A Note On Nonlinear Regression Under L2 Loss
Machine Learning
2023-04-03 v1 Numerical Analysis
Numerical Analysis
Optimization and Control
Machine Learning
Abstract
We investigate the nonlinear regression problem under L2 loss (square loss) functions. Traditional nonlinear regression models often result in non-convex optimization problems with respect to the parameter set. We show that a convex nonlinear regression model exists for the traditional least squares problem, which can be a promising towards designing more complex systems with easier to train models.
Keywords
Cite
@article{arxiv.2303.17745,
title = {A Note On Nonlinear Regression Under L2 Loss},
author = {Kaan Gokcesu and Hakan Gokcesu},
journal= {arXiv preprint arXiv:2303.17745},
year = {2023}
}