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Through the Data Management Lens: Experimental Analysis and Evaluation
  of Fair Classification
v1v2v3v4 (latest)

Through the Data Management Lens: Experimental Analysis and Evaluation of Fair Classification

18 January 2021
Maliha Tashfia Islam
Anna Fariha
A. Meliou
Babak Salimi
    FaML
ArXiv (abs)PDFHTML

Papers citing "Through the Data Management Lens: Experimental Analysis and Evaluation of Fair Classification"

11 / 11 papers shown
Title
CausalPre: Scalable and Effective Data Pre-processing for Causal Fairness
CausalPre: Scalable and Effective Data Pre-processing for Causal Fairness
Ying Zheng
Yangfan Jiang
Kian-Lee Tan
68
0
0
18 Sep 2025
Stress-Testing ML Pipelines with Adversarial Data Corruption
Stress-Testing ML Pipelines with Adversarial Data CorruptionProceedings of the VLDB Endowment (PVLDB), 2025
Jiongli Zhu
Geyang Xu
Felipe Lorenzi
Boris Glavic
Babak Salimi
187
0
0
02 Jun 2025
Is it Still Fair? A Comparative Evaluation of Fairness Algorithms
  through the Lens of Covariate Drift
Is it Still Fair? A Comparative Evaluation of Fairness Algorithms through the Lens of Covariate DriftMachine-mediated learning (ML), 2024
Oscar Blessed Deho
Michael Bewong
Selasi Kwashie
Jiuyong Li
Jixue Liu
Lin Liu
Srecko Joksimovic
FaML
236
0
0
19 Sep 2024
Enforcing Conditional Independence for Fair Representation Learning and
  Causal Image Generation
Enforcing Conditional Independence for Fair Representation Learning and Causal Image Generation
Jensen Hwa
Qingyu Zhao
Aditya Lahiri
Adnan Masood
Babak Salimi
Ehsan Adeli
OODCML
123
4
0
21 Apr 2024
OTClean: Data Cleaning for Conditional Independence Violations using
  Optimal Transport
OTClean: Data Cleaning for Conditional Independence Violations using Optimal Transport
Alireza Pirhadi
Mohammad Hossein Moslemi
Alexander Cloninger
Mostafa Milani
Babak Salimi
131
12
0
04 Mar 2024
Adaptive Boosting with Fairness-aware Reweighting Technique for Fair
  Classification
Adaptive Boosting with Fairness-aware Reweighting Technique for Fair Classification
Xiaobin Song
Zeyuan Liu
Benben Jiang
FaML
125
5
0
06 Jan 2024
How Far Can Fairness Constraints Help Recover From Biased Data?
How Far Can Fairness Constraints Help Recover From Biased Data?International Conference on Machine Learning (ICML), 2023
Mohit Sharma
Amit Deshpande
FaML
220
5
0
16 Dec 2023
Explainable Disparity Compensation for Efficient Fair Ranking
Explainable Disparity Compensation for Efficient Fair RankingIEEE International Conference on Data Engineering (ICDE), 2023
A. Gale
A. Marian
107
0
0
25 Jul 2023
Non-Invasive Fairness in Learning through the Lens of Data Drift
Non-Invasive Fairness in Learning through the Lens of Data DriftIEEE International Conference on Data Engineering (ICDE), 2023
Ke Yang
A. Meliou
219
1
0
30 Mar 2023
On Comparing Fair Classifiers under Data Bias
On Comparing Fair Classifiers under Data Bias
Mohit Sharma
Amit Deshpande
R. Shah
266
2
0
12 Feb 2023
Consistent Range Approximation for Fair Predictive Modeling
Consistent Range Approximation for Fair Predictive ModelingProceedings of the VLDB Endowment (PVLDB), 2022
Jiongli Zhu
Sainyam Galhotra
Nazanin Sabri
Babak Salimi
185
13
0
21 Dec 2022
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