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Victor Chernozhukov

Victor Chernozhukov

Academic outputs

Cemmap Working Paper CWP41/18
We develop a theory for estimation of a high-dimensional sparse parameter 𝛳 defi ned as a minimizer of a population loss function LD(𝛳,g0) which, in addition to 𝛳, depends on a, potentially infi nite dimensional, nuisance parameter g0.
Cemmap Working Paper CWP40/18
This paper provides estimation and inference methods for a structural function, such as Conditional Average Treatment Effect (CATE), based on modern machine learning (ML) tools.

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