Noise-Aware Shrinkage for Differentially Private Zeroth-Order Fine-Tuning of Large Language Models
Differentially private zeroth-order optimization (DP-ZO) enables memory-efficient private fine-tuning of large language models using only forward evaluations. Existing aggregation-based DP-ZO methods reconstruct model updates at a fixed scale, ignoring that the strength of useful signals varies throughout training. Con...