Výsledky vyhledávání - Quantile regression and single-loop algorithm

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  1. 1

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

    ISSN: 1061-8600, 1537-2715
    Vydáno: Alexandria Taylor & Francis 02.10.2017
    “… 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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    Journal Article
  2. 2

    Smoothing ADMM for Sparse-Penalized Quantile Regression With Non-Convex Penalties Autor Mirzaeifard, Reza, Venkategowda, Naveen K. D., Gogineni, Vinay Chakravarthi, Werner, Stefan

    ISSN: 2644-1322, 2644-1322
    Vydáno: New York IEEE 2024
    “…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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    Journal Article
  3. 3

    Smoothing ADMM for Sparse-Penalized Quantile Regression with Non-Convex Penalties Autor Mirzaeifard, Reza, Venkategowda, Naveen K D, Gogineni, Vinay Chakravarthi, Werner, Stefan

    ISSN: 2331-8422
    Vydáno: Ithaca Cornell University Library, arXiv.org 04.09.2023
    Vydáno v arXiv.org (04.09.2023)
    “…) and introduce a novel single-loop smoothing ADMM algorithm with an increasing…”
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    Paper
  4. 4

    Distributed Quantile Regression Analysis and a Group Variable Selection Method Autor Yu, Liqun

    ISBN: 9780355867046, 0355867044
    Vydáno: ProQuest Dissertations & Theses 01.01.2018
    “…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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    Dissertation