A parametric regression framework for the skew sinh-arcsinh t distribution
Sign Up to like & getrecommendations! Published in 2021 at "Applied Mathematical Modelling"
DOI: 10.1016/j.apm.2020.08.036
Abstract: Abstract On the basis of an interesting and tractable parametric family of distributions, which figures prominently as an empirical model for asymmetric and heavy-tailed data, we introduce a novel parametric regression model that is quite… read more here.
Keywords: parametric regression; skew sinh; regression; regression framework ... See more keywords
A regression framework to uncover pleiotropy in large-scale electronic health record data
Sign Up to like & getrecommendations! Published in 2019 at "Journal of the American Medical Informatics Association : JAMIA"
DOI: 10.1093/jamia/ocz084
Abstract: OBJECTIVE Pleiotropy, where 1 genetic locus affects multiple phenotypes, can offer significant insights in understanding the complex genotype-phenotype relationship. Although individual genotype-phenotype associations have been thoroughly explored, seemingly unrelated phenotypes can be connected genetically through… read more here.
Keywords: regression; health record; large scale; electronic health ... See more keywords
A Deep Regression Framework Toward Laboratory Accuracy in the Shop Floor of Microelectronics
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2022.3182343
Abstract: Deep learning (DL) has certainly improved industrial inspection, while significant progress has also been achieved in metrology with impressive results reached through their combination. However, it is not easy to deploy metrology sensors in a… read more here.
Keywords: regression framework; deep regression; methodology; toward laboratory ... See more keywords
A Robust Regression Framework with Laplace Kernel-Induced Loss
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DOI: 10.1162/neco_a_01002
Abstract: This work proposes a robust regression framework with nonconvex loss function. Two regression formulations are presented based on the Laplace kernel-induced loss (LK-loss). Moreover, we illustrate that the LK-loss function is a nice approximation for… read more here.
Keywords: regression; regression framework; laplace kernel; robust regression ... See more keywords