• DocumentCode
    20220
  • Title

    New Trends of Learning in Computational Intelligence [Guest Editorial]

  • Author

    Huang, Guang-Bin ; Cambria, Erik ; Toh, Kar-Ann ; Widrow, Bernard ; Xu, Zongben

  • Author_Institution
    Nanyang Technological University, Singapore
  • Volume
    10
  • Issue
    2
  • fYear
    2015
  • fDate
    May-15
  • Firstpage
    16
  • Lastpage
    17
  • Abstract
    The articles in this special issue are dedicated to new trends of Learning in the field of computational intelligence. Over the past few decades, conventional computational intelligence techniques faced severe bottlenecks in terms of algorithmic learning. Particularly, in the areas of big data computation, brain science, cognition and reasoning, it is almost inevitable that intensive human intervention and time consuming trial and error efforts are to be employed before any meaningful observations can be obtained. Recent development of emerging computational intelligence techniques such as extreme learning machines (ELM) and fast solutions shed some light upon how to effectively deal with these computational bottlenecks.
  • Keywords
    Biological system modeling; Cognition; Computational intelligence; Computer science education; Human factors; Learning systems; Market research; Neural networks; Real-time systems; Special issues and sections;
  • fLanguage
    English
  • Journal_Title
    Computational Intelligence Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1556-603X
  • Type

    jour

  • DOI
    10.1109/MCI.2015.2405277
  • Filename
    7083692