Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization | Paper Citation Record

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This paper cites IEEE Trans.

Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization IEEE Trans

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This paper cites Springer-Verlag, Berlin, Heidelberg (1990).

Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization Springer-Verlag, Berlin, Heidelberg (1990)

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This paper cites A survey of bias in Machine Learning through the prism of Statistical Parity for the Adult Data Set.

Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization A survey of bias in Machine Learning through the prism of Statistical Parity for the Adult Data Set

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Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization Unresolved cited work

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This paper cites In: Proceedings of the 1st Conference on Fairness, Accountability and Transparency, Proceedings of Machine Learning Research, vol.

Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization In: Proceedings of the 1st Conference on Fairness, Accountability and Transparency, Proceedings of Machine Learning Research, vol

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This paper cites Big data 5, 153–163 (2017) 14 Tackling Algorithmic Bias in Neural-Network Classiﬁers using Wasserstein-2 RegularizationA PREPRINT.

Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization Big data 5, 153–163 (2017) 14 Tackling Algorithmic Bias in Neural-Network Classiﬁers using Wasserstein-2 RegularizationA PREPRINT

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This paper cites In: Proceedings of the 27th International Conference on Neural Information Processing Systems - V olume 2, p.

Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization In: Proceedings of the 27th International Conference on Neural Information Processing Systems - V olume 2, p

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This paper cites Obtaining fairness using optimal transport theory.

Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization Obtaining fairness using optimal transport theory

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This paper cites Information and Inference: A Journal of the IMA (2018).

Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization Information and Inference: A Journal of the IMA (2018)

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This paper cites Review of Mathematical frameworks for Fairness in Machine Learning.

Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization Review of Mathematical frameworks for Fairness in Machine Learning

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Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization Unresolved cited work

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This paper cites In: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp.

Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization In: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp

Reference 12

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This paper cites In: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, p.

Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization In: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, p

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This paper cites In: International Conference on Machine Learning, pp.

Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization In: International Conference on Machine Learning, pp

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Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization Unresolved cited work

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This paper cites In: Advances in neural information processing systems, pp.

Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization In: Advances in neural information processing systems, pp

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This paper cites In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.

Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp

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This paper cites 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) pp.

Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) pp

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This paper cites In: International Conference on Machine Learning, pp.

Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization In: International Conference on Machine Learning, pp

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Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization In: Proc

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This paper cites In: Proceedings Conference on Uncertainty in Artiﬁcial Intelligence (UAI) (2019).

Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization In: Proceedings Conference on Uncertainty in Artiﬁcial Intelligence (UAI) (2019)

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Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization Unresolved cited work

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This paper cites In: Proceedings of the 2012th European Conference on Machine Learning and Knowledge Discovery in Databases - V olume Part II, p.

Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization In: Proceedings of the 2012th European Conference on Machine Learning and Knowledge Discovery in Databases - V olume Part II, p

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This paper cites In: International Conference on Machine Learning, pp.

Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization In: International Conference on Machine Learning, pp

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This paper cites International Conference on Learning Representations (2014).

Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization International Conference on Learning Representations (2014)

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Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization Adam: A Method for Stochastic Optimization

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Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization In: Advances in Neural Information Processing Systems 25, pp

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Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization Neural Comput

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Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization In: Proceedings of the IEEE, vol

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Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization In: Proceedings of International Conference on Computer Vision (ICCV) (2015)

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Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization Information and Inference: A Journal of the IMA (2019)

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Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization FNNC: Achieving Fairness through Neural Networks

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Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization In: Proceedings of the 36th International Conference on Machine Learning, vol

Reference 35

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Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization University of California Press (2016)

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Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization Making Neural Networks FAIR

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Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization In: Recent Trends in Learning From Data, pp

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Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization In: ECML/PKDD (1), pp

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Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2019)

Reference 40

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Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp

Reference 42

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Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization Anchor regression: heterogeneous data meets causality

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Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization Optimal transport natural gradient for statistical manifolds with continuous sample space

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Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization In: Proceedings of the 26th International Conference on World Wide Web, pp

Reference 47

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Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization In: Proceedings of the 26th International Conference on World Wide Web, pp

Reference 48

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Tackling Algorithmic Bias in Neural-Network Classifiers using Wasserstein-2 Regularization In: Proceedings of the 20th International Conference on Artiﬁcial Intelligence and Statistics, vol

Reference 49

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