wqruan

xgboost

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

deeplearning-models

A collection of various deep learning architectures, models, and tips

pytorch-sentiment-analysis

Tutorials on getting started with PyTorch and TorchText for sentiment analysis.

research-method

论文写作与资料分享

libsnark

C++ library for zkSNARKs

federated

A collection of Google research projects related to Federated Learning and Federated Analytics.

NIID-Bench

Federated Learning Benchmark - Federated Learning on Non-IID Data Silos: An Experimental Study (ICDE 2022)

EzPC

onnx2pytorch

Transform ONNX model to PyTorch representation

mc2

A Platform for Secure Analytics and Machine Learning

pFedMe

Personalized Federated Learning with Moreau Envelopes (pFedMe) using Pytorch (NeurIPS 2020)

Basset

Convolutional neural network analysis for predicting DNA sequence activity.

mpc4j

libscapi

Comprehensive Open Source Library for Secure Multiparty Computation

fresco

A FRamework for Efficient Secure COmputation

scBasset

Sequence-based Modeling of single-cell ATAC-seq using Convolutional Neural Networks.

MultipartyPSI

Practical Multi-party Private Set Intersection from Symmetric-Key Techniques[ACM CCS 2017]

piranha

Piranha: A GPU Platform for Secure Computation

Garnet

FudanMPL 2.0, a series of multi-party learning frameworks, with rich features, including secure and fast XGBoost, secure Fine-tuning for pre-trained models, and open source SecureML.

Awesome-MPL

Repository for collection of research papers on multi-party learning.

MOTION2NX

A framework for generic hybrid two-party computation and private inference with neural networks

capc-iclr

CaPC is a method that enables collaborating parties to improve their own local heterogeneous machine learning models in a setting where both confidentiality and privacy need to be preserved to prevent explicit and implicit sharing of private data.

waldo

pMPL

pMPL: A Robust Multi-Party Learning Framework with a Privileged Party. This project is connected with the publication @ ACM CCS 2022.

SIDP

Robust Differentially Private Training of Deep Neural Networks

kamino

Source code for the VLDB 2021 paper.

BERT_IMDB

National-Scale-Secure-Parallel-Computation

Secure parallel computation on national scale volumes of data

Weir-PCFG

Weir's PCFG, rewrite train in python3

PaperReproduce

密码学论文复现