4 papers
LFFR: Logistic Function For (multi-output) Regression
John Chiang
In this manuscript, we extend our previous work on privacy-preserving regression to address multi-output regression problems using data encrypted under a fully homomorphic encrypti…
LFFR: Logistic Function For (single-output) Regression
John Chiang
Privacy-preserving regression in machine learning is a crucial area of research, aimed at enabling the use of powerful machine learning techniques while protecting individuals' pri…
Privacy-Preserving Logistic Regression Training on Large Datasets
John Chiang
Privacy-preserving machine learning is one class of cryptographic methods that aim to analyze private and sensitive data while keeping privacy, such as homomorphic logistic regress…
A Simple Solution for Homomorphic Evaluation on Large Intervals
John Chiang
Homomorphic encryption (HE) is a promising technique used for privacy-preserving computation. Since HE schemes only support primitive polynomial operations, homomorphic evaluation…