Adversarial mitigation to reduce unwanted biases in machine learning. (Réduire les biais indésirables en apprentissage automatique par atténuation adverse).

[BibT_eX]

[DOI]

Vincent Grari

PhD thesis, 2022

A fair pricing model via adversarial learning.

[BibT_eX]

[DOI]

CoRR, 2022

Fairness without the Sensitive Attribute via Causal Variational Autoencoder.

[BibT_eX]

[DOI]

Vincent Grari

Sylvain Lamprier

Marcin Detyniecki

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

2021

Learning Unbiased Representations via Rényi Minimization.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Enforcing Individual Fairness via Rényi Variational Inference.

[BibT_eX]

[DOI]

Proceedings of the Neural Information Processing - 28th International Conference, 2021

2020

Achieving Fairness with Decision Trees: An Adversarial Approach.

[BibT_eX]

[DOI]

Data Sci. Eng., 2020

Fairness-Aware Neural Rényi Minimization for Continuous Features.

[BibT_eX]

[DOI]

Vincent Grari

Sylvain Lamprier

Marcin Detyniecki

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019

Fairness-Aware Neural Réyni Minimization for Continuous Features.

[BibT_eX]

[DOI]

CoRR, 2019

Fair Adversarial Gradient Tree Boosting.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Vincent Grari

Timeline

Legend:

Links

On csauthors.net:

Bibliography

Loading...