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Diminishing Stepsize Methods for Nonconvex Composite Problems Via Ghost Penalties: From the General to the Convex Regular Constrained Case

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F22%3A00344351" target="_blank" >RIV/68407700:21230/22:00344351 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1080/10556788.2020.1854253" target="_blank" >https://doi.org/10.1080/10556788.2020.1854253</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1080/10556788.2020.1854253" target="_blank" >10.1080/10556788.2020.1854253</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Diminishing Stepsize Methods for Nonconvex Composite Problems Via Ghost Penalties: From the General to the Convex Regular Constrained Case

  • Original language description

    In this paper, we first extend the diminishing stepsize method for nonconvex constrained problems presented in F. Facchinei, V. Kungurtsev, L. Lampariello and G. Scutari [Ghost penalties in nonconvex constrained optimization: Diminishing stepsizes and iteration complexity, To appear on Math. Oper. Res. 2020. Available at https://arxiv.org/abs/1709.03384.] to deal with equality constraints and a nonsmooth objective function of composite type. We then consider the particular case in which the constraints are convex and satisfy a standard constraint qualification and show that in this setting the algorithm can be considerably simplified, reducing the computational burden of each iteration.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Optimization Methods and Software

  • ISSN

    1055-6788

  • e-ISSN

    1029-4937

  • Volume of the periodical

    37

  • Issue of the periodical within the volume

    4

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    27

  • Pages from-to

    1242-1268

  • UT code for WoS article

    000596273600001

  • EID of the result in the Scopus database

    2-s2.0-85097070223