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Statistical algorithms are usually helping in making decisions in many aspects of our lives.
The Monge-Kantorovich problem on mass transfer and its applications in stochastics
S. T. Rachev · 1984
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Notes on the wasserstein metric in hilbert spaces
Juan Antonio Cuesta and Carlos Matrán · 1989
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Topics in optimal transportation
Cédric Villani · 2003
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Introduction to statistical learning theory
Olivier Bousquet, Stéphane Boucheron, and Gábor Lugosi · 2004
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Concentration inequalities and model selection
Pascal Massart · 2007
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Optimal transport: old and new
Cédric Villani · 2008
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Barycenters in the wasserstein space
Martial Agueh and Guillaume Carlier · 2011
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Characterization of barycenters in the wasserstein space by averaging optimal transport maps
Jérémie Bigot and Thierry Klein · 2012
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A study of top-k measures for discrimination discovery
Dino Pedreschi, Salvatore Ruggieri, and Franco Turini · 2012
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Fast computation of wasserstein barycenters
Marco Cuturi and Arnaud Doucet · 2014
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Distributions template estimate with wasserstein metrics
Emmanuel Boissard, Thibaut Le Gouic, Jean-Michel Loubes, et al · 2015
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Certifying and removing disparate impact
Michael Feldman, Sorelle A Friedler, John Moeller, Carlos Scheidegger, and Suresh Venkatasubramanian · 2015
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Fairness in criminal justice risk assessments: the state of the art
A continuous framework for fairness
Philipp Hacker and Emil Wiedemann · 2017
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James E Johndrow and Kristian Lum · 2017
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Existence and consistency of wasserstein barycenters
Thibaut Le Gouic and Jean-Michel Loubes · 2017
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Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez Rodriguez, and Krishna P Gummadi · 2017
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Confidence intervals for testing disparate impact in fair learning
Philippe Besse, Eustasio Del Barrio, Paula Gordaliza, and Jean-Michel Loubes · 2018
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Richard Berk, Hoda Heidari, Shahin Jabbari, Michael Kearns, and Aaron Roth · 2017
Cited alongside, same era.
Penalizing Unfairness in Binary Classification
Y. Bechavod and K. Ligett · 2017
Cited alongside, same era.
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Empirical Risk Minimization under Fairness Constraints
M. Donini, L. Oneto, S. Ben-David, J. Shawe-Taylor, and M. Pontil · 2018
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A comparative study of fairness-enhancing interventions in machine learning
S. A. Friedler, C. Scheidegger, S. Venkatasubramanian, S. Choudhary, E. P. Hamilton, and D. Roth · 2018
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