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T.P. Hong, S.S. Tseng, "Learning Concepts in Parallel Based Upon the Strategy of Version Space," IEEE Transactions on Knowledge and Data Engineering, vol. 6, no. 6, pp. 857867, December, 1994.  
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@article{ 10.1109/69.334877, author = {T.P. Hong and S.S. Tseng}, title = {Learning Concepts in Parallel Based Upon the Strategy of Version Space}, journal ={IEEE Transactions on Knowledge and Data Engineering}, volume = {6}, number = {6}, issn = {10414347}, year = {1994}, pages = {857867}, doi = {http://doi.ieeecomputersociety.org/10.1109/69.334877}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
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TY  JOUR JO  IEEE Transactions on Knowledge and Data Engineering TI  Learning Concepts in Parallel Based Upon the Strategy of Version Space IS  6 SN  10414347 SP857 EP867 EPD  857867 A1  T.P. Hong, A1  S.S. Tseng, PY  1994 KW  learning (artificial intelligence); parallel algorithms; computational complexity; generalisation (artificial intelligence); configuration management; concept learning; parallel versionspace learning algorithm; divideandconquer method; time complexity; training instances; application domains; bounded processor number; generalization process; hypothesis; specialization process VL  6 JA  IEEE Transactions on Knowledge and Data Engineering ER   
Applies the technique of parallel processing to concept learning. A parallel versionspace learning algorithm based upon the principle of divideandconquer is proposed. Its time complexity is analyzed to be O(k log/sub 2/n) with n processors, where n is the number of given training instances and k is a coefficient depending on the application domains. For a bounded number of processors in real situations, a modified parallel learning algorithm is then proposed. Experimental results are then performed on a real learning problem, showing that our parallel learning algorithm works, and being quite consistent with the results of theoretical analysis. We conclude that when the number of training instances is large, it is worth learning in parallel because of its faster execution.
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