Suchergebnisse - Quantile regression and single-loop algorithm

A Parallel Algorithm for Large-Scale Nonconvex Penalized Quantile Regression von 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 von 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 von 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 von 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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