# Steklov Regularization and Trajectory Methods for Univariate Global Optimization

arXiv: https://arxiv.org/abs/1809.04530 · HTML: https://mlsanity.com/paper/1809.04530/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Sep 2018.

## Built on by (most cited first, 1 of 1)

- [Yuille-Poggio's Flow and Global Minimizer of Polynomials through Convexification by Heat Evolution](https://mlsanity.com/paper/2301.00326/) (2023)

## Abstract (arXiv)

We introduce a new regularization technique, using what we refer to as the Steklov regularization function, and apply this technique to devise an algorithm that computes a global minimizer of univariate coercive functions. First, we show that the Steklov regularization convexifies a given univariate coercive function. Then, by using the regularization parameter as the independent variable, a trajectory is constructed on the surface generated by the Steklov function. For monic quartic polynomials, we prove that this trajectory does generate a global minimizer. In the process, we derive some properties of quartic polynomials. Comparisons are made with a previous approach which uses a quadratic regularization function. We carry out numerical experiments to illustrate the working of the new method on polynomials of various degree as well as a non-polynomial function.