8 citations · 11 across the 4 of their papers we have counts for
Showing math.OCShow all
3 papers · 1 filter
math.OC2021
Rational activation functions in neural networks with uniform based loss functions and its application in classification
Vinesha Peiris
In this paper, we demonstrate the application of generalised rational uniform (Chebyshev) approximation in neural networks. In particular, our activation functions are one degree r…
math.OC2020★ 1 cited
The extension of linear inequality method for generalised rational Chebyshev approximation to approximation by general quasilinear functions
Vinesha Peiris, Nadezda Sukhorukova
In this paper we demonstrate that a well known linear inequality method developed for rational Chebyshev approximation is equivalent to the application of the bisection method used…
math.OC2020★ 8 cited
Rational approximation and its application to improving deep learning classifiers
V. Peiris, N. Sharon, N. Sukhorukova J. Ugon
A rational approximation by a ratio of polynomial functions is a flexible alternative to polynomial approximation. In particular, rational functions exhibit accurate estimations to…