Stars
An implementation of MobileNetV3 with pyTorch
Micro search space NAS framework for efficient private inference architecture
Code of "Seesaw: Compensating for Nonlinear Reduction with Linear Computations for Private Inference" in ICML'24
"Efficient Neural Architecture Search via Parameter Sharing" implementation in PyTorch
Transform ONNX model to PyTorch representation
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.
A framework for generic hybrid two-party computation and private inference with neural networks
Convolutional neural network analysis for predicting DNA sequence activity.
Sequence-based Modeling of single-cell ATAC-seq using Convolutional Neural Networks.
A collection of various deep learning architectures, models, and tips
Repository for collection of research papers on multi-party learning.
Federated Learning Benchmark - Federated Learning on Non-IID Data Silos: An Experimental Study (ICDE 2022)
Personalized Federated Learning with Moreau Envelopes (pFedMe) using Pytorch (NeurIPS 2020)
pMPL: A Robust Multi-Party Learning Framework with a Privileged Party. This project is connected with the publication @ ACM CCS 2022.
A Platform for Secure Analytics and Machine Learning
Secure parallel computation on national scale volumes of data
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 prev…
A collection of Google research projects related to Federated Learning and Federated Analytics.
Comprehensive Open Source Library for Secure Multiparty Computation
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
Practical Multi-party Private Set Intersection from Symmetric-Key Techniques[ACM CCS 2017]