AI RESEARCH
Revisiting ML Training under Fully Homomorphic Encryption: Convergence Guarantees, Differential Privacy, and Efficient Algorithms
arXiv CS.LG
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ArXi:2605.27782v1 Announce Type: new We present the first theoretical convergence analysis of under fully homomorphic encryption (FHE), combined with a differentially private (DP)