Chernozhukov et al., 2018 - Google Patents
Double/debiased machine learning for treatment and structural parametersChernozhukov et al., 2018
View HTML- Document ID
- 17289873169606420768
- Author
- Chernozhukov V
- Chetverikov D
- Demirer M
- Duflo E
- Hansen C
- Newey W
- Robins J
- Publication year
- Publication venue
- The econometrics journal
External Links
Snippet
We revisit the classic semi‐parametric problem of inference on a low‐dimensional parameter θ0 in the presence of high‐dimensional nuisance parameters η0. We depart from the classical setting by allowing for η0 to be so high‐dimensional that the traditional …
- 238000010801 machine learning 0 title abstract description 38
Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
- G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
- G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
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