An adaptive shortest-solution guided decimation approach to sparse high-dimensional linear regression
Abstract High-dimensional linear regression model is the most popular statistical model for high-dimensional data, but it is quite a challenging task to achieve a sparse set of regression coefficients.In this paper, we propose a simple heuristic algorithm to construct sparse high-dimensional linear regression models, which is adapted from the short