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In this paper, we propose a new framework for mitigating biases in machine learning systems.
Nonmetric test of the minimax theory of two-person zerosum games
B. O’Neill · 1987
Earlier work this paper cites.
Exponentiated gradient versus gradient descent for linear predictors
J. Kivinen and M. K. Warmuth · 1997
Earlier work this paper cites.
A fast learning algorithm for deep belief nets
G. E. Hinton, S. Osindero, and Y.-W. Teh · 2006
Earlier work this paper cites.
Under-sampling approaches for improving prediction of the minority class in an imbalanced dataset
S.-J. Yen and Y.-S. Lee · 2006
Earlier work this paper cites.
Greedy layer-wise training of deep networks
Y. Bengio, P. Lamblin, D. Popovici, and H. Larochelle · 2007
Earlier work this paper cites.
Data preprocessing techniques for classification without discrimination
F. Kamiran and T. Calders · 2012
Earlier work this paper cites.
Generative adversarial nets
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
Earlier work this paper cites.
Semi-supervised learning with deep generative models
D. P. Kingma, S. Mohamed, D. J. Rezende, and M. Welling · 2014
Earlier work this paper cites.
Conditional generative adversarial nets
M. Mirza and S. Osindero · 2014
Earlier work this paper cites.
Certifying and removing disparate impact
M. Feldman, S. A. Friedler, J. Moeller, C. Scheidegger, and S. Venkatasubramanian · 2015
Earlier work this paper cites.
Deep learning
Y. LeCun, Y. Bengio, and G. Hinton · 2015
Earlier work this paper cites.
Tutorial on variational autoencoders
C. Doersch · 2016
Earlier work this paper cites.
Satisfying real-world goals with dataset constraints
G. Goh, A. Cotter, M. Gupta, and M. P. Friedlander · 2016
Earlier work this paper cites.
Nips 2016 tutorial: Generative adversarial networks
I. Goodfellow · 2016
Cited alongside, same era.
Deep learning
I. Goodfellow, Y. Bengio, and A. Courville · 2016
Cited alongside, same era.
Equality of opportunity in supervised learning
M. Hardt, E. Price, N. Srebro, et al · 2016
Cited alongside, same era.
Categorical reparameterization with gumbel-softmax
E. Jang, S. Gu, and B. Poole · 2016
Cited alongside, same era.
The concrete distribution: A continuous relaxation of discrete random variables
C. J. Maddison, A. Mnih, and Y. W. Teh · 2016
Cited alongside, same era.
Optimized pre-processing for discrimination prevention
Generating multi-categorical samples with generative adversarial networks
R. Camino, C. Hammerschmidt, and R. State · 2018
Later among the works it cites.
X. Chen, J. Wang, and H. Ge · 2018
Later among the works it cites.
A cooperative game for online cloud federation formation based on security risk assessment
T. Halabi, M. Bellaiche, and A. Abusitta · 2018
Later among the works it cites.
Adaptive sensitive reweighting to mitigate bias in fairness-aware classification
E. Krasanakis, E. Spyromitros-Xioufis, S. Papadopoulos, and Y. Kompatsiaris · 2018
Later among the works it cites.
Learning adversarially fair and transferable representations
D. Madras, E. Creager, T. Pitassi, and R. Zemel · 2018
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A. Campolo, M. Sanfilippo, M. Whittaker, and K. Crawford · 2017
Cited alongside, same era.
Improved training of wasserstein gans
I. Gulrajani, F. Ahmed, M. Arjovsky, V. Dumoulin, and A. C. Courville · 2017
Cited alongside, same era.
Learning to pivot with adversarial networks
G. Louppe, M. Kagan, and K. Cranmer · 2017
Cited alongside, same era.
On fairness and calibration
G. Pleiss, M. Raghavan, F. Wu, J. Kleinberg, and K. Q. Weinberger · 2017
Cited alongside, same era.
Learning non-discriminatory predictors
B. Woodworth, S. Gunasekar, M. I. Ohannessian, and N. Srebro · 2017
Cited alongside, same era.
A trust-based game theoretical model for cooperative intrusion detection in multi-cloud environments
A. Abusitta, M. Bellaiche, and M. Dagenais · 2018
Cited alongside, same era.
Later among the works it cites.
Fairgan: Fairness-aware generative adversarial networks
D. Xu, S. Yuan, L. Zhang, and X. Wu · 2018
Later among the works it cites.
Mitigating unwanted biases with adversarial learning
B. H. Zhang, B. Lemoine, and M. Mitchell · 2018
Later among the works it cites.
https://talhassner.github.io/home/projects/Adience/Adience-data.html#agegender
The Adience data set , 2019 (accessed April 2, 2019) · 2019
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Toward secure resource allocation in mobile cloud computing: A matching game
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