Adaptive Lasso, Transfer Lasso, and Beyond: An Asymptotic Perspective

arXiv:2308.15838v2 Announce Type: replace
Abstract: This paper presents a comprehensive exploration of the theoretical properties inherent in the Adaptive Lasso and the Transfer Lasso. The Adaptive Lasso, a well-established method, employs regularization divided by initial estimators and is characterized by asymptotic normality and variable selection consistency. In contrast, the recently proposed Transfer Lasso employs regularization subtracted by initial estimators with the demonstrated capacity to curtail non-asymptotic estimation errors. A pivotal question thus emerges: Given the distinct ways the Adaptive Lasso …

abstract arxiv beyond contrast cs.lg exploration lasso math.st normality paper perspective regularization stat.me stat.ml stat.th transfer type