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Found 3 papers, 1 papers with code
Penalized Generative Variable Selection
Deep networks are increasingly applied to a wide variety of data, including data with high-dimensional predictors.
Semi-parametric Bayesian variable selection for gene-environment interactions
Existing Bayesian methods for G$\times$E interaction studies are challenged by the high-dimensional nature of the study and the complexity of environmental influences.
Methodology
Structural modeling using overlapped group penalties for discovering predictive biomarkers for subgroup analysis
The identification of predictive biomarkers from a large scale of covariates for subgroup analysis has attracted fundamental attention in medical research.
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