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With the advent of generative modeling techniques, synthetic data and its use has penetrated across various domains from unstructured data such as image, text to structured dataset modeling healthcare outcome, risk decisioning in financial domain, and many more.
Gaussian copula marginal regression
Guido Masarotto, Cristiano Varin, et al · 2012
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Generative adversarial networks
Ian J Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Equality of opportunity in supervised learning
Moritz Hardt, Eric Price, and Nathan Srebro · 2016
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A convex framework for fair regression
Richard Berk, Hoda Heidari, Shahin Jabbari, Matthew Joseph, Michael Kearns, Jamie Morgenstern, Seth Neel, and Aaron Roth · 2017
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Conscientious classification: A data scientist’s guide to discrimination-aware classification
Brian d’Alessandro, Cathy O’Neil, and Tom LaGatta · 2017
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Rachel KE Bellamy, Kuntal Dey, Michael Hind, Samuel C Hoffman, Stephanie Houde, Kalapriya Kannan, Pranay Lohia, Jacquelyn Martino, Sameep Mehta, Aleksandra Mojsilovic, et al · 2018
Cited alongside, same era.
Adversarial removal of demographic attributes from text data
Yanai Elazar and Yoav Goldberg · 2018
Cited alongside, same era.
Pate-gan: Generating synthetic data with differential privacy guarantees
James Jordon, Jinsung Yoon, and Mihaela Van Der Schaar · 2018
Cited alongside, same era.
Fairness definitions explained
Sahil Verma and Julia Rubin · 2018
Cited alongside, same era.
Differential privacy has disparate impact on model accuracy
Eugene Bagdasaryan and Vitaly Shmatikov · 2019
ifair: Learning individually fair data representations for algorithmic decision making
Preethi Lahoti, Krishna P Gummadi, and Gerhard Weikum · 2019
Later among the works it cites.
A survey on bias and fairness in machine learning
Ninareh Mehrabi, Fred Morstatter, Nripsuta Saxena, Kristina Lerman, and Aram Galstyan · 2019
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Balanced datasets are not enough: Estimating and mitigating gender bias in deep image representations
Tianlu Wang, Jieyu Zhao, Mark Yatskar, Kai-Wei Chang, and Vicente Ordonez · 2019
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Modeling tabular data using conditional gan
Lei Xu, Maria Skoularidou, Alfredo Cuesta-Infante, and Kalyan Veeramachaneni · 2019
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Cited alongside, same era.
Sara Hooker, Nyalleng Moorosi, Gregory Clark, Samy Bengio, and Emily Denton · 2020
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