# Square-Root Lasso: Pivotal Recovery of Sparse Signals via Conic Programming

@inproceedings{Belloni2010SquareRootLP,
title={Square-Root Lasso: Pivotal Recovery of Sparse Signals via Conic Programming},
author={Alexandre Belloni and Victor Chernozhukov and Lie Wang},
year={2010}
}
• Published 2010
• Mathematics
We propose a pivotal method for estimating high-dimensional sparse linear regression models, where the overall number of regressors p is large, possibly much larger than n, but only s regressors are significant. The method is a modification of Lasso, called square-root Lasso. The method neither relies on the knowledge of the standard deviation σ of the regression errors nor does it need to pre-estimate σ. Despite not knowing σ, square-root Lasso achieves near-oracle performance, attaining the… Expand
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