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@incollection{kennedy2016semiparametric,
title = {Semiparametric Theory and Empirical Processes in Causal Inference},
author = {Kennedy, Edward H},
booktitle = {Statistical Causal Inferences and Their Applications in Public
Health Research},
editor = {He, Hua and Wu, Pan and Chen, Ding-Geng (Din)},
year = {2016},
publisher = {Springer},
pages = {141--167},
doi = {10.1007/978-3-319-41259-7_8},
}
@article{fisher2020visually,
title = {Visually communicating and teaching intuition for influence
functions},
author = {Fisher, Aaron and Kennedy, Edward H},
journal = {The American Statistician},
volume = {75},
number = {2},
pages = {162--172},
year = {2020},
publisher = {Taylor \& Francis},
doi = {10.1080/00031305.2020.1717620},
}
@misc{herbps10_2023,
author = {Susmann, Herb},
title = {One Step Estimators and Pathwise Derivatives},
howpublished = {\url{https://observablehq.com/@herbps10/one-step-estimators-and-pathwise-derivatives}},
year = {2023},
note = {Accessed: YYYY-MM-DD},
}
@incollection{kennedy2022semiparametric,
title={Semiparametric doubly robust targeted double machine learning: A
review},
author={Kennedy, Edward H},
booktitle={Handbook of Statistical Methods for Precision Medicine},
editor={Laber, Eric and Chakraborty, Bibhas and Moodie, Erica E M and Cai,
Tianxi and {van der Laan}, Mark J},
pages={207--236},
year={2024},
publisher={Chapman and Hall/CRC},
doi={10.48550/arXiv.2203.06469}
}
@article{hines2022demystifying,
title = {Demystifying statistical learning based on efficient influence
functions},
author = {Hines, Oliver and Dukes, Oliver and Diaz-Ordaz, Karla and
Vansteelandt, Stijn},
journal = {The American Statistician},
volume = {76},
number = {3},
pages = {292--304},
year = {2022},
publisher = {Taylor \& Francis},
doi = {10.1080/00031305.2021.2021984},
}
@article{diaz2020machine,
title = {Machine learning in the estimation of causal effects: targeted
minimum loss-based estimation and double/debiased machine learning},
author = {D{\'\i}az, Iv{\'a}n},
journal = {Biostatistics},
volume = {21},
number = {2},
pages = {353--358},
year = {2020},
publisher = {Oxford University Press},
doi = {10.1093/biostatistics/kxz042},
}
@article{henmi2004paradox,
title = {A paradox concerning nuisance parameters and projected estimating
functions},
author = {Henmi, Masayuki and Eguchi, Shinto},
journal = {Biometrika},
volume = {91},
number = {4},
pages = {929--941},
year = {2004},
publisher = {Oxford University Press},
doi = {10.1093/biomet/91.4.929},
}
@article{ying2024geometric,
title = {A geometric perspective on double robustness by semiparametric theory
and information geometry},
author = {Ying, Andrew},
journal = {arXiv preprint arXiv:2404.13960},
url = {https://arxiv.org/abs/2404.13960},
year = {2024},
}
@book{tsiatis2007semiparametric,
title = {Semiparametric Theory and Missing Data},
author = {Tsiatis, Anastasios},
year = {2007},
publisher = {Springer},
doi = {10.1007/0-387-37345-4},
}
@book{kosorok2008introduction,
title = {Introduction to Empirical Processes and Semiparametric Inference},
author = {Kosorok, Michael R},
year = {2008},
publisher = {Springer},
doi = {10.1007/978-0-387-74978-5},
}
@book{vdl2003unified,
title = {Unified Methods for Censored Longitudinal Data and Causality},
author = {{van der Laan}, Mark J and Robins, James M},
year = {2003},
publisher = {Springer},
doi = {10.1007/978-0-387-21700-0},
}
@book{vdl2011targeted,
title = {Targeted Learning: Causal Inference for Observational and
