Interventional Fairness: Causal Database Repair for Algorithmic Fairness

Salimi, Babak, Rodriguez, Luke, Howe, Bill, Suciu, Dan·2019·Proceedings of the 2019 International Conference on Management of Data

Cited by (146)

Items 101–146 of 146

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    Sainyam Galhotra, Karthikeyan Shanmugam, Prasanna Sattigeri, Kush R. Varshney · 2020 · arXiv (Cornell University)
  2. Approximation and inapproximability results on computing optimal repairs
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  3. Fair and Actionable Causal Prescription Ruleset
    Benton Li, Nativ Levy, Brit Youngmann, Sainyam Galhotra, Sudeepa Roy · 2025 · Proceedings of the ACM on Management of Data
  4. RAGUEL
    Aparajita Haldar, Teddy Cunningham, Hakan Ferhatosmanoğlu · 2022 · ACM International Conference on Information and Knowledge Management (CIKM)
  5. A Framework to Maximize Group Fairness for Workers on Online Labor Platforms
    Anis El Rabaa, Shady Elbassuoni, Jihad Hanna, Amer E. Mouawad, Ayham Olleik, Sihem Amer-Yahia · 2023 · Data Science and Engineering
  6. Falcon: Fair Active Learning Using Multi-Armed Bandits
    Ki Hyun Tae, Hantian Zhang, Jaeyoung Park, Kexin Rong, Steven Euijong Whang · 2024 · Proceedings of the VLDB Endowment
  7. Sensitivity Analysis: Improving Inclusive Credit Scoring Algorithm Through Feature Weight and Penalty-Based Approach
    Reni Sulastri, Aaron Yi Ding, Marijn Janssen · 2025 · International Conference on eDemocracy & eGovernment
  8. Towards Fairness Certification in Artificial Intelligence
    Tatiana Tommasi, Silvia Bucci, Barbara Caputo B, Pietro Asinari · 2021 · arXiv (Cornell University)
  9. FairHash: A Fair and Memory/Time-efficient Hashmap
    Nima Shahbazi, Stavros Sintos, Abolfazl Asudeh · 2024 · Proceedings of the ACM on Management of Data
  10. Reliability evaluation of individual predictions: a data-centric approach
    Nima Shahbazi, Abolfazl Asudeh · 2024 · The VLDB Journal
  11. Causal DAG Summarization
    Anna Zeng, Michael Cafarella, Batya Kenig, Markos Markakis, Brit Youngmann, Babak Salimi · 2025 · Proceedings of the VLDB Endowment
  12. Non-Invasive Fairness in Learning Through the Lens of Data Drift
    Ke Yang, Alexandra Meliou · 2024 · IEEE International Conference on Data Engineering (ICDE)
  13. Enforcing Conditional Independence for Fair Representation Learning and Causal Image Generation
    Jensen Hwa, Qingyu Zhao, Aditya Lahiri, Adnan Masood, Babak Salimi, Ehsan Adeli · 2024 · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
  14. Towards fair AI: a review of bias and fairness in machine intelligence
    Venkatesha Kurumayya · 2025 · Journal of Computational Social Science
  15. Is Integer Linear Programming All You Need for Deletion Propagation? A Unified and Practical Approach for Generalized Deletion Propagation
    Neha Makhija, Wolfgang Gatterbauer · 2025 · Proceedings of the VLDB Endowment
  16. Attempt to Better Trust Classification Models: Application to the Ageing of Refrigerated Transport Vehicles
    Marie Le Guilly, C Capo, Jean-Marc Petit, Vasile-Marian Scuturici, Rémi Revellin, Jocelyn Bonjour, G Cavalier · 2021 · Studies in computational intelligence
  17. Quantification of Racial Disparity on Urinary Tract Infection Recurrence and Treatment Resistance in Florida using Algorithmic Fairness Methods
    Inyoung Jun, Sarah E Ser, Jie Xu, Jiang Bian, Mattia Prosperi · 2023 · IEEE International Conference on Healthcare Informatics (ICHI)
  18. Explainable Disparity Compensation for Efficient Fair Ranking
    Abraham Gale, Amélie Marian · 2024 · IEEE International Conference on Data Engineering (ICDE)
  19. The Cost of Representation by Subset Repairs
    Yu-xi Liu, Fangzhu Shen, Kushagra Ghosh, Amir Gilad, Benny Kimelfeld, Sudeepa Roy · 2024 · Proceedings of the VLDB Endowment
  20. SynthFair: Ensuring Subgroup Fairness in Classification via Synthetic Data Generation
    Begüm Hattatoğlu, Abdulhakim A. Qahtan, Heysem Kaya, Yannis Velegrakis · 2025 · Communications in computer and information science
  21. The Fair Game: Auditing & debiasing AI algorithms over time
    Debabrota Basu, Udvas Das · 2025 · Cambridge Forum on AI Law and Governance
  22. A Sociotechnical View of Algorithmic Fairness
    Mateusz Dolata, Stefan Feuerriegel, Gerhard Schwabe · 2021 · Zurich Open Repository and Archive (University of Zurich)
