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
Link To Document