Important Markov-Chain Properties of (1,lambda)-ES Linear Optimization Models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F14%3A00432405" target="_blank" >RIV/67985807:_____/14:00432405 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Important Markov-Chain Properties of (1,lambda)-ES Linear Optimization Models
Original language description
Several recent publications investigated Markov-chain modelling of linear optimization by a (1,lambda)-ES, considering both unconstrained and linearly constrained optimization, and both constant and varying step size. All of them assume normality of theinvolved random steps. This is a very strong and specific assumption. The objective of our contribution is to show that in the constant step size case, valuable properties of the Markov chain can be obtained even for steps with substantially more generaldistributions. Several results that have been previously proved using the normality assumption are proved here in a more general way without that assumption. Finally, the decomposition of a multidimensional distribution into its marginals and the copulacombining them is applied to the new distributional assumptions, particular attention being paid to distributions with Archimedean copulas.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GA13-17187S" target="_blank" >GA13-17187S: Constructing Advanced Comprehensible Classifiers</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
ITAT 2014. Information Technologies - Applications and Theory. Part II
ISBN
978-80-87136-19-5
ISSN
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e-ISSN
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Number of pages
9
Pages from-to
44-52
Publisher name
Institute of Computer Science AS CR
Place of publication
Prague
Event location
Demänovská dolina
Event date
Sep 25, 2014
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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