Yihong Gu
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126
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2026
Optimally taming biases in black-box models for efficient semiparametric estimation
The paper proposes a new, optimal estimator for semiparametric inference that improves upon standard double machine learning (DML) rates by eliminating the first-order stochastic error of nuisance function estimation.
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