A kernel machine for hidden object-ranking problems (HORPs)
Sign Up to like & getrecommendations! Published in 2020 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-020-09184-y
Abstract: Hidden Object-Ranking Problems (HORPs) are object-ranking problems stated as classification or instance-ranking problems. There exists so far no dedicated algorithm for solving them properly and HORPs are usually solved as if they were classification (multi-class… read more here.
Keywords: information; ranking problems; object ranking; hidden object ... See more keywords
MiRKAT: kernel machine regression-based global association tests for the microbiome
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DOI: 10.1093/bioinformatics/btaa951
Abstract: SUMMARY Distance-based tests of microbiome beta diversity are an integral part of many microbiome analyses. MiRKAT enables distance-based association testing with a wide variety of outcome types, including continuous, binary, censored time-to-event, multivariate, correlated and… read more here.
Keywords: tests microbiome; association; regression based; mirkat kernel ... See more keywords
Prenatal metal concentrations and childhood cardio-metabolic risk using Bayesian Kernel Machine Regression to assess mixture and interaction effects.
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DOI: 10.1097/ede.0000000000000962
Abstract: BACKGROUND Trace metal concentrations may affect cardio-metabolic risk, but the role of prenatal exposure is unclear. We examined: 1) the relationship between blood metal concentrations during pregnancy and child cardio-metabolic risk factors; 2) overall effects… read more here.
Keywords: metabolic risk; bayesian kernel; cardio; cardio metabolic ... See more keywords
Cerebellum as a kernel machine: A novel perspective on expansion recoding in granule cell layer
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Computational Neuroscience"
DOI: 10.3389/fncom.2022.1062392
Abstract: Sensorimotor information provided by mossy fibers (MF) is mapped to high-dimensional space by a huge number of granule cells (GrC) in the cerebellar cortex’s input layer. Significant studies have demonstrated the computational advantages and primary… read more here.
Keywords: kernel machine; novel perspective; perspective expansion; expansion recoding ... See more keywords
More accurate semiparametric regression in pharmacogenomics.
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DOI: 10.4310/sii.2018.v11.n4.a2
Abstract: A key step in pharmacogenomic studies is the development of accurate prediction models for drug response based on individuals' genomic information. Recent interest has centered on semiparametric models based on kernel machine regression, which can… read more here.
Keywords: accurate semiparametric; irrelevant covariates; regression pharmacogenomics; regression ... See more keywords