Experimental Data},
author = {{van der Laan}, Mark J and Rose, Sherri},
year = {2011},
publisher = {Springer},
doi = {10.1007/978-1-4419-9782-1},
}
@book{vdl2018targeted,
title = {Targeted Learning in Data Science: Causal Inference for Complex
Longitudinal Studies},
author = {{van der Laan}, Mark J and Rose, Sherri},
year = {2018},
publisher = {Springer},
doi = {10.1007/978-3-319-65304-4},
}
@phdthesis{rytgaard2020phd,
title = {Targeted causal learning for longitudinal data},
school = {University of Copenhagen},
author = {Rytgaard, Helene Charlotte},
year = {2020},
url = {https://biostat.ku.dk/dissertations/2020_rytgaard.pdf},
}
@book{hernan2023causal,
title = {Causal Inference: What If},
author = {Hern{\'a}n, Miguel A and Robins, James M},
year = {2024},
publisher = {CRC Press},
doi = {},
}
@article{bang2005doubly,
title = {Doubly robust estimation in missing data and causal inference models},
author = {Bang, Heejung and Robins, James M.},
journal = {Biometrics},
volume = {61},
number = {4},
pages = {962--973},
year = {2005},
publisher = {Wiley Online Library},
doi = {10.1111/j.1541-0420.2005.00377.x},
}
@article{vdl2012targeted,
title = {Targeted minimum loss based estimation of causal effects of multiple
time point interventions},
author = {{van der Laan}, Mark J and Gruber, Susan},
journal = {The International Journal of Biostatistics},
volume = {8},
number = {1},
year = {2012},
publisher = {De Gruyter},
}
@article{liu2023causal,
title = {Causal inference for longitudinal data based on historical controls},
author = {Liu, Jeen and Zhang, Jane and Mitchell, Alan and Fang, Mindy and
Tian, Lu},
journal = {Journal of Biopharmaceutical Statistics},
volume = {33},
number = {3},
pages = {289--306},
year = {2023},
publisher = {Taylor \& Francis},
doi = {10.1080/10543406.2022.2148164},
}
@book{vdvaart1998asymptotic,
title = {Asymptotic Statistics},
author = {{van der Vaart}, Aad W},
year = {1998},
publisher = {Cambridge University Press},
doi = {10.1017/CBO9780511802256},
}
@book{bickel2015mathematical,
title={Mathematical Statistics: Basic Ideas and Selected Topics, Volume II},
author={Bickel, Peter J and Doksum, Kjell A},
year={2015},
publisher={CRC Press},
doi={10.1201/b19822}
}
@book{tsybakov2009introduction,
title = {Introduction to Nonparametric Estimation},
author = {Tsybakov, Alexandre B},
year = {2009},
publisher = {Springer},
doi = {10.1007/b13794},
}
@book{wainwright2019highdim,
title = {High-Dimensional Statistics: A Non-Asymptotic Viewpoint},
author = {Wainwright, Martin J},
year = {2019},
publisher = {Cambridge University Press},
doi = {10.1017/9781108627771},
}
@book{hardt2022patterns,
title = {Patterns, Predictions, and Actions: Foundations of Machine
Learning},
author = {Hardt, Moritz and Recht, Benjamin},
year = {2022},
publisher = {Princeton University Press},
doi = {},
url = {https://mlstory.org/}
}
@book{boucheron2013concentration,
title = {Concentration Inequalities: A Nonasymptotic Theory of Independence},
author = {Boucheron, St{\'e}phane and Lugosi, G{\'a}bor and Massart, Pascal},
year = {2013},
publisher = {Oxford University Press},
doi = {10.1093/acprof:oso/9780199535255.001.0001}
}
@book{bach2024learning,
title = {Learning Theory from First Principles},
author = {Bach, Francis},
year = {2024},
publisher = {},
url = {https://www.di.ens.fr/%7Efbach/ltfp_book.pdf}
}
@book{duchi2024statistics,
title = {Statistics and Information Theory},
author = {Duchi, John},
year = {2024},
publisher = {},
url = {https://web.stanford.edu/class/stats311/lecture-notes.pdf}
}