Special Issue on Safe and Fair Machine Learning
ISSN:
0885-6125 (Print)
1573-0565 (Online)
In this topical collection (18 articles)
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OriginalPaper
Adversarial learning for counterfactual fairness
Vincent Grari, Sylvain Lamprier, Marcin Detyniecki Pages 741-763 -
OriginalPaper
Adversarial supervised contrastive learning
Zhuorong Li, Daiwei Yu, Minghui Wu, Canghong Jin, Hongchuan Yu Pages 2105-2130 -
OriginalPaper
Imbalanced gradients: a subtle cause of overestimated adversarial robustness
Xingjun Ma, Linxi Jiang, Hanxun Huang, Zejia Weng, James Bailey… Pages 2301-2326 -
OriginalPaper
On the incompatibility of accuracy and equal opportunity
Carlos Pinzón, Catuscia Palamidessi, Pablo Piantanida, Frank Valencia Pages 2405-2434 -
OriginalPaper
Dealing with the unevenness: deeper insights in graph-based attack and defense
Haoxi Zhan, Xiaobing Pei Pages 2921-2953 -
OriginalPaper
PreCoF: counterfactual explanations for fairness
Sofie Goethals, David Martens, Toon Calders Pages 3111-3142 -
OriginalPaper
Wasserstein dropout
Joachim Sicking, Maram Akila, Maximilian Pintz, Tim Wirtz… Pages 3161-3204 -
OriginalPaper
Fairness seen as global sensitivity analysis
Clément Bénesse, Fabrice Gamboa, Jean-Michel Loubes, Thibaut Boissin Pages 3205-3232 -
OriginalPaper
Fair tree classifier using strong demographic parity
António Pereira Barata, Frank W. Takes, H. Jaap van den Herik… Pages 3305-3324
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