Zobrazeno 1 - 10
of 32
pro vyhledávání: '"Harada, Kazuharu"'
Autor:
Harada, Kazuharu, Taguri, Masataka
While data-driven confounder selection requires careful consideration, it is frequently employed in observational studies. Widely recognized criteria for confounder selection include the minimal-set approach, which involves selecting variables releva
Externí odkaz:
http://arxiv.org/abs/2402.18904
The exploration of biomarkers, which are clinically useful biomolecules, and the development of prediction models using them are important problems in biomedical research. Biomarkers are widely used for disease screening, and some are related not onl
Externí odkaz:
http://arxiv.org/abs/2309.04685
Autor:
Okuno, Akifumi, Harada, Kazuharu
This study proposes an interpretable neural network-based non-proportional odds model (N$^3$POM) for ordinal regression. N$^3$POM is different from conventional approaches to ordinal regression with non-proportional models in several ways: (1) N$^3$P
Externí odkaz:
http://arxiv.org/abs/2303.17823
Autor:
Harada, Kazuharu, Fujisawa, Hironori
The inverse probability (IPW) and doubly robust (DR) estimators are often used to estimate the average causal effect (ATE), but are vulnerable to outliers. The IPW/DR median can be used for outlier-resistant estimation of the ATE, but the outlier res
Externí odkaz:
http://arxiv.org/abs/2106.13946
Autor:
Minami, Yoshihito, Hiruma, Junichiro, Harada, Kazuharu, Fujimori, Kazuki, Suzuki, Risa, Mori, Miho, Okura, Masahiro, Abe, Namiko, Harada, Kazutoshi, Okubo, Yukari
Publikováno v:
In Journal of the American Academy of Dermatology September 2024
Autor:
Harada, Kazuharu, Fujisawa, Hironori
We consider the problem of inferring the causal structure from observational data, especially when the structure is sparse. This type of problem is usually formulated as an inference of a directed acyclic graph (DAG) model. The linear non-Gaussian ac
Externí odkaz:
http://arxiv.org/abs/2009.03077
Autor:
Okuno, Akifumi1,2 (AUTHOR) okuno@ism.ac.jp, Harada, Kazuharu1,3 (AUTHOR)
Publikováno v:
Journal of Computational & Graphical Statistics. Oct-Dec2024, Vol. 33 Issue 4, p1454-1463. 10p.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Harada, Kazuharu, Fujisawa, Hironori
Publikováno v:
In Neurocomputing 12 October 2021 459:223-233