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Least squares after model selection in high-dimensional sparse models

Least squares after model selection in high-dimensional sparse models

A. Belloni
Victor Chernozhukov
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Papers citing "Least squares after model selection in high-dimensional sparse models"

5 / 5 papers shown
Title
Treatment Effect Estimation with Observational Network Data using Machine Learning
Treatment Effect Estimation with Observational Network Data using Machine Learning
Corinne Emmenegger
Meta-Lina Spohn
Timon Elmer
Peter Buhlmann
CML
119
3
1
20 Jan 2025
Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation
Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation
Jikai Jin
Vasilis Syrgkanis
CML
120
1
0
22 Feb 2024
Taking Advantage of Sparsity in Multi-Task Learning
Taking Advantage of Sparsity in Multi-Task Learning
Karim Lounici
Massimiliano Pontil
Alexandre B. Tsybakov
Sara van de Geer
283
292
0
09 Mar 2009
The sparsity and bias of the Lasso selection in high-dimensional linear regression
The sparsity and bias of the Lasso selection in high-dimensional linear regression
Cun-Hui Zhang
Jian Huang
318
869
0
07 Aug 2008
High-dimensional generalized linear models and the lasso
High-dimensional generalized linear models and the lasso
Sara van de Geer
456
755
0
04 Apr 2008