5 citations · 6 across the 2 of their papers we have counts for
2 papers
cs.CR2021★ 5 cited
Privacy-Preserving Training of Tree Ensembles over Continuous Data
Samuel Adams, Chaitali Choudhary, Martine De Cock +5
Most existing Secure Multi-Party Computation (MPC) protocols for privacy-preserving training of decision trees over distributed data assume that the features are categorical. In re…
cs.CR2020★ 1 cited
High Performance Logistic Regression for Privacy-Preserving Genome Analysis
Martine De Cock, Rafael Dowsley, Anderson C. A. Nascimento +3
In this paper, we present a secure logistic regression training protocol and its implementation, with a new subprotocol to securely compute the activation function. To the best of…