Approaching (Almost) Any Machine Learning Problem

An experimental platform for federated learning.

An easy-to-use federated learning platform

📷 EasyPhoto | Your Smart AI Photo Generator.

Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond

An implementation of pneumonia medical X-ray image classification problem using Federated Learning in PySyft.

电力人工智能数据竞赛——安全帽未佩戴行为目标检测赛道基准模型

使用pysyft 0.5.0基于breast_cancer数据集进行横向联邦学习逻辑递归的实现

Federated learning with homomorphic encryption enables multiple parties to securely co-train artificial intelligence models in pathology and radiology, reaching state-of-the-art performance with pr…

Handy PyTorch implementation of Federated Learning (for your painless research)

ChatGPT 中文调教指南。各种场景使用指南。学习怎么让它听你的话。

Privacy-preserving detection of COVID-19 in X-ray images using differential privacy and deep learning (CNN)

基于phe库的安全多方计算协议实现

This project studied homomorphic encryption and attempted to apply it in training machine learning models. We trained some models on plain data and evaluated them on encrypted data using encrypted …

Implementation of Paillier's Homomorphic Encryption to the Linear Machine Learning Model.

Homoporhic encryption provide you a safe encryption method that allows second party to process your encrypted data. No decryption is required so your data is safe

Project to implement Privacy Preserving Machine Learning using partial Homomorphic encryption

Implementing Homomorphic-Encryption for Privacy Preserving Machine Learning

Medical data is often highly sensitive in terms of data privacy and security concerns. Federated learning, one type of machine learn- ing techniques, has been started to use for the improvement of …

Privacy-Preserving Convolutional Neural Networks using Homomorphic Encryption

Privacy-Preserving Deep Learning via Additively Homomorphic Encryption

这是一个基于Paillier同态加密系统的隐私保护SVM模型训练算法。

一种基于全同态加密技术的医疗隐私保密系统，是一个较为成熟的项目，公开源代码实现，小组成员如下：王子旭、许嘉晨、夏萌、王宏任

基于同态加密的联邦学习安全聚合系统

基于全同态加密的安全人脸识别系统/Secure Face Recognition System based on Fully Homomorphic Encryption

Code for the CCS'22 paper "Federated Boosted Decision Trees with Differential Privacy"

Differentially Private Federated Learning on Heterogeneous Data

Differentially Private Synthetic Data Generation [DP-SDG] - Experimental Setups & Knowledge Base - WORK IN PROGRESS

Synthetic data generators for structured and unstructured text, featuring differentially private learning.