• DocumentCode
    3556849
  • Title

    Models of parallel learning systems

  • Author

    Hong, Tzung-Pei ; Tseng, Shian-Shyong

  • Author_Institution
    Inst. of Comput. Sci. & Inf. Eng., Nat. Chiao-Tung Univ., Hsin-Chu, Taiwan
  • fYear
    1991
  • fDate
    20-24 May 1991
  • Firstpage
    125
  • Lastpage
    132
  • Abstract
    The technique of parallel processing is applied to concept learning. The learning strategies can be divided into two classes: top-down learning and bottom-up learning. Based on the partition of learning tasks on the multiple processors and the principle of divide-and-conquer, respectively, two corresponding parallel learning models are proposed. It is shown that these two models can be easily embedded into two practical and commonly used architectures: the MIMD shared memory architecture and the SIMD shared memory architecture. The ID3 and the version space learning strategies are parallelized to show how a parallel top-down learning or a parallel bottom-up learning strategy can work well
  • Keywords
    learning systems; parallel programming; ID3; MIMD shared memory architecture; SIMD shared memory architecture; bottom-up learning; concept learning; divide-and-conquer; parallel learning systems; parallel processing; top-down learning; version space learning; Artificial intelligence; Computer science; Concurrent computing; Information science; Knowledge based systems; Learning systems; Machine learning; Memory architecture; Parallel machines; Parallel processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Distributed Computing Systems, 1991., 11th International Conference on
  • Conference_Location
    Arlington, TX
  • Print_ISBN
    0-8186-2144-3
  • Type

    conf

  • DOI
    10.1109/ICDCS.1991.148653
  • Filename
    148653