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Estimating linear, mean-square continuous functionals is a pivotal challenge in statistics.
Linear hypothesis testing in dense high-dimensional linear models
Zhu, Y. and Bradic, J. (2018) · 1912
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Probability inequalities for sums of bounded random variables
Hoeffding, W. (1963) · 1963
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The central role of the propensity score in observational studies for causal effects
Rosenbaum, P. R. and Rubin, D. B. (1983) · 1983
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Series estimation of semilinear models
Donald, S. G. and Newey, W. K. (1994) · 1994
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Weak Convergence and Empirical Processes: With Applications to Statistics
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Targeted learning: causal inference for observational and experimental data
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Inference on treatment effects after selection among high-dimensional controls
Belloni, A., Chernozhukov, V., and Hansen, C. (2014) · 2014
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Confidence intervals for high-dimensional linear regression: Minimax rates and adaptivity
Cai, T. T. and Guo, Z. (2017) · 2017
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Approximate residual balancing: debiased inference of average treatment effects in high dimensions
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Debiasing the lasso: Optimal sample size for gaussian designs
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Orthogonal machine learning: Power and limitations
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Cross-fitting and fast remainder rates for semiparametric estimation
Newey, W. K. and Robins, J. R. (2018) · 2018
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