Regularization vs. Relaxation: A conic optimization perspective of statistical variable selection


Variable selection is a fundamental task in statistical data analysis. Sparsity-inducing regularization methods are a popular class of methods that simultaneously perform variable selection and model estimation. The central problem is a quadratic optimization problem with an `0-norm penalty. Exactly enforcing the `0-norm penalty is computationally… (More)


4 Figures and Tables