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Given the increasing importance of machine learning (ML) in our lives, several algorithmic fairness techniques have been proposed to mitigate biases in the outcomes of the ML models.
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A. Caliskan, J. J. Bryson, and A. Narayanan · 2017
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M. B. Zafar, I. Valera, M. Gomez-Rodriguez, and K. P. Gummadi · 2019
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J. Chakraborty, S. Majumder, Z. Wu, and T. Menzies · 2020
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J. R. Foulds, R. Islam, K. N. Keya, and S. Pan · 2020
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