Models of parallel learning systems
作者： T.-P. Hong , S.-S. Tseng
DOI: 10.1109/ICDCS.1991.148653
关键词:
摘要: The technique of parallel processing is applied to concept learning. learning strategies can be divided into two classes: top-down and bottom-up Based on the partition tasks multiple processors principle divide-and-conquer, respectively, corresponding models are proposed. It shown that these easily embedded practical commonly used architectures: MIMD shared memory architecture SIMD architecture. ID3 version space parallelized show how a or strategy work well. >
sci-hub.se 参考文章(15)
Stephen I. Gallant, Automatic Generation of Expert Systems from Examples. CAIA. pp. 313- 319 ,(1985)
Anoop Gupta, Implementing OPS5 production systems on DADO ,(1984)
Faye A. Briggs, Kai Hwang, Computer Architecture and Parallel Processing ,(1984)
Sartaj Sahni, Ellis Horowitz, Fundamentals of Computer Algorithms ,(1983)
Salvatore J. Stolfo, Daniel P Miranker, DADO: A Parallel Processor for Expert Systems Department of Computer Science, Columbia University. pp. 74- 82 ,(1984) , 10.7916/D8F196VH
Tom M Mitchell, None, Generalization as search Artificial Intelligence. ,vol. 18, pp. 203- 226 ,(1982) , 10.1016/0004-3702(82)90040-6
Michael J. Quinn, Designing Efficient Algorithms for Parallel Computers ,(1987)
Michael J Shaw, Applying inductive learning to enhance knowledge-based expert systems decision support systems. ,vol. 3, pp. 319- 332 ,(1987) , 10.1016/0167-9236(87)90103-5
Virendra K. Janakiram, Edward F. Gehringer, Dharma P. Agrawal, Ravi Mehrotra, A randomized parallel branch-and-bound algorithm International Journal of Parallel Programming. ,vol. 17, pp. 277- 301 ,(1989) , 10.1007/BF02427853
Thomas G. Dietterich, Ryszard S. Michalski, A Comparative Review of Selected Methods for Learning from Examples Machine Learning. pp. 41- 81 ,(1983) , 10.1007/978-3-662-12405-5_3