Privacy-preserving machine learning

The goal of privacy-preserving machine learning is to train and evaluate machine learning models on input data that has to remain private. Several cryptographic techniques exist such as fully homomorphic encryption and multi-party computation. The goal of the PhD thesis is to design optimized subroutines that are frequently employed in machine learning.