March 20, 2024, 4:43 a.m. | Aramayis Dallakyan, Mohsen Pourahmadi

stat.ML updates on arXiv.org arxiv.org

arXiv:2403.12357v1 Announce Type: cross
Abstract: The Graphical Lasso (GLasso) algorithm is fast and widely used for estimating sparse precision matrices (Friedman et al., 2008). Its central role in the literature of high-dimensional covariance estimation rivals that of Lasso regression for sparse estimation of the mean vector. Some mysteries regarding its optimization target, convergence, positive-definiteness and performance have been unearthed, resolved and presented in Mazumder and Hastie (2011), leading to a new/improved (dual-primal) DP-GLasso. Using a new and slightly different reparametriztion …

abstract algorithm arxiv covariance lasso literature mean optimization precision regression role stat.co stat.ml type vector

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