  23. AMAT-Net: An Unbiased Network with High Performance for Metabolic Diseases Prediction Using Facial Images
    Fajin Feng, Kai Wang, Xiaohong Liu, Qifeng Gu, Guangyu Wang · 2022 · IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
  24. Adversarial Learning of Group and Individual Fair Representations
    Hao Liu, Raymond Chi-Wing Wong · 2024 · Lecture notes in computer science
  25. Fair Top-k Query on Alpha-Fairness
    Hao Liu, Raymond Chi-Wing Wong, Zheng Zhang, Min Xie, Bo Tang · 2024 · IEEE International Conference on Data Engineering (ICDE)
  26. LAGOON: Achieving bounded individual fairness through classification frequency equalization
    Maria L. M. Silva, Iago Chaves, Javam C. Machado · 2024 · Journal of the Brazilian Computer Society
  27. Complexity and Efficient Algorithms for Data Inconsistency Evaluating and Repairing
    Dongjing Miao, Zhipeng Cai, Jianzhong Li, Xiangyu Gao, Xianmin Liu · 2020 · arXiv (Cornell University)
  28. DataExposer: Exposing Disconnect between Data and Systems
    Sainyam Galhotra, Anna Fariha, Raoni Lourenço, Juliana Freire, Alexandra Meliou, Divesh Srivastava · 2021 · arXiv (Cornell University)
  29. An Information-Theoretic Measure for Enabling Category Exemptions with an Application to Filter Bubbles
    Chenyu Jiang, Bowen Wu, Sanghamitra Dutta, Pulkit Grover · 2021 · Communications in computer and information science
  30. Testing, Debugging, and Repairing Individual Discrimination in Machine Learning Models
    Diptikalyan Saha, Aniya Agarwal, Sandeep Hans, Swagatam Haldar · 2023 · Studies in computational intelligence
  31. Adaptive Boosting with Fairness-Aware Reweighting Technique for Fair Classification
    Xiaobin Song, Zeyuan Liu, Benson Jiang · 2024 · SSRN Electronic Journal
  32. Heart condition monitoring system using IoT
    Meilia Nur Indah Susanti, Indrianto Indrianto, Abdurrasyid Abdurrasyid · 2024 · AIP conference proceedings
  33. Fair Latent Representation Learning with Adaptive Reweighing
    Puspita Majumdar, Raghav Sharan Sharma, Rohit Bhattacharya, Balraj Prajesh · 2024 · Lecture notes in computer science
  34. Automated Data Bias Mitigation Technique for Algorithmic Fairness
    Jia Ming Shi, Chuitian Rong · 2025 · The European Journal on Artificial Intelligence
  35. CausaLens: A System for Summarizing Causal DAGs
    Noam Chen, Anna Zeng, Michael Cafarella, Batya Kenig, Markos Markakis, Oren Mishali, Brit Youngmann, Babak Salimi · 2025 · ACM SIGMOD International Conference on Management of Data (SIGMOD)
  36. From fair graphs to fair data: a DAG-based approach to mitigating bias in AI systems
    Vivian Wei Jiang, Gustavo Batista, Michael Bain · 2026 · Knowledge and Information Systems
  37. SAFES: Sequential Privacy and Fairness Enhancing Data Synthesis for Responsible AI
    Spencer Giddens, Xiaoan Lang, Fang Liu · 2025 · ACM transactions on probabilistic machine learning.
  38. Guided data selection for predictive models
    Marie Le Guilly · 2020 · theses.fr (ABES)
  39. Hybrid processing for algorithmic fairness
    Guilherme Alves da Silva · 2022 · theses.fr (ABES)
  40. Analyzing Deviations from Monotonic Trends through Database Repair
    Shunit Agmon, Jonathan Gal, Amir Gilad, Ester Livshits, Or Mutay, Brit Youngmann, Benny Kimelfeld · 2026 · Proceedings of the ACM on Management of Data
  41. Approximating Optimal Soft Repairs for Denial Constraints
    Zizheng Guo, Pengyu Chen, Jianwei Yang, Dongjing Miao · 2026 · IEEE Transactions on Knowledge and Data Engineering
  42. F air -C ount -M in : Frequency Estimation under Equal Group-wise Approximation Factor
    Nima Shahbazi, Stavros Sintos, Abolfazl Asudeh · 2026 · Proceedings of the ACM on Management of Data
  43. Structure Selection for Fairness-Constrained Differentially Private Data Synthesis
    Naeim Ghahramanpour, Mostafa Milani · 2026 · IEEE International Conference on Data Engineering Workshops (ICDEW)
  44. A Survey of Causal Learning in Graph-Based Recommender Systems
    Dianer Yu, Qian Li, Balamurugan Soundararaj, Christopher James Pettit, Guandong Xu · 2026 · ACM Computing Surveys
  45. SubCure: A System for Stress-Testing Causal Conclusions Using Cardinality Repairs
    Shira Raviv, Ben Hechler, Yarden Gabbay, Haoquan Guan, Shaull Almagor, El Kindi Rezig, Brit Youngmann, Babak Salimi · 2026 · Proceedings of the VLDB Endowment
  46. A Survey on Multisided Fairness in Recommender Systems
    Reza Shafiloo, Maria Stratigi, Kostas Stefanidis · 2026 · Lecture notes in computer science