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In machine learning, it is commonly assumed that training and test data share the same population distribution.
The Theory of Error-Correcting Codes , volume 16
Florence Jessie MacWilliams and Neil James Alexander Sloane · 1977
Earlier work this paper cites.
Minimum aberration 2 k − p 2^{k-p} designs
Arthur Fries and William G Hunter · 1980
Earlier work this paper cites.
The central role of the propensity score in observational studies for causal effects
Paul R Rosenbaum and Donald B Rubin · 1983
Earlier work this paper cites.
Regression shrinkage and selection via the lasso
Robert Tibshirani · 1996
Earlier work this paper cites.
A note on generalized aberration in factorial designs
Chang-Xing Ma and Kai-Tai Fang · 2001
Earlier work this paper cites.
Generalized minimum aberration for asymmetrical fractional factorial designs
Hongquan Xu and CF Jeff Wu · 2001
Earlier work this paper cites.
Statistics for experimenters
George EP Box, J Stuart Hunter, and William G Hunter · 2005
Earlier work this paper cites.
Majorization framework for balanced lattice designs
Aijun Zhang, Kai-Tai Fang, Runze Li, Agus Sudjianto, et al · 2005
Earlier work this paper cites.
Stable weights that balance covariates for estimation with incomplete outcome data
José R Zubizarreta · 2006
Earlier work this paper cites.
Fractional Factorial Plans , volume 496
Aloke Dey and Rahul Mukerjee · 2009
Earlier work this paper cites.
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Petros Drineas, Michael W Mahoney, Shan Muthukrishnan, and Tamás Sarlós · 2011
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Experiments: Planning, Analysis, and Optimization , volume 552
CF Jeff Wu and Michael S Hamada · 2011
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Ping Ma, Michael W Mahoney, and Bin Yu · 2015
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Causal inference by using invariant prediction: identification and confidence intervals
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Domain generalization by marginal transfer learning
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Approximate residual balancing: debiased inference of average treatment effects in high dimensions
Susan Athey, Guido W Imbens, and Stefan Wager · 2018
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Stable prediction across unknown environments
Kun Kuang, Peng Cui, Susan Athey, Ruoxuan Xiong, and Bo Li · 2018
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A Samad Hedayat, Neil James Alexander Sloane, and John Stufken · 2012
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Sampling
Steven K. Thompson · 2012
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Domain generalization via invariant feature representation
Krikamol Muandet, David Balduzzi, and Bernhard Schölkopf · 2013
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R package frf2 for creating and analyzing fractional factorial 2-level designs
Ulrike Grönmping · 2014
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Estimating treatment effect in the wild via differentiated confounder balancing
Kun Kuang, Peng Cui, Bo Li, Meng Jiang, and Shiqiang Yang
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Treatment effect estimation with data-driven variable decomposition
Kun Kuang, Peng Cui, Bo Li, Meng Jiang, Shiqiang Yang, and Fei Wang
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Mateo Rojas-Carulla, Bernhard Schölkopf, Richard Turner, and Jonas Peters · 2018
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Optimal subsampling for large sample logistic regression
HaiYing Wang, Rong Zhu, and Ping Ma · 2018
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More efficient estimation for logistic regression with optimal subsamples
HaiYing Wang · 2019
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Information-based optimal subdata selection for big data linear regression
HaiYing Wang, Min Yang, and John Stufken · 2019
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