AI & ML
The Adaptive Lasso with Weighted IPW Factor and KRR Penalty Function
arXiv stat.TH0 views
arXiv:2610.08805v1 Announce Type: new Abstract: In this paper, we first consider a Lasso estimator incorporating a weighted IPW factor,and obtain certain conditions for the Lasso variable selection to be consistent or inconsistent. Then we provide a modified version of the adaptive Lasso equipped with a weighted IPW factor and a KRR penalty function, establishing that the proposed adaptive Lasso possesses the Oracle property. Numerical simulations demonstrate that the proposed adaptive Lasso exhibits near-minimax optimality in performance
Source:https://arxiv.org/abs/2610.08805PreviousMadeleine: Learning Involuntary Recall for Conversational Memory from Simulated LivesNextGraph-monotone entrywise guarantees for MLE and Rank Centrality on general comparison graphs
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