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  • Search: subject:"Approximate sparsity"
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Year of publication
Subject
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Approximate Sparsity vs. Density 2 Approximate sparsity 2 Artificial intelligence 2 Double/De-biased Machine Learning 2 Estimation theory 2 Künstliche Intelligenz 2 Lasso 2 Linear Functionals 2 Regularized Riesz Representers 2 Riesz representer 2 Schätztheorie 2 debiased machine learning 2 linear functional 2 Forecasting model 1 Learning process 1 Lernprozess 1 Nichtparametrisches Verfahren 1 Nonparametric statistics 1 Prognoseverfahren 1 Regression analysis 1 Regressionsanalyse 1
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Online availability
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Free 4
Type of publication
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Book / Working Paper 4
Type of publication (narrower categories)
All
Working Paper 4 Arbeitspapier 2 Graue Literatur 2 Non-commercial literature 2
Language
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English 4
Author
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Chernozhukov, Victor 4 Newey, Whitney K. 4 Bradic, Jelena 2 Robins, James 2 Zhu, Yinchu 2
Published in...
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CEMMAP working papers / Centre for Microdata Methods and Practice 2 cemmap working paper 2
Source
All
ECONIS (ZBW) 2 EconStor 2
Showing 1 - 4 of 4
Cover Image
Minimax semiparametric learning with approximate sparsity
Bradic, Jelena; Chernozhukov, Victor; Newey, Whitney K.; … - 2021
This paper is about the ability and means to root-n consistently and efficiently estimate linear, mean-square continuous functionals of a high dimensional, approximately sparse regression. Such objects include a wide variety of interesting parameters such as the covariance between two regression...
Persistent link: https://www.econbiz.de/10012667932
Saved in:
Cover Image
Minimax semiparametric learning with approximate sparsity
Bradic, Jelena; Chernozhukov, Victor; Newey, Whitney K.; … - 2021
This paper is about the ability and means to root-n consistently and efficiently estimate linear, mean-square continuous functionals of a high dimensional, approximately sparse regression. Such objects include a wide variety of interesting parameters such as the covariance between two regression...
Persistent link: https://www.econbiz.de/10012595665
Saved in:
Cover Image
Double/de-biased machine learning using regularized Riesz representers
Chernozhukov, Victor; Newey, Whitney K.; Robins, James - 2018
We provide adaptive inference methods for linear functionals of L1-regularized linear approximations to the conditional expectation function. Examples of such functionals include average derivatives, policy effects, average treatment effects, and many others. The construction relies on building...
Persistent link: https://www.econbiz.de/10011941446
Saved in:
Cover Image
Double/de-biased machine learning using regularized Riesz representers
Chernozhukov, Victor; Newey, Whitney K.; Robins, James - 2018
We provide adaptive inference methods for linear functionals of L1-regularized linear approximations to the conditional expectation function. Examples of such functionals include average derivatives, policy effects, average treatment effects, and many others. The construction relies on building...
Persistent link: https://www.econbiz.de/10011804936
Saved in:
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