Nir Drucker

Efficient Pruning for Machine Learning Under Homomorphic Encryption

2022 · arXiv (Cornell University)

Privacy-preserving machine learning (PPML) solutions are gaining widespread popularity. Among these, many rely on homomorphic encryption (HE) that offers confidentiality of the model and the data, but at the cost of large latency and memory …