This article is concerned with identifying important features in high-dimensional data analysis, especially when there are complex relationships among predictors. Without any specification of an ac...

–Thompson sampling is a heuristic algorithm for the multi-armed bandit problem which has long tradition in machine learning. The Bayesian spirit sense that it selects arms based on posterior samples of reward probabilities each arm. By forging connection between combinatorial binary bandits and spike-and-slab variable selection, we propose stochastic optimization approach to subset selection ca...