dc.contributor.author | Petrović, Milena | |
dc.contributor.author | Ivanović, Milica | |
dc.contributor.author | Đorđević, Marijana | |
dc.date.accessioned | 2023-04-19T11:56:53Z | |
dc.date.available | 2023-04-19T11:56:53Z | |
dc.identifier.uri | https://platon.pr.ac.rs/handle/123456789/1227 | |
dc.description.abstract | We analyze a performance profile of several accelerated and hybrid accelerated methods. All comparative methods
are at least linearly convergent and have satisfied numerical characteristics regarding tested metrics: number of
iterations, CPU time and number of function evaluations. Among the chosen set of methods we numerically show
which one is the most efficient and the most effective. Therewith, we derived a conclusion about what type of method
is more preferable to use considering analyzed metrics. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Prirodno-matematički fakultet Univerziteta u Prištini u Kosovskoj Mitrovici, Srbija | en_US |
dc.title | Comparative performance analysis of some accelerated and hybrid accelerated gradient models | en_US |
dc.title.alternative | UNIVERSITY THOUGHT - Publication in Natural Sciences | en_US |
dc.type | clanak-u-casopisu | en_US |
dc.description.version | publishedVersion | en_US |
dc.identifier.doi | 10.5937/univtho9-18174 | |
dc.citation.volume | 9 | |
dc.citation.issue | 1 | |
dc.citation.spage | 57 | |
dc.citation.epage | 61 | |
dc.subject.keywords | Gradient descent methods | en_US |
dc.subject.keywords | Line search | en_US |
dc.subject.keywords | Convergence rate | en_US |
dc.type.mCategory | M53 | en_US |
dc.type.mCategory | openAccess | en_US |
dc.type.mCategory | M53 | en_US |
dc.type.mCategory | openAccess | en_US |