Missing Data Imputation using Optimal Transport

Boris Muzellec, Julie Josse, Claire Boyer, Marco Cuturi

Type: Preprint

Publication Date: 2020-01-01

Citations: 31

DOI: https://doi.org/10.48550/arxiv.2002.03860

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arXiv (Cornell University) - View
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Works Cited by This (21)

Action	Title	Year	Authors
+	Fast Computation of Wasserstein Barycenters	2014	Marco Cuturi Arnaud Doucet
+	Statistical Analysis With Missing Data	1989	Maureen Lahiff Roderick J. A. Little Donald B. Rubin
+	Maximum Likelihood from Incomplete Data Via the <i>EM</i> Algorithm	1977	A. P. Dempster N. M. Laird Donald B. Rubin
+	What Is Meant by “Missing at Random”?	2013	Shaun R. Seaman John C. Galati Dan Jackson John B. Carlin
+	Scikit-learn: Machine Learning in Python	2012	Fabián Pedregosa Gaël Varoquaux Alexandre Gramfort Vincent Michel Bertrand Thirion Olivier Grisel Mathieu Blondel Peter Prettenhofer Ron J. Weiss Vincent Dubourg
+	<b>mice</b>: Multivariate Imputation by Chained Equations in<i>R</i>	2011	Stef van Buuren Catharina G. M. Groothuis‐Oudshoorn
+	<b>missMDA</b>: A Package for Handling Missing Values in Multivariate Data Analysis	2016	Julie Josse François Husson
+	Improving GANs Using Optimal Transport	2018	Tim Salimans Han Zhang Alec Radford Dimitris Metaxas
+ PDF Chat	Computational Optimal Transport	2019	Gabriel Peyré Marco Cuturi
+ PDF Chat	Why Are Big Data Matrices Approximately Low Rank?	2019	Madeleine Udell Alex Townsend