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A Nondeterministic Minimization Algorithm

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dc.creator Caprile, Bruno
dc.creator Girosi, Federico
dc.date 2004-10-04T15:31:26Z
dc.date 2004-10-04T15:31:26Z
dc.date 1990-09-01
dc.date.accessioned 2013-10-09T02:45:58Z
dc.date.available 2013-10-09T02:45:58Z
dc.date.issued 2013-10-09
dc.identifier AIM-1254
dc.identifier http://hdl.handle.net/1721.1/6560
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description The problem of minimizing a multivariate function is recurrent in many disciplines as Physics, Mathematics, Engeneering and, of course, Computer Science. In this paper we describe a simple nondeterministic algorithm which is based on the idea of adaptive noise, and that proved to be particularly effective in the minimization of a class of multivariate, continuous valued, smooth functions, associated with some recent extension of regularization theory by Poggio and Girosi (1990). Results obtained by using this method and a more traditional gradient descent technique are also compared.
dc.format 1240414 bytes
dc.format 492517 bytes
dc.format application/postscript
dc.format application/pdf
dc.language en_US
dc.relation AIM-1254
dc.title A Nondeterministic Minimization Algorithm


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