TITLE:
Least Squares Method from the View Point of Deep Learning II: Generalization
AUTHORS:
Kazuyuki Fujii
KEYWORDS:
Least Squares Method, Statistics, Deep Learning, Learning Rate, Gerschgorin’s Theorem
JOURNAL NAME:
Advances in Pure Mathematics,
Vol.8 No.9,
September
25,
2018
ABSTRACT: The least squares method is one of the most fundamental
methods in Statistics to estimate correlations among various data. On the other
hand, Deep Learning is the heart of Artificial Intelligence and it is a
learning method based on the least squares method, in which a parameter called
learning rate plays an important role. It is in general very hard to determine
its value. In this paper we generalize the preceding paper [K. Fujii: Least
squares method from the view point of Deep Learning: Advances in Pure
Mathematics, 8, 485-493, 2018] and give an admissible value of the
learning rate, which is easily obtained.