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Proceedings Paper

Particle searches with neural nets
Author(s): Georg Stimpfl-Abele
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Paper Abstract

The efficiency and robustness of neural feed-forward nets in particle searches is studied using the search for the standard Higgs Boson at LEP-200 as an example. Methods to select the most efficient variables, to define standard cuts, and to recognize significant differences between the training-data sample and a test-data sample are presented. The efficiencies of the neural nets are significantly better than those of standard methods.

Paper Details

Date Published: 6 April 1995
PDF: 11 pages
Proc. SPIE 2492, Applications and Science of Artificial Neural Networks, (6 April 1995); doi: 10.1117/12.205100
Show Author Affiliations
Georg Stimpfl-Abele, Univ. de Barcelona (Spain)

Published in SPIE Proceedings Vol. 2492:
Applications and Science of Artificial Neural Networks
Steven K. Rogers; Dennis W. Ruck, Editor(s)

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