2 papers
cs.AR2025
Understanding the Error Sensitivity of Privacy-Aware Computing
MatÃas Mazzanti, Esteban Mocskos, Augusto Vega +1
Homomorphic Encryption (HE) enables secure computation on encrypted data without decryption, allowing a great opportunity for privacy-preserving computation. In particular, domains…
cs.CR2024
Efficient Pruning for Machine Learning Under Homomorphic Encryption
Ehud Aharoni, Moran Baruch, Pradip Bose +8
Privacy-preserving machine learning (PPML) solutions are gaining widespread popularity. Among these, many rely on homomorphic encryption (HE) that offers confidentiality of the mod…