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Journal Articles
- 2022
[j2]Alexey Miroshnikov
, Konstandinos Kotsiopoulos, Ryan Franks, Arjun Ravi Kannan:
Wasserstein-based fairness interpretability framework for machine learning models. Mach. Learn. 111(9): 3307-3357 (2022)- 2017
- [j1]Alexey Miroshnikov, Robin Young:
Weak* Solutions II: The Vacuum in Lagrangian Gas Dynamics. SIAM J. Math. Anal. 49(3): 1810-1843 (2017)
Informal and Other Publications
- 2023
- [i5]Khashayar Filom, Alexey Miroshnikov, Konstandinos Kotsiopoulos, Arjun Ravi Kannan:
On marginal feature attributions of tree-based models. CoRR abs/2302.08434 (2023) - [i4]Konstandinos Kotsiopoulos, Alexey Miroshnikov, Khashayar Filom, Arjun Ravi Kannan:
Approximation of group explainers with coalition structure using Monte Carlo sampling on the product space of coalitions and features. CoRR abs/2303.10216 (2023) - 2021
- [i3]Alexey Miroshnikov, Konstandinos Kotsiopoulos, Arjun Ravi Kannan:
Mutual information-based group explainers with coalition structure for machine learning model explanations. CoRR abs/2102.10878 (2021) - [i2]Alexey Miroshnikov, Konstandinos Kotsiopoulos, Ryan Franks, Arjun Ravi Kannan:
Model-agnostic bias mitigation methods with regressor distribution control for Wasserstein-based fairness metrics. CoRR abs/2111.11259 (2021) - 2020
- [i1]Alexey Miroshnikov, Konstandinos Kotsiopoulos, Ryan Franks, Arjun Ravi Kannan:
Wasserstein-based fairness interpretability framework for machine learning models. CoRR abs/2011.03156 (2020)
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