Optimizing High-Dimensional Differentially Private Linear Models: A Comprehensive Review and Empirical Evaluation

This paper provides a comprehensive review of optimization techniques for high-dimensional differentially private linear models, including linear and logistic regression. The authors implement and empirically evaluate all the reviewed methods, providing insights on their strengths, weaknesses, and performance across various datasets.