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Coordinated Double Machine Learning
Nitai Fingerhut
, Matteo Sesia
,
Yaniv Romano
Research output
:
Contribution to journal
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Conference article
›
peer-review
Overview
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Dive into the research topics of 'Coordinated Double Machine Learning'. Together they form a unique fingerprint.
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Keyphrases
Double Machine Learning
100%
Deep Neural Network
50%
Statistical Methods
50%
Black-box Model
50%
Numerical Experiments
50%
Observational Data
50%
Empirical Performance
50%
Learning Algorithm
50%
Continuous Outcomes
50%
Linear Coefficient
50%
Estimation Bias
50%
Partially Linear Model
50%
High-dimensional Covariates
50%
Treatment Effect Estimation
50%
Coordinated Learning
50%
Nonlinear Prediction Model
50%
Mathematics
Predictive Model
100%
Covariate
50%
Numerical Experiment
50%
Nonlinear
50%
Real Data
50%
Black Box
50%
Simulated Data
50%
Deep Neural Network
50%
Statistical Method
50%
Linear Models
50%
Linear Coefficient
50%
Treatment Effect
50%
Observational Data
50%
Effect Estimate
50%