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Wasserstein-based fairness interpretability framework for machine
  learning models
v1v2v3v4v5 (latest)

Wasserstein-based fairness interpretability framework for machine learning models

6 November 2020
A. Miroshnikov
Konstandinos Kotsiopoulos
Ryan Franks
Arjun Ravi Kannan
    FAtt
ArXiv (abs)PDFHTML

Papers citing "Wasserstein-based fairness interpretability framework for machine learning models"

10 / 10 papers shown
From Fragile to Certified: Wasserstein Audits of Group Fairness Under Distribution Shift
From Fragile to Certified: Wasserstein Audits of Group Fairness Under Distribution Shift
A. Ehyaei
G. Farnadi
Samira Samadi
175
0
0
30 Sep 2025
Enforcing Fair Predicted Scores on Intervals of Percentiles by Difference-of-Convex Constraints
Enforcing Fair Predicted Scores on Intervals of Percentiles by Difference-of-Convex Constraints
Yutian He
Yankun Huang
Yao Yao
Qihang Lin
226
0
0
18 May 2025
Explainable post-training bias mitigation with distribution-based fairness metrics
Explainable post-training bias mitigation with distribution-based fairness metrics
Ryan Franks
A. Miroshnikov
Konstandinos Kotsiopoulos
484
0
0
01 Apr 2025
OT-Net: A Reusable Neural Optimal Transport Solver
OT-Net: A Reusable Neural Optimal Transport SolverMachine-mediated learning (ML), 2023
Zezeng Li
Shenghao Li
Lianbao Jin
Na Lei
Zhongxuan Luo
OT
259
5
0
14 Jun 2023
Retiring $Δ$DP: New Distribution-Level Metrics for Demographic
  Parity
Retiring ΔΔΔDP: New Distribution-Level Metrics for Demographic Parity
Xiaotian Han
Zhimeng Jiang
Hongye Jin
Zirui Liu
Na Zou
Qifan Wang
Helen Zhou
460
4
0
31 Jan 2023
AI Fairness: from Principles to Practice
AI Fairness: from Principles to Practice
A. Bateni
Matthew Chan
Ray Eitel-Porter
130
6
0
20 Jul 2022
Model-agnostic bias mitigation methods with regressor distribution
  control for Wasserstein-based fairness metrics
Model-agnostic bias mitigation methods with regressor distribution control for Wasserstein-based fairness metrics
A. Miroshnikov
Konstandinos Kotsiopoulos
Ryan Franks
Arjun Ravi Kannan
181
6
0
19 Nov 2021
FairCanary: Rapid Continuous Explainable Fairness
FairCanary: Rapid Continuous Explainable FairnessAAAI/ACM Conference on AI, Ethics, and Society (AIES), 2021
Avijit Ghosh
Aalok Shanbhag
Christo Wilson
355
26
0
13 Jun 2021
FiSH: Fair Spatial Hotspots
FiSH: Fair Spatial HotspotsData mining and knowledge discovery (DMKD), 2021
Deepak P
Sowmya S. Sundaram
327
1
0
01 Jun 2021
Unified Shapley Framework to Explain Prediction Drift
Unified Shapley Framework to Explain Prediction Drift
Aalok Shanbhag
A. Ghosh
Josh Rubin
FAttFedMLAI4TS
167
4
0
15 Feb 2021
1
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