Develops higher-order influence function estimators for implicitly defined parameters in non-separable structural models using U-processes theory.
Method-of-moments inference for glms and doubly robust functionals under proportional asymptotics
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s-step self-distillation is optimal among spectral shrinkage estimators for s-spiked covariance matrices and necessary for optimality.
This review synthesizes representative advances in high-dimensional statistics, highlights common themes and open problems, and points to key entry works.
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Higher-Order Debiased Estimators for General Treatment Models
Develops higher-order influence function estimators for implicitly defined parameters in non-separable structural models using U-processes theory.
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Self-Distillation is Optimal Among Spectral Shrinkage Estimators in Spiked Covariance Models
s-step self-distillation is optimal among spectral shrinkage estimators for s-spiked covariance matrices and necessary for optimality.
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High-Dimensional Statistics: Reflections on Progress and Open Problems
This review synthesizes representative advances in high-dimensional statistics, highlights common themes and open problems, and points to key entry works.