Search Results - Quantile regression and single-loop algorithm

A Parallel Algorithm for Large-Scale Nonconvex Penalized Quantile Regression by Yu, Liqun, Lin, Nan, Wang, Lan

“… This results in a new single-loop algorithm, which we refer to as the QPADM algorithm. The QPADM demonstrates favorable performance in both computational speed and statistical accuracy, particularly when the sample size n and/or the number of features p are large. Supplementary material for this article is available online…”
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Smoothing ADMM for Sparse-Penalized Quantile Regression With Non-Convex Penalties by Mirzaeifard, Reza, Venkategowda, Naveen K. D., Gogineni, Vinay Chakravarthi, Werner, Stefan

“…This paper investigates quantile regression in the presence of non-convex and non-smooth sparse penalties, such as the minimax concave penalty (MCP…”
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Smoothing ADMM for Sparse-Penalized Quantile Regression with Non-Convex Penalties by Mirzaeifard, Reza, Venkategowda, Naveen K D, Gogineni, Vinay Chakravarthi, Werner, Stefan

“…) and introduce a novel single-loop smoothing ADMM algorithm with an increasing…”
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Distributed Quantile Regression Analysis and a Group Variable Selection Method by Yu, Liqun

“…This dissertation develops novel methodologies for distributed quantile regression analysis for big data by utilizing a distributed optimization algorithm called the alternating direction method of multipliers (ADMM…”
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