2 papers
cs.CR2025
EVA-S2PLoR: Decentralized Secure 2-party Logistic Regression with A Subtly Hadamard Product Protocol (Full Version)
Tianle Tao, Shizhao Peng, Tianyu Mei +2
The implementation of accurate nonlinear operators (e.g., sigmoid function) on heterogeneous datasets is a key challenge in privacy-preserving machine learning (PPML). Most existin…
cs.CR2025
EVA-S2PMLP: Secure and Scalable Two-Party MLP via Spatial Transformation
Shizhao Peng, Shoumo Li, Tianle Tao
Privacy-preserving neural network training in vertically partitioned scenarios is vital for secure collaborative modeling across institutions. This paper presents \textbf{EVA-S2PML…