Subset Selection with Shrinkage: Sparse Linear Modeling When the SNR Is Low

Subset Selection with Shrinkage: Sparse Linear Modeling When the SNR Is Low

<jats:p> Learning Compact High-Dimensional Models in Noisy Environments </jats:p><jats:p> Building compact, interpretable statistical models where the output depends upon a small number of input features is a well-known problem in modern analytics applications. A fundamental tool u...

Полное описание

Библиографические подробности
Главные авторы:	Mazumder, Rahul, Radchenko, Peter, Dedieu, Antoine
Другие авторы:	Sloan School of Management
Формат:	Статья
Язык:	English
Опубликовано:	Institute for Operations Research and the Management Sciences (INFORMS) 2022
Online-ссылка:	https://hdl.handle.net/1721.1/144220

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