IDEAS home Printed from https://ideas.repec.org/a/hin/jnddns/826812.html
   My bibliography  Save this article

Learning Bounds of ERM Principle for Sequences of Time-Dependent Samples

Author

Listed:
  • Mingchen Yao
  • Chao Zhang
  • Wei Wu

Abstract

Many generalization results in learning theory are established under the assumption that samples are independent and identically distributed (i.i.d.). However, numerous learning tasks in practical applications involve the time-dependent data. In this paper, we propose a theoretical framework to analyze the generalization performance of the empirical risk minimization (ERM) principle for sequences of time-dependent samples (TDS). In particular, we first present the generalization bound of ERM principle for TDS. By introducing some auxiliary quantities, we also give a further analysis of the generalization properties and the asymptotical behaviors of ERM principle for TDS.

Suggested Citation

  • Mingchen Yao & Chao Zhang & Wei Wu, 2015. "Learning Bounds of ERM Principle for Sequences of Time-Dependent Samples," Discrete Dynamics in Nature and Society, Hindawi, vol. 2015, pages 1-8, November.
    • Handle: RePEc:hin:jnddns:826812
    DOI: 10.1155/2015/826812
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/DDNS/2015/826812.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/DDNS/2015/826812.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2015/826812?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnddns:826812. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.