DocumentCode
1683019
Title
Efficient parallel implementation of Kolmogorov superpositions
Author
Neruda, Roman
Author_Institution
Inst. of Comput. Sci., Acad. of Sci. of the Czech Republic, Prague, Czech Republic
Volume
2
fYear
2002
fDate
6/24/1905 12:00:00 AM
Firstpage
1224
Lastpage
1227
Abstract
We analyze serial and parallel implementation of the learning algorithm based on Kolmogorov superposition theorem. Theoretical time complexity estimates are compared and parallel speedup is determined. Practical experiments show that the speedup in the order of 2n, where n is the input dimension, is achievable for real parallel environments (such as clusters of workstations)
Keywords
computational complexity; learning (artificial intelligence); parallel algorithms; Kolmogorov superpositions; clusters of workstations; learning algorithm; parallel environments; parallel implementation; parallel speedup; time complexity; Algorithm design and analysis; Clustering algorithms; Computer networks; Computer science; Estimation theory; Neural networks; Quantum computing; Workstations; Zinc;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location
Honolulu, HI
ISSN
1098-7576
Print_ISBN
0-7803-7278-6
Type
conf
DOI
10.1109/IJCNN.2002.1007669
Filename
1007669
Link To Document