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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- Integrating induction and deduction for finding evidence of discriminationSalvatore Ruggieri, Dino Pedreschi, Franco Turini · 2010 · Artificial Intelligence and Law
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- Techniques for Discrimination-Free Predictive ModelsFaisal Kamiran, Toon Calders, Mykola Pechenizkiy · 2012 · Studies in applied philosophy, epistemology and rational ethics
- Gradient Reversal against Discrimination: A Fair Neural Network Learning ApproachEdward Raff, Jared Sylvester · 2018 · IEEE International Conference on Data Science and Advanced Analytics (DSAA)
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- Longitudinal Fairness with CensorshipWenbin Zhang, Jeremy C. Weiss · 2022 · Proceedings of the AAAI Conference on Artificial Intelligence
- Situation testing-based discrimination discovery: a causal inference approachLu Zhang, Yongkai Wu, Xintao Wu · 2016 · International Joint Conference on Artificial Intelligence
- On Generalized Degree Fairness in Graph Neural NetworksZemin Liu, Trung‐Kien Nguyen, Yuan Fang · 2023 · Proceedings of the AAAI Conference on Artificial Intelligence
- FairGAN+: Achieving Fair Data Generation and Classification through Generative Adversarial NetsDepeng Xu, Shuhan Yuan, Lu Zhang, Xintao Wu · 2019 · IEEE International Conference on Big Data (BigData)
- Classification with Fairness Constraints: A Meta-Algorithm with Provable GuaranteesL. Elisa Celis, Lingxiao Huang, Vijay Keswani, Nisheeth K. Vishnoi · 2018 · arXiv (Cornell University)
- Causal Fairness Analysis: A Causal Toolkit for Fair Machine LearningDrago Plečko, Elias Bareinboim · 2024 · Foundations and Trends® in Machine Learning
- A Unified Approach to Quantifying Algorithmic UnfairnessTill Speicher, Hoda Heidari, Nina Grgić-Hlača, Krishna P. Gummadi, Adish Kumar Singla, Adrian Weller, Muhammad Bilal Zafar · 2018 · Apollo (University of Cambridge)
- Fairness-Enhancing Interventions in Stream ClassificationVasileios Iosifidis, Thi Ngoc Han Tran, Eirini Ntoutsi · 2019 · Lecture notes in computer science
- General Fair Empirical Risk MinimizationLuca Oneto, Michele Donini, Massimiliano Pontil · 2020 · International Joint Conference on Neural Networks (IJCNN)
- The Sensitivity of Counterfactual Fairness to Unmeasured ConfoundingNiki Kilbertus, Philip Ball, Matt J. Kusner, Adrian Weller, Ricardo Silva · 2019 · arXiv (Cornell University)
- Algorithmic decision making methods for fair credit scoringMoldovan, Darie · 2023 · IEEE Access
- Database Repair Meets Algorithmic FairnessBabak Salimi, Bill Howe, Dan Mircea Suciu · 2020 · ACM SIGMOD Record
- Fair PersonalizationL. Elisa Celis, Nisheeth K. Vishnoi · 2017 · arXiv (Cornell University)
- FairCF: fairness-aware collaborative filteringPengyang Shao, Le Wu, Lei Chen, Kun Zhang, Meng Wang · 2022 · Science China Information Sciences
- Direct and Indirect Discrimination Prevention MethodsHajian, Sara, Domingo-Ferrer, Josep · 2013 · Studies in Applied Philosophy, Epistemology and Rational Ethics
- The Authors Matter: Understanding and Mitigating Implicit Bias in Deep Text ClassificationHaochen Liu, Wei Jin, Hamid Karimi, Zitao Liu, Jiliang Tang · 2021 · Findings of the Association for Computational Linguistics: ACL (Findings of ACL)
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- The Impact of Data Preparation on the Fairness of Software SystemsInês Valentim, Nuno Lourenço, Nuno Antunes · 2019 · Proceedings/Proceedings - International Symposium on Software Reliability Engineering
- On Discrimination Discovery Using Causal NetworksLu Zhang, Yongkai Wu, Xintao Wu · 2016 · Lecture notes in computer science
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- The Zoo of Fairness Metrics in Machine LearningAlessandro Castelnovo, Riccardo Crupi, Greta Greco, Daniele Regoli, Ilaria Giuseppina Penco, Andrea Claudio Cosentini · 2021 · Research Square
- Preventing Discriminatory Decision-making in Evolving Data StreamsZichong 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)
- Fairness in Clustering with Multiple Sensitive AttributesSavitha Sam Abraham, P Deepak, Sowmya S. Sundaram · 2019 · arXiv (Cornell University)
- Proceedings of the 29th ACM International Conference on Information & Knowledge ManagementRamanujam Madhavan, Mohit Wadhwa · 2020
- FNNC: Achieving Fairness through Neural NetworksManisha Padala, Sujit Gujar · 2018 · arXiv (Cornell University)
- The Externalities of Exploration and How Data Diversity Helps ExploitationManish Raghavan · 2023 · ACM eBooks
- Bias on Demand: A Modelling Framework That Generates Synthetic Data With BiasJoachim Baumann, Alessandro Castelnovo, Riccardo Crupi, Nicole Inverardi, Daniele Regoli · 2023 · ACM Conference on Fairness, Accountability, and Transparency (FAccT)
- Discrimination-aware classificationFaisal Kamiran · 2011
- Preprocessing to Address Bias in Healthcare DataEmel Seker, John R. Talburt, Melody Greer · 2022 · Studies in health technology and informatics
- Discovering Unwarranted Associations in Data-Driven Applications with the FairTest Testing ToolkitFlorian Tramèr, Vaggelis Atlidakis, Roxana Geambasu, Daniel Hsu, Jean‐Pierre Hubaux, Mathias Humbert, Ari Juels, Lin Huang · 2015 · arXiv (Cornell University)
- Rényi Fair InferenceSina Baharlouei, Maher Nouiehed, Ahmad Beirami, Meisam Razaviyayn · 2019 · arXiv (Cornell University)
- Exposing and Correcting the Gender Bias in Image Captioning Datasets and ModelsBhargava, Shruti, David Alexander Forsyth · 2019 · arXiv (Cornell University)
- BeFair: Addressing Fairness in the Banking SectorAlessandro Castelnovo, Riccardo Crupi, Giulia Del Gamba, Greta Greco, Aisha Naseer, Daniele Regoli, Beatriz San Miguel González · 2020 · IEEE International Conference on Big Data (BigData)
- Investigating Oversampling Techniques for Fair Machine Learning ModelsSanja Rančić, Sandro Radovanović, Boris Delibašić · 2021 · Lecture notes in business information processing
- Non-Discriminatory Machine Learning Through Convex Fairness CriteriaNaman Goel, Mohammad Yaghini, Boi V. Faltings · 2018 · Proceedings of the AAAI Conference on Artificial Intelligence
- Selection Problems in the Presence of Implicit BiasManish Raghavan · 2023 · ACM eBooks
- Removing the Influence of Group Variables in High-Dimensional Predictive ModellingEmanuele Aliverti, Kristian Lum, James E. Johndrow, David B. Dunson · 2021 · Journal of the Royal Statistical Society Series A (Statistics in Society)
- Classifying Socially Sensitive Data Without Discrimination: An Analysis of a Crime Suspect DatasetFaisal Kamiran, Asim Karim, Sicco Verwer, Heike Goudriaan · 2012 · IEEE ... International Conference on Data Mining workshops
- Local data debiasing for fairness based on generative adversarial training.Aïvodji, Ulrich, Bidet, François, Gambs, Sébastien, Ngueveu, Rosin Claude, Tapp, Alain · 2021 · Algorithms
- Search results diversification for effective fair ranking in academic searchGraham McDonald, Craig Macdonald, Iadh Ounis · 2021 · Information Retrieval
- Did You Do Your Homework? Raising Awareness on Software Fairness and DiscriminationMax Hort, Federica Sarro · 2021 · IEEE/ACM International Conference on Automated Software Engineering (ASE)
- FFTree: A flexible tree to handle multiple fairness criteriaAlessandro Castelnovo, Andrea Cosentini, Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica · 2022 · Information Processing & Management
- Enforcing fairness in logistic regression algorithmSandro Radovanović, Andrija Petrović, Boris Delibašić, Milija Suknović · 2020 · International Conference on Innovations in Intelligent Systems and Applications (INISTA)
- FEAT: A Fairness-Enhancing and Concept-Adapting Decision Tree ClassifierWenbin Zhang, Albert Bifet · 