A Quantum-Behaved Particle Swarm Optimization Algorithm on Riemannian Manifolds

The Riemannian manifold optimization algorithms have been widely used in machine learning, computer vision, data mining, and other technical fields. Most of these algorithms are based on the geodesic or the retracement operator and use the classical methods (i.e., the steepest descent method, the co...

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Vydáno v:	Mathematics (Basel) Ročník 10; číslo 22; s. 4168
Hlavní autoři:	Halimu, Yeerjiang, Zhou, Chao, You, Qi, Sun, Jun
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Basel MDPI AG 01.11.2022
Témata:	Adaptation Algorithms Approximation Computer vision Conjugate gradient method Data mining Euclidean geometry Euclidean space Lie groups Machine learning Manifolds (Mathematics) Mathematical analysis Mathematical functions Mathematical optimization matrix manifold optimization Methods Newton methods Operators (mathematics) Optimization algorithms Particle swarm optimization Physics Quantum theory quantum-behaved particle swarm optimization retracement operator Riemann manifold Riemannian manifold Search process Semidefinite programming Steepest descent method Swarm intelligence Vectors (mathematics) China
ISSN:	2227-7390, 2227-7390
On-line přístup:	Získat plný text
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