A Parallel Algorithm for Large-Scale Nonconvex Penalized Quantile Regression
A Parallel Algorithm for Large-Scale Nonconvex Penalized Quantile Regression
Penalized quantile regression (PQR) provides a useful tool for analyzing high-dimensional data with heterogeneity. However, its computation is challenging due to the nonsmoothness and (sometimes) the nonconvexity of the objective function. An iterative coordinate descent algorithm (QICD) was recently proposed to solve PQR with nonconvex penalty. The QICD significantly improves …