Classifying without discriminating

Kamiran, Faisal, Calders, Toon·2009·2009 2nd International Conference on Computer, Control and Communication

Cited by (403)

Items 101–200 of 403

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  3. Conditional Learning of Fair Representations
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  4. Towards Fair Classifiers Without Sensitive Attributes
    Tianxiang Zhao, Enyan Dai, Kai Shu, Suhang Wang · 2022 · ACM International Conference on Web Search and Data Mining (WSDM)
  5. FairNeuron
    Xuanqi Gao, Juan Zhai, Shiqing Ma, Chao Qun Shen, Yufei Chen, Qian Wang · 2022 · ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)
  6. FairMask: Better Fairness via Model-Based Rebalancing of Protected Attributes
    Kewen Peng, Joymallya Chakraborty, Tim Menzies · 2022 · IEEE Transactions on Software Engineering
  7. Integrating induction and deduction for finding evidence of discrimination
    Salvatore Ruggieri, Dino Pedreschi, Franco Turini · 2010 · Artificial Intelligence and Law
  8. Proceedings of the First ACL Workshop on Ethics in Natural Language Processing
    2017
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    Depeng Xu, Wei Du, Xintao Wu · 2021 · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
  10. Aligning Eyes between Humans and Deep Neural Network through Interactive Attention Alignment
    Yuyang Gao, Tong Sun, Liang Zhao, Sung-Soo Hong · 2022 · Proceedings of the ACM on Human-Computer Interaction
  11. Techniques for Discrimination-Free Predictive Models
    Faisal Kamiran, Toon Calders, Mykola Pechenizkiy · 2012 · Studies in applied philosophy, epistemology and rational ethics
  12. Gradient Reversal against Discrimination: A Fair Neural Network Learning Approach
    Edward Raff, Jared Sylvester · 2018 · IEEE International Conference on Data Science and Advanced Analytics (DSAA)
  13. Efficient fair principal component analysis
    Mohammad Mahdi Kamani, Farzin Haddadpour, Rana Forsati, Mehrdad Mahdavi · 2022 · Machine Learning
  14. Towards Fair Truth Discovery from Biased Crowdsourced Answers
    Yanying Li, Haipei Sun, Hui Wang · 2020 · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
  15. Mitigating Unfairness via Evolutionary Multiobjective Ensemble Learning
    Qingquan Zhang, Jialin Liu, Zeqi Zhang, Junyi Wen, Bifei Mao, Xin Yao · 2022 · IEEE Transactions on Evolutionary Computation
  16. Longitudinal Fairness with Censorship
    Wenbin Zhang, Jeremy C. Weiss · 2022 · Proceedings of the AAAI Conference on Artificial Intelligence
  17. Situation testing-based discrimination discovery: a causal inference approach
    Lu Zhang, Yongkai Wu, Xintao Wu · 2016 · International Joint Conference on Artificial Intelligence
  18. On Generalized Degree Fairness in Graph Neural Networks
    Zemin Liu, Trung‐Kien Nguyen, Yuan Fang · 2023 · Proceedings of the AAAI Conference on Artificial Intelligence
  19. FairGAN+: Achieving Fair Data Generation and Classification through Generative Adversarial Nets
    Depeng Xu, Shuhan Yuan, Lu Zhang, Xintao Wu · 2019 · IEEE International Conference on Big Data (BigData)
  20. Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees
    L. Elisa Celis, Lingxiao Huang, Vijay Keswani, Nisheeth K. Vishnoi · 2018 · arXiv (Cornell University)
  21. Causal Fairness Analysis: A Causal Toolkit for Fair Machine Learning
    Drago Plečko, Elias Bareinboim · 2024 · Foundations and Trends® in Machine Learning
  22. A Unified Approach to Quantifying Algorithmic Unfairness
    Till Speicher, Hoda Heidari, Nina Grgić-Hlača, Krishna P. Gummadi, Adish Kumar Singla, Adrian Weller, Muhammad Bilal Zafar · 2018 · Apollo (University of Cambridge)
  23. Fairness-Enhancing Interventions in Stream Classification
    Vasileios Iosifidis, Thi Ngoc Han Tran, Eirini Ntoutsi · 2019 · Lecture notes in computer science
  24. General Fair Empirical Risk Minimization
    Luca Oneto, Michele Donini, Massimiliano Pontil · 2020 · International Joint Conference on Neural Networks (IJCNN)
  25. The Sensitivity of Counterfactual Fairness to Unmeasured Confounding
    Niki Kilbertus, Philip Ball, Matt J. Kusner, Adrian Weller, Ricardo Silva · 2019 · arXiv (Cornell University)
  26. Algorithmic decision making methods for fair credit scoring
    Moldovan, Darie · 2023 · IEEE Access
  27. Database Repair Meets Algorithmic Fairness
    Babak Salimi, Bill Howe, Dan Mircea Suciu · 2020 · ACM SIGMOD Record
  28. Fair Personalization
    L. Elisa Celis, Nisheeth K. Vishnoi · 2017 · arXiv (Cornell University)
  29. FairCF: fairness-aware collaborative filtering
    Pengyang Shao, Le Wu, Lei Chen, Kun Zhang, Meng Wang · 2022 · Science China Information Sciences
  30. Direct and Indirect Discrimination Prevention Methods
    Hajian, Sara, Domingo-Ferrer, Josep · 2013 · Studies in Applied Philosophy, Epistemology and Rational Ethics
  31. The Authors Matter: Understanding and Mitigating Implicit Bias in Deep Text Classification
    Haochen Liu, Wei Jin, Hamid Karimi, Zitao Liu, Jiliang Tang · 2021 · Findings of the Association for Computational Linguistics: ACL (Findings of ACL)
  32. Minimizing bias when using artificial intelligence in critical care medicine
    Benjamin L. Ranard, Soojin Park, Yugang Jia, Yiye Zhang, Fatima S. Alwan, Leo Anthony Celi, Elizabeth R. Lusczek · 2024 · Journal of Critical Care
  33. A General Framework for Fair Regression
    Jack Fitzsimons, AbdulRahman Al Ali, Michael Osborne, Stephen Roberts · 2019 · Entropy
  34. FAWOS: Fairness-Aware Oversampling Algorithm Based on Distributions of Sensitive Attributes
    Teresa Salazar, Miriam Seoane Santos, Helder Jesus Araújo, Pedro Henriques Abreu · 2021 · IEEE Access
  35. Integrating Behavioral, Economic, and Technical Insights to Address Algorithmic Bias: Challenges and Opportunities for IS Research
    Gediminas Adomavičius, Mochen Yang · 2019 · ACM Transactions on Management Information Systems
  36. Fair Decision-making Under Uncertainty
    Wenbin Zhang, Jeremy C. Weiss · 2021 · Proceedings
  37. Achieving Non-Discrimination in Prediction
    Lu Zhang, Yongkai Wu, Xintao Wu · 2018 · International Joint Conference on Artificial Intelligence
  38. The Impact of Data Preparation on the Fairness of Software Systems
    Inês Valentim, Nuno Lourenço, Nuno Antunes · 2019 · Proceedings/Proceedings - International Symposium on Software Reliability Engineering
  39. On Discrimination Discovery Using Causal Networks
    Lu Zhang, Yongkai Wu, Xintao Wu · 2016 · Lecture notes in computer science
  40. FAIM: Fairness-aware interpretable modeling for trustworthy machine learning in healthcare
    Mingxuan Liu, Yilin Ning, Yuhe Ke, Yuqing Shang, Bibhas Chakraborty, Marcus Eng Hock Ong, ROGER D. VAUGHAN, Nan Liu · 2024 · Patterns
  41. Accurate Fairness: Improving Individual Fairness without Trading Accuracy
    Xuran Li, Peng Wu, Jing Su · 2023 · Proceedings of the AAAI Conference on Artificial Intelligence
  42. Leave No Patient Behind: Enhancing Medication Recommendation for Rare Disease Patients
    Zihao Zhao, Yi Jing, Fuli Feng, Jiancan Wu, Chongming Gao, Xiangnan He · 2024 · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
  43. The Zoo of Fairness Metrics in Machine Learning
    Alessandro Castelnovo, Riccardo Crupi, Greta Greco, Daniele Regoli, Ilaria Giuseppina Penco, Andrea Claudio Cosentini · 2021 · Research Square
  44. Preventing Discriminatory Decision-making in Evolving Data Streams
    Zichong Wang, Nripsuta Ani Saxena, Tongjia Yu, Sneha Karki, Tyler Zetty, Israat Haque, Shan Zhou, Dukka B. KC, Ian Stockwell, Xuyu Wang et al. · 2023 · ACM Conference on Fairness, Accountability, and Transparency (FAccT)
  45. Fairness in Clustering with Multiple Sensitive Attributes
    Savitha Sam Abraham, P Deepak, Sowmya S. Sundaram · 2019 · arXiv (Cornell University)
  46. Proceedings of the 29th ACM International Conference on Information & Knowledge Management
    Ramanujam Madhavan, Mohit Wadhwa · 2020
  47. FNNC: Achieving Fairness through Neural Networks
    Manisha Padala, Sujit Gujar · 2018 · arXiv (Cornell University)
  48. The Externalities of Exploration and How Data Diversity Helps Exploitation
    Manish Raghavan · 2023 · ACM eBooks
  49. Bias on Demand: A Modelling Framework That Generates Synthetic Data With Bias
    Joachim Baumann, Alessandro Castelnovo, Riccardo Crupi, Nicole Inverardi, Daniele Regoli · 2023 · ACM Conference on Fairness, Accountability, and Transparency (FAccT)
  50. Discrimination-aware classification
    Faisal Kamiran · 2011
  51. Preprocessing to Address Bias in Healthcare Data
    Emel Seker, John R. Talburt, Melody Greer · 2022 · Studies in health technology and informatics
  52. Discovering Unwarranted Associations in Data-Driven Applications with the FairTest Testing Toolkit
    Florian Tramèr, Vaggelis Atlidakis, Roxana Geambasu, Daniel Hsu, Jean‐Pierre Hubaux, Mathias Humbert, Ari Juels, Lin Huang · 2015 · arXiv (Cornell University)
  53. Rényi Fair Inference
    Sina Baharlouei, Maher Nouiehed, Ahmad Beirami, Meisam Razaviyayn · 2019 · arXiv (Cornell University)
  54. Exposing and Correcting the Gender Bias in Image Captioning Datasets and Models
    Bhargava, Shruti, David Alexander Forsyth · 2019 · arXiv (Cornell University)
  55. BeFair: Addressing Fairness in the Banking Sector
    Alessandro Castelnovo, Riccardo Crupi, Giulia Del Gamba, Greta Greco, Aisha Naseer, Daniele Regoli, Beatriz San Miguel González · 2020 · IEEE International Conference on Big Data (BigData)
  56. Investigating Oversampling Techniques for Fair Machine Learning Models
    Sanja Rančić, Sandro Radovanović, Boris Delibašić · 2021 · Lecture notes in business information processing
  57. Non-Discriminatory Machine Learning Through Convex Fairness Criteria
    Naman Goel, Mohammad Yaghini, Boi V. Faltings · 2018 · Proceedings of the AAAI Conference on Artificial Intelligence
  58. Selection Problems in the Presence of Implicit Bias
    Manish Raghavan · 2023 · ACM eBooks
  59. Removing the Influence of Group Variables in High-Dimensional Predictive Modelling
    Emanuele Aliverti, Kristian Lum, James E. Johndrow, David B. Dunson · 2021 · Journal of the Royal Statistical Society Series A (Statistics in Society)
  60. Classifying Socially Sensitive Data Without Discrimination: An Analysis of a Crime Suspect Dataset
    Faisal Kamiran, Asim Karim, Sicco Verwer, Heike Goudriaan · 2012 · IEEE ... International Conference on Data Mining workshops
  61. Local data debiasing for fairness based on generative adversarial training.
    Aïvodji, Ulrich, Bidet, François, Gambs, Sébastien, Ngueveu, Rosin Claude, Tapp, Alain · 2021 · Algorithms
  62. Search results diversification for effective fair ranking in academic search
    Graham McDonald, Craig Macdonald, Iadh Ounis · 2021 · Information Retrieval
  63. Did You Do Your Homework? Raising Awareness on Software Fairness and Discrimination
    Max Hort, Federica Sarro · 2021 · IEEE/ACM International Conference on Automated Software Engineering (ASE)
  64. FFTree: A flexible tree to handle multiple fairness criteria
    Alessandro Castelnovo, Andrea Cosentini, Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica · 2022 · Information Processing & Management
  65. Enforcing fairness in logistic regression algorithm
    Sandro Radovanović, Andrija Petrović, Boris Delibašić, Milija Suknović · 2020 · International Conference on Innovations in Intelligent Systems and Applications (INISTA)
  66. FEAT: A Fairness-Enhancing and Concept-Adapting Decision Tree Classifier
    Wenbin Zhang, Albert Bifet · 2020 · Lecture notes in computer science
  67. Influence in Classification via Cooperative Game Theory
    Amit Jyoti Datta, Anupam Datta, Ariel D. Procaccia, Yair Zick · 2015 · arXiv (Cornell University)
  68. Review of Mathematical frameworks for Fairness in Machine Learning
    Eustasio del Barrio, Paula Gordaliza, Jean–Michel Loubes · 2020 · arXiv (Cornell University)
  69. Individual Fairness Under Uncertainty
    Wenbin Zhang, Zichong Wang, Ju-Yong Kim, Cheng Cheng, Thomas Oommen, Pradeep Ravikumar, Jeremy Weiss · 2023 · Frontiers in artificial intelligence and applications
  70. Improving Academic Advising in Engineering Education with Machine Learning Using a Real-World Dataset
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  71. Fairness of Classification Using Users’ Social Relationships in Online Peer-To-Peer Lending
    Yanying Li, Yue Ning, Rong Liu, Ying Wu, Hui Wang · 2020 · International World Wide Web Conference (WWW)
  72. Discrimination Data Analysis: A Multi-disciplinary Bibliography
    Andrea Romei, Salvatore Ruggieri · 2012 · Studies in applied philosophy, epistemology and rational ethics
  73. Measuring Unfairness Through Game-Theoretic Interpretability
    Juliana Cesaro, Fábio Gagliardi Cozman · 2020 · Communications in computer and information science
  74. Comprehensive Validation on Reweighting Samples for Bias Mitigation via AIF360
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  75. Towards Fairness Through Time
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  76. Kernel dependence regularizers and Gaussian processes with applications to algorithmic fairness
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  77. Fair Classification with Adversarial Perturbations
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  78. From Transparency to Accountability and Back: A Discussion of Access and Evidence in AI Auditing
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  79. Search-based Automatic Repair for Fairness and Accuracy in Decision-making Software
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  80. Fairer Machine Learning Through Multi-objective Evolutionary Learning
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  81. Almost politically acceptable criminal justice risk assessment
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  82. Fairness with censorship and group constraints
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  83. On Explaining Unfairness: An Overview
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  84. Randomized learning and generalization of fair and private classifiers: From PAC-Bayes to stability and differential privacy
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  85. On Fairness-Aware Learning for Non-discriminative Decision-Making
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  86. Flexible and Adaptive Fairness-aware Learning in Non-stationary Data Streams
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  87. Coverage-Guided Fairness Testing
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  88. Fair Classification with Noisy Protected Attributes: A Framework with Provable Guarantees
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  89. Fairness and Discrimination in Information Access Systems
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  90. A Near-Optimal Algorithm for Debiasing Trained Machine Learning Models
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  91. Unveiling Accuracy-Fairness Trade-Offs
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  93. Properties of Fairness Measures in the Context of Varying Class Imbalance and Protected Group Ratios
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  97. Capuchin: Causal Database Repair for Algorithmic Fairness
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  98. Privacy for All: Demystify Vulnerability Disparity of Differential Privacy against Membership Inference Attack
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  99. Wasserstein-based fairness interpretability framework for machine learning models
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