Differentially Private Optimization for Smooth Nonconvex ERM

Published: 01 Jan 2023, Last Modified: 01 Oct 2024CoRR 2023EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: We develop simple differentially private optimization algorithms that move along directions of (expected) descent to find an approximate second-order solution for nonconvex ERM. We use line search, mini-batching, and a two-phase strategy to improve the speed and practicality of the algorithm. Numerical experiments demonstrate the effectiveness of these approaches.
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