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pro vyhledávání: '"Rowley, Jeff"'
Autor:
Kitagawa, Toru, Rowley, Jeff
Static supervised learning-in which experimental data serves as a training sample for the estimation of an optimal treatment assignment policy-is a commonly assumed framework of policy learning. An arguably more realistic but challenging scenario is
Externí odkaz:
http://arxiv.org/abs/2409.00379
This paper proposes a novel method to estimate individualised treatment assignment rules. The method is designed to find rules that are stochastic, reflecting uncertainty in estimation of an assignment rule and about its welfare performance. Our appr
Externí odkaz:
http://arxiv.org/abs/2211.01537
Autor:
Kitagawa, Toru, Rowley, Jeff
The von Mises-Fisher family is a parametric family of distributions on the surface of the unit ball, summarised by a concentration parameter and a mean direction. As a quasi-Bayesian prior, the von Mises-Fisher distribution is a convenient and parsim
Externí odkaz:
http://arxiv.org/abs/2202.05192
Autor:
Rowley, Jeffrey R.
Publikováno v:
Theses and Dissertations.
Accurate flash point and flammability limit data are needed to design safe chemical processes. Unfortunately, improper data storage and reporting policies that disregard the temperature dependence of the flammability limit and the fundamental relatio