10 citations · 18 across the 3 of their papers we have counts for
4 papers
Ditto: Quantization-aware Secure Inference of Transformers upon MPC
Haoqi Wu, Wenjing Fang, Yancheng Zheng +4
Due to the rising privacy concerns on sensitive client data and trained models like Transformers, secure multi-party computation (MPC) techniques are employed to enable secure infe…
PUMA: Secure Inference of LLaMA-7B in Five Minutes
Ye Dong, Wen-jie Lu, Yancheng Zheng +7
With ChatGPT as a representative, tons of companies have began to provide services based on large Transformers models. However, using such a service inevitably leak users' prompts…
When Homomorphic Encryption Marries Secret Sharing: Secure Large-Scale Sparse Logistic Regression and Applications in Risk Control
Chaochao Chen, Jun Zhou, Li Wang +7
Logistic Regression (LR) is the most widely used machine learning model in industry for its efficiency, robustness, and interpretability. Due to the problem of data isolation and t…
Large-Scale Secure XGB for Vertical Federated Learning
Wenjing Fang, Derun Zhao, Jin Tan +6
Privacy-preserving machine learning has drawn increasingly attention recently, especially with kinds of privacy regulations come into force. Under such situation, Federated Learnin…