Fetching the paper…
Reading the bibliography…
In observational causal inference, in order to emulate a randomized experiment, weights are used to render treatments independent of observed covariates.
Asymptotic theory of rejective sampling with varying probabilities from a finite population
Jaroslav Hájek · 1964
Earlier work this paper cites.
The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming
L.M. Bregman · 1967
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.
Evaluating the econometric evaluations of training programs with experimental data
Robert J LaLonde · 1986
Earlier work this paper cites.
Causal inference from complex longitudinal data
James M Robins · 1997
Earlier work this paper cites.
A probabilistic analysis of the rocchio algorithm with tfidf for text categorization
Thorsten Joachims · 1997
Earlier work this paper cites.
Inferences for case-control and semiparametric two-sample density ratio models
Jing Qin · 1998
Earlier work this paper cites.
Learning with kernels: support vector machines, regularization, optimization, and beyond
Bernhard Scholkopf and Alexander J Smola · 2001
Earlier work this paper cites.
Boosting and maximum likelihood for exponential models
Guy Lebanon and John D Lafferty · 2002
Earlier work this paper cites.
Efficient estimation of average treatment effects using the estimated propensity score
Keisuke Hirano, Guido W Imbens, and Geert Ridder · 2003
Earlier work this paper cites.
Semiparametric density estimation under a two-sample density ratio model
Kuang Fu Cheng, Chih-Kang Chu, et al · 2004
Earlier work this paper cites.
Causal inference with general treatment regimes: Generalizing the propensity score
Kosuke Imai and David A Van Dyk · 2004
Earlier work this paper cites.
On multivariate goodness-of-fit and two-sample testing
Jerome Friedman · 2004
Earlier work this paper cites.
Kernel methods for measuring independence
A. Gretton, R. Herbrich, A. Smola, O. Bousquet, and B. Schoelkopf · 2005
Earlier work this paper cites.
Loss functions for binary class probability estimation and classification: Structure and applications
Andreas Buja, Werner Stuetzle, and Yi Shen · 2005
Earlier work this paper cites.
Does matching overcome lalonde’s critique of nonexperimental estimators?
Jeffrey A Smith and Petra E Todd · 2005
Earlier work this paper cites.
Discriminative learning for differing training and test distributions
Steffen Bickel, Michael Brückner, and Tobias Scheffer · 2007
Earlier work this paper cites.
Demystifying double robustness: A comparison of alternative strategies for estimating a population mean from incomplete data
Joseph DY Kang and Joseph L Schafer · 2007
Cited alongside, same era.
Strictly proper scoring rules, prediction, and estimation
Tilmann Gneiting and Adrian E Raftery · 2007
Cited alongside, same era.
The geometry of proper scoring rules
A Philip Dawid · 2007
Cited alongside, same era.
Correcting sample selection bias by unlabeled data
Jiayuan Huang, Arthur Gretton, Karsten M Borgwardt, Bernhard Schölkopf, and Alex J Smola · 2007
Cited alongside, same era.
Constructing inverse probability weights for marginal structural models
Stephen R. Cole and Miguel A. Hernán · 2008
Cited alongside, same era.
Does obesity shorten life? the importance of well-defined interventions to answer causal questions
Miguel A Hernán and Sarah L Taubman · 2008
Entropy balancing for causal effects: A multivariate reweighting method to produce balanced samples in observational studies
Jens Hainmueller · 2012
Later among the works it cites.
Density-ratio matching under the bregman divergence: a unified framework of density-ratio estimation
Masashi Sugiyama, Taiji Suzuki, and Takafumi Kanamori · 2012
Later among the works it cites.
A kernel two-sample test
Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, and Alexander Smola · 2012
Later among the works it cites.
Scoring rules, divergences and information in Bayesian machine learning
Ferenc Huszar · 2013
Later among the works it cites.
Genetic matching for estimating causal effects: A general multivariate matching method for achieving balance in observational studies
Alexis Diamond and Jasjeet S Sekhon · 2013
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
On pinsker’s type inequalities and csiszár’s f-divergences. part i: Second and fourth-order inequalities
Gustavo L Gilardoni · 2008
Cited alongside, same era.
Injective hilbert space embeddings of probability measures
Bharath K Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Gert RG Lanckriet, and Bernhard Schölkopf · 2008
Cited alongside, same era.
Learning via Hilbert space embedding of distributions
Le Song · 2008
Cited alongside, same era.
Causality
Judea Pearl · 2009
Cited alongside, same era.
Covariate shift by kernel mean matching
Arthur Gretton, Alex Smola, Jiayuan Huang, Marcel Schmittfull, Karsten Borgwardt, and Bernhard Scholkopf · 2009
Cited alongside, same era.
Propensity score techniques and the assessment of measured covariate balance to test causal associations in psychological research
Valerie S Harder, Elizabeth A Stuart, and James C Anthony · 2010
Cited alongside, same era.
Kosuke Imai and Marc Ratkovic · 2014
Later among the works it cites.
Stable weights that balance covariates for estimation with incomplete outcome data
José R Zubizarreta · 2015
Later among the works it cites.
Kernel balancing: A flexible non-parametric weighting procedure for estimating causal effects
Chad Hazlett · 2016
Later among the works it cites.
Non-parametric methods for doubly robust estimation of continuous treatment effects
Edward H. Kennedy, Zongming Ma, Matthew D. McHugh, and Dylan S. Small · 2016
Later among the works it cites.
Linking losses for density ratio and class-probability estimation
Aditya Menon and Cheng Soon Ong · 2016
Later among the works it cites.
Learning in implicit generative models
Shakir Mohamed and Balaji Lakshminarayanan · 2016
Later among the works it cites.
Bipartite ranking: a risk-theoretic perspective
Aditya Krishna Menon and Robert C Williamson · 2016
Later among the works it cites.
Kernel-based covariate functional balancing for observational studies
Raymond KW Wong and Kwun Chuen Gary Chan · 2017
Later among the works it cites.
Covariate balancing propensity score for a continuous treatment: Application to the efficacy of political advertisements
Christian Fong, Chad Hazlett, Kosuke Imai, et al · 2018
Later among the works it cites.
Covariate balancing propensity score by tailored loss functions
Qingyuan Zhao · 2019
Closest in time.
A framework for covariate balance using bregman distances
Kevin P. Josey, Elizabeth Juarez-Colunga, Fan Yang, and Debashis Ghosh · 2020
Closest in time.