Convolutional optimization with convex kernel and power lift
Optimization and Control
2025-03-31 v1 Computational Engineering, Finance, and Science
Computation and Language
Abstract
We focus on establishing the foundational paradigm of a novel optimization theory based on convolution with convex kernels. Our goal is to devise a morally deterministic model of locating the global optima of an arbitrary function, which is distinguished from most commonly used statistical models. Limited preliminary numerical results are provided to test the efficiency of some specific algorithms derived from our paradigm, which we hope to stimulate further practical interest.
Cite
@article{arxiv.2503.22135,
title = {Convolutional optimization with convex kernel and power lift},
author = {Zhipeng Lu},
journal= {arXiv preprint arXiv:2503.22135},
year = {2025}
}