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pro vyhledávání: '"Mavrogonatou, Lida"'
Designing experiments often requires balancing between learning about the true treatment effects and earning from allocating more samples to the superior treatment. While optimal algorithms for the Multi-Armed Bandit Problem (MABP) provide allocation
Externí odkaz:
http://arxiv.org/abs/2301.01107
Publikováno v:
In Computational Statistics and Data Analysis December 2022 176
Designing experiments often requires balancing between learning about the true treatment effects and earning from allocating more samples to the superior treatment. While optimal algorithms for the Multi-Armed Bandit Problem (MABP) provide allocation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::838e2035098af0256321111a2826d7be
Autor:
Mavrogonatou, Lida
Modern science has been progressively moving towards the study of increasingly complex structures, investigating not only their individual components but also their interactions, dependencies and co-existence as a whole. This thesis is concerned with
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3420775cf552e16b1166ae0e64f926a7
Online detection of abrupt changes in the parameters of a generative model for a time series is useful when modelling data in areas of application such as finance, robotics, and biometrics. We present an algorithm based on Sequential Importance Sampl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=core_ac_uk__::ceca4331067b30c13b0f715af59163bc
https://eprints.gla.ac.uk/135827/1/135827.pdf
https://eprints.gla.ac.uk/135827/1/135827.pdf