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Optimization Methods In Training Neural Networks

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dc.contributor.authorSathasivam, Saratha
dc.date.accessioned2025-03-02T06:42:03Z
dc.date.available2025-03-02T06:42:03Z
dc.date.issued2003-07
dc.description.abstractIn steepest descent methods, we construct a functional which when extremized will deliver a solution. The function will have convexity properties, so that the vector that extremizes the function is the solution of the algebraic problem in question. This means the search for the vector for which the gradient of the function is zero can be done in an iterative fashion. A special steepest descent method which is appropriate for the solution of the linear algebraic problem is the 'Conjugate Gradient Method'.
dc.identifier.urihttps://erepo.usm.my/handle/123456789/21211
dc.language.isoen
dc.subjectMathematical optimization
dc.titleOptimization Methods In Training Neural Networks
dc.typeResource Types::text::thesis::master thesis
dspace.entity.typePublication
oairecerif.author.affiliationUniversiti Sains Malaysia
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