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Semi-supervised (SS) inference has received much attention in recent years.
A unifying approach for doubly-robust l 1 l_{1} regularized estimation of causal contrasts
Smucler, E., Rotnitzky, A., and Robins, J. M. (2019) · 1904
Earlier work this paper cites.
Sparsity double robust inference of average treatment effects
Bradic, J., Wager, S., and Zhu, Y. (2019) · 1905
Earlier work this paper cites.
High dimensional m-estimation with missing outcomes: A semi-parametric framework
Chakrabortty, A., Lu, J., Cai, T. T., and Li, H. (2019) · 1911
Earlier work this paper cites.
Optimal Asymptotic Test of a Composite Statistical Hypothesis
Accomando, F. W. (1974) · 1974
Earlier work this paper cites.
Estimating causal effects of treatments in randomized and nonrandomized studies
Rubin, D. B. (1974) · 1974
Earlier work this paper cites.
Estimation of regression coefficients when some regressors are not always observed
Robins, J. M., Rotnitzky, A., and Zhao, L. P. (1994) · 1994
Earlier work this paper cites.
Semiparametric efficiency in multivariate regression models with missing data
Robins, J. M. and Rotnitzky, A. (1995) · 1995
Earlier work this paper cites.
Inferences for case-control and semiparametric two-sample density ratio models
Qin, J. (1998) · 1998
Earlier work this paper cites.
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Van der Vaart, A. W. (2000) · 2000
Earlier work this paper cites.
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Kallus, N. and Mao, X. (2020) · 2003
Earlier work this paper cites.
Nonparametric estimation of average treatment effects under exogeneity: A review
Imbens, G. W. (2004) · 2004
Earlier work this paper cites.
Doubly robust estimation in missing data and causal inference models
Bang, H. and Robins, J. M. (2005) · 2005
Earlier work this paper cites.
Semi-supervised learning literature survey
Zhu, X. (2005) · 2005
Earlier work this paper cites.
Semi-Supervised Learning
Chapelle, O., Schölkopf, B., and Zien, A. (2006) · 2006
Earlier work this paper cites.
Demystifying double robustness: A comparison of alternative strategies for estimating a population mean from incomplete data
Kang, J. D. and Schafer, J. L. (2007) · 2007
Earlier work this paper cites.
Infinitely imbalanced logistic regression
Owen, A. B. (2007) · 2007
Earlier work this paper cites.
Semiparametric theory and missing data
Tsiatis, A. (2007) · 2007
Earlier work this paper cites.
Dealing with limited overlap in estimation of average treatment effects
Crump, R. K., Hotz, V. J., Imbens, G. W., and Mitnik, O. A. (2009) · 2009
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Gronsbell, J., Liu, M., Tian, L., and Cai, T. (2020) · 2010
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Doubly robust covariate shift regression with semi-nonparametric nuisance models
Liu, M., Zhang, Y., and Cai, T. (2020) · 2010
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A unified framework for high-dimensional analysis of m-estimators with decomposable regularizers
Negahban, S. N., Ravikumar, P., Wainwright, M. J., and Yu, B. (2010) · 2010
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Restricted eigenvalue properties for correlated gaussian designs
Raskutti, G., Wainwright, M. J., and Yu, B. (2010) · 2010
Asymptotic causal inference with observational studies trimmed by the estimated propensity scores
Yang, S. and Ding, P. (2017) · 2017
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Efficient and adaptive linear regression in semi-supervised settings
Chakrabortty, A. and Cai, T. (2018) · 2018
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Double/debiased machine learning for treatment and structural parameters
Chernozhukov, V., Chetverikov, D., Demirer, M., Duflo, E., Hansen, C., Newey, W., and Robins, J. (2018) · 2018
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Handling limited overlap in observational studies with cardinality matching
Visconti, G. and Zubizarreta, J. R. (2018) · 2018
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High-dimensional statistics: A non-asymptotic viewpoint
Wainwright, M. J. (2019) · 2019
Later among the works it cites.
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Introduction to the non-asymptotic analysis of random matrices
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Efficiency bounds for missing data models with semiparametric restrictions
Graham, B. S. (2011) · 2011
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Asymptotics for minimisers of convex processes
Hjort, N. L. and Pollard, D. (2011) · 2011
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Sparse models and methods for optimal instruments with an application to eminent domain
Belloni, A., Chen, D., Chernozhukov, V., and Hansen, C. (2012) · 2012
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A unified framework for high-dimensional analysis of m m -estimators with decomposable regularizers
Negahban, S. N., Ravikumar, P., Wainwright, M. J., and Yu, B. (2012) · 2012
Cited alongside, same era.
Semi-supervised learning with density-ratio estimation
Kawakita, M. and Kanamori, T. (2013) · 2013
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The Bernstein–Orlicz norm and deviation inequalities
van de Geer, S. and Lederer, J. (2013) · 2013
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Zhang, A., Brown, L. D., Cai, T. T., et al. (2019) · 2019
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Semisupervised inference for explained variance in high dimensional linear regression and its applications
Cai, T. T. and Guo, Z. (2020) · 2020
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Inference on finite-population treatment effects under limited overlap
Hong, H., Leung, M. P., and Li, J. (2020) · 2020
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Model-assisted inference for treatment effects using regularized calibrated estimation with high-dimensional data
Tan, Z. (2020) · 2020
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Logistic regression for massive data with rare events
Wang, H. (2020) · 2020
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Semi-supervised linear regression
Azriel, D., Brown, L. D., Sklar, M., Berk, R., Buja, A., and Zhao, L. (2022) · 2022
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Nonparametric inverse probability weighted estimators based on the highly adaptive lasso
Ertefaie, A., Hejazi, N. S., and van der Laan, M. J. (2022) · 2022
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Moving beyond sub-gaussianity in high-dimensional statistics: Applications in covariance estimation and linear regression
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High-dimensional semi-supervised learning: in search of optimal inference of the mean
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Causal Inference: What If. Boca Raton: Chapman & \& Hall/CRC
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Irregular identification, support conditions, and inverse weight estimation
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