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  • Search: subject:"Double/De-biased Machine Learning"
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Year of publication
Subject
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Approximate Sparsity vs. Density 2 Double/De-biased Machine Learning 2 Linear Functionals 2 Regularized Riesz Representers 2 Artificial intelligence 1 Estimation theory 1 Forecasting model 1 Künstliche Intelligenz 1 Prognoseverfahren 1 Schätztheorie 1
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Online availability
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Free 2
Type of publication
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Book / Working Paper 2
Type of publication (narrower categories)
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Working Paper 2 Arbeitspapier 1 Graue Literatur 1 Non-commercial literature 1
Language
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English 2
Author
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Chernozhukov, Victor 2 Newey, Whitney K. 2 Robins, James 2
Published in...
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CEMMAP working papers / Centre for Microdata Methods and Practice 1 cemmap working paper 1
Source
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ECONIS (ZBW) 1 EconStor 1
Showing 1 - 2 of 2
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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
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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
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