Yicheng Liu

Transfer Learning for High‐Dimensional Huber Approximate Quantile Regression via Elastic Net

This paper proposes a novel transfer learning framework for high‐dimensional quantile regression, addressing the non‐differentiability of quantile loss via a Huber approximation and leveraging elastic net regularization to handle sparse inference. By replacing the piecewise linear quantile check function with a smoot...