Bayesian stopping rule in discrete parameter space with multiple local maxima

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F19%3A00503809" target="_blank" >RIV/67985556:_____/19:00503809 - isvavai.cz</a>
Result on the web
<a href="https://www.kybernetika.cz/content/2019/1/1" target="_blank" >https://www.kybernetika.cz/content/2019/1/1</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.14736/kyb-2019-1-0001" target="_blank" >10.14736/kyb-2019-1-0001</a>

Result language
angličtina
Original language name
Bayesian stopping rule in discrete parameter space with multiple local maxima
Original language description
The paper presents the stopping rule for random search for Bayesian model-structure estimation by maximising the likelihood function. The inspected maximisation uses random restarts to cope with local maxima in discrete space. The stopping rule, suitable for any maximisation of this type, exploits the probability of finding global maximum implied by the number of local maxima already found. It stops the search when this probability crosses a given threshold. The inspected case represents an important example of the search in a huge space of hypotheses so common in artificial intelligence, machine learning and computer science.
Czech name
—
Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10103 - Statistics and probability

Project
<a href="/en/project/GA16-09848S" target="_blank" >GA16-09848S: Rationality and Deliberation</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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