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Parallel factorised algorithms for mixture estimation
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SYSNO ASEP 0410577 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title Parallel factorised algorithms for mixture estimation Author(s) Tichý, Milan (UTIA-B)
Kovář, Bohumil (UTIA-B) RIDIssue data Wien: Springer, 2001 ISBN 3-211-83651-9 Source Title Artificial Neural Nets and Genetic Algorithms. Proceedings / Kůrková V. ; Neruda R. ; Kárný M. ; Steele M. C. Pages s. 410-413 Number of pages 4 s. Action International Conference on Artificial Neural Networks and Genetic Algorithms /5./ Event date 22.04.2001-25.04.2001 VEvent location Praha Country CZ - Czech Republic Event type WRD Language eng - English Country AT - Austria Keywords data mining Subject RIV JC - Computer Hardware ; Software R&D Projects GA102/99/1564 GA ČR - Czech Science Foundation (CSF) CEZ 1075907 Annotation This paper describes software ospects of an advisory system based on finite-mixture estimation. Factorised algorithms have been designed. Parallelism is used as a principal approach to acceleration of learning and processing phases. The Parallel Virtual Machine (PVM) is used for parallel implementation. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.
Number of the records: 1