“...We derive the degrees of freedom of the lasso fit, placing no assumptions on the predictor matrix X. Like the well-known result of Zou, Hastie and Tibshirani...”

“...In the sparse linear regression setting, we consider testing the significance of the predictor variable that enters the current lasso model, in the sequence of...”

“...We propose a general method for constructing confidence intervals and statistical tests for single or low-dimensional components of a large parameter vector in...”

“...We propose MC+, a fast, continuous, nearly unbiased and accurate method of penalized variable selection in high-dimensional linear regression. The LASSO is...”

“...This paper considers the noisy sparse phase retrieval problem: recovering a sparse signal x ϵ ℝp from noisy quadratic measurements yj = (a′jx)² + εj, j = 1 , ...”

“...We study full Bayesian procedures for high-dimensional linear regression under sparsity constraints. The prior is a mixture of point masses at zero and...”

“...In the period 1991-2015, algorithmic advances in Mixed Integer Optimization (MIO) coupled with hardware improvements have resulted in an astonishing 450...”

“...We consider the problem of estimating the graph associated with a binary Ising Markov random field. We describe a method based on ℓ₁-regularized logistic...”