Publication Date

8-2019

Comments

Technical Report: UTEP-CS-19-93

Abstract

Numerical experiments show that for classifying neural networks, it is beneficial to select a smaller deviation for initial weights that what is usually recommended. In this paper, we provide a theoretical explanation for these unexpected simulation results.

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