Year: 2021
Type: preprint
Abstract: The aim of paper is to apply two types of particle swarm optimization, global best andlocal best PSO to a constrained maximum likelihood estimation problem in pseudotime anal-ysis, a sub-field in bioinformatics. The results have shown that particle swarm optimizationis extremely useful and efficient when the optimization problem is non-differentiable and non-convex so that analytical solution can not be derived and gradient-based methods can not beapplied.
Source: arXiv (Cornell University)
Authors: Cui, Elvis, Song, Dongyuan, Wong, Weng Kee
Institution: University of California, Los Angeles
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3153379136