agenda

PLANS in CALENDER

anonymous_github

Anonymous Github is a proxy server to support anonymous browsing of Github repositories for open-science code and data.

ansj_seg

ansj分词.ict的真正java实现.分词效果速度都超过开源版的ict. 中文分词,人名识别,词性标注,用户自定义词典

apriori

Apriori algorithm implement

awesome-vpn

A curated list of awesome free VPNs and proxies.免费的代理,科学上网,翻墙，梯子大集合

benchmark

A microbenchmark support library

better-homomorphic-sine-evaluation

bitpolymul

chimera-idash2018

Team CEA-EPFL-Inpher: code for the iDash 2018 competition

clementine

:tangerine: Clementine Music Player

competitive-programming

my foray into the world of competitive programming

concrete

Concrete Operates oN Ciphertexts Rapidly by Extending TfhE

core

MIRACL Core

cryptodl

Privacy-preserving Deep Learning based on homomorphic encryption (HE)

cryptonets

CryptoNets is a demonstration of the use of Neural-Networks over data encrypted with Homomorphic Encryption. Homomorphic Encryptions allow performing operations such as addition and multiplication over data while it is encrypted. Therefore, it allows keeping data private while outsourcing computation (see here and here for more about Homomorphic Encryptions and its applications). This project demonstrates the use of Homomorphic Encryption for outsourcing neural-network predictions. The scenario in mind is a provider that would like to provide Prediction as a Service (PaaS) but the data for which predictions are needed may be private. This may be the case in fields such as health or finance. By using CryptoNets, the user of the service can encrypt their data using Homomorphic Encryption and send only the encrypted message to the service provider. Since Homomorphic Encryptions allow the provider to operate on the data while it is encrypted, the provider can make predictions using a pre-trained Neural-Network while the data remains encrypted throughout the process and finaly send the prediction to the user who can decrypt the results. During the process the service provider does not learn anything about the data that was used, the prediction that was made or any intermediate result since everything is encrypted throughout the process. This project uses the Simple Encrypted Arithmetic Library SEAL version 3.2.1 implementation of Homomorphic Encryption developed in Microsoft Research.

cs-180

UCLA CS 180

cs230-code-examples

Code examples in pyTorch and Tensorflow for CS230

cs231n.github.io

Public facing notes page

cuda_practice

cude-fhe

Phantom: A GPU Homomorphic Encryption Library

cufhe

CUDA-accelerated Fully Homomorphic Encryption Library

cuhe

CUDA Homomorphic Encryption Library

cv

Personal CV

cws_evaluation

Java开源项目cws_evaluation：中文分词器分词效果评估对比

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

exroc.biginteger

Provides a BigInteger class that can be used like a basic data type https://github.com/ExRoc/BigInteger/

fhe.rs

Fully Homomorphic Encryption library in Rust

fhew

fly_us

美国大学备考资料 How to apply US colleges

fourier_neural_operator

Use Fourier transform to learn operators in differential equations.