… Here, we apply the LASSO Bandit to learn an optimal dosing strategy using patients’ clinical
… to a Bayesian prior over the unknown arm parameters. In practice, the decision maker may …

… : regular Bayesian LASSO and reciprocal Bayesian LASSO, in light of their respective
hierarchical formulations. To observe that, we rewrite the Bayesian LASSO hierarchical model …

… properties of lasso approaches used for variable selection to Bayesian variable … Bayesian
lasso and elastic net lasso, but they also included a formulation for spike-and-slab Bayesian …

… Bayesian LASSO method to determine what factors affect an individual's FWB score. The
Bayesian LASSO … zero, indicating that the Bayesian LASSO technique was successful in …

… This study applies Bayesian LASSO approach to investigate the main determinants of
CO 2 emissions in 56 countries from 1995 to 2014. In a multivariate framework, this study …

… A set of individual, family, and contextual characteristics was selected through the Lasso
method and a Bayesian approach to explain the decision not to continue on with upper …

… Overall, the Pythagorean fuzzy multivariate regression analysis enables decision makers to
… Therefore, Bayesian Lasso [56] can be developed to improve the original form of the Lasso …

… functions, similarly to Bayesian fused LASSO in its functional form, … The problem of
overshrinkage that is inherent in lasso is … prior can be expressed as the hierarchical Bayesian …

… We defined two threshold values for DR th and D th for decision making in subsurface
modeling practice. The higher the threshold values used, the simpler the stratification model …

The goal of this paper is to contrast and survey the major advances in two of the most commonly
used high-dimensional techniques, namely, the Lasso and horseshoe regularization. …