In this paper, we consider the problem of feature reconstruction from incomplete X-ray CT data. Such data problems occur when number measured X-rays is restricted either due to limit radiation exposure or practical constraints, making detection certain rays challenging. Since image a severely ill-posed (unstable) problem, reconstructed images may suffer characteristic artefacts missing features...

We consider the problem of variable selection in high-dimensional settings with missing observations among covariates. To address this relatively understudied problem, we propose a new synergistic procedure—adaptive Bayesian SLOPE values—which effectively combines (sorted l1 regularization) spike-and-slab LASSO (SSL) and is accompanied by an efficient stochastic approximation expected maximizat...