dynamic Personalized Federated Learning with Adaptive Differential Privacy
☆81Updated 11 months ago
Alternatives and similar repositories for DynamicPFL
Users that are interested in DynamicPFL are comparing it to the libraries listed below
Sorting:
- An open source FL implement with dataset(Femnist, Shakespeare, MNIST, Cifar-10 and Fashion-Mnist) using pytorch☆130Updated 2 years ago
- Everything you want about DP-Based Federated Learning, including Papers and Code. (Mechanism: Laplace or Gaussian, Dataset: femnist, shak…☆398Updated 10 months ago
- This repository contains the official implementation for the manuscript: Make Landscape Flatter in Differentially Private Federated Lear…☆51Updated 2 years ago
- ☆39Updated last year
- FedAvg code with privacy protection function, the application of Paillier homomorphic encryption algorithm and differential privacy, diff…☆126Updated 11 months ago
- A PyTorch implementation of "Communication-Efficient Learning of Deep Networks from Decentralized Data", AISTATS, 2017☆86Updated last year
- ☆26Updated 2 years ago
- Similarity Guided Model Aggregation for Federated Learning☆25Updated 3 years ago
- Implementing the algorithm from our paper: "A Reputation Mechanism Is All You Need: Collaborative Fairness and Adversarial Robustness in …☆35Updated last year
- FLIS: Clustered Federated Learning via Inference Similarity for Non-IID Data Distribution☆39Updated 2 years ago
- Code for Data Poisoning Attacks Against Federated Learning Systems☆198Updated 4 years ago
- Accenture Labs Federated Learning☆104Updated last year
- ☆72Updated 10 months ago
- Implementation of dp-based federated learning framework using PyTorch☆305Updated 2 years ago
- Code for NDSS 2021 Paper "Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses Against Federated Learning"☆147Updated 3 years ago
- Differential priavcy based federated learning framework by various neural networks and svm using PyTorch.☆45Updated 2 years ago
- Differentially Private Federated Learning on Heterogeneous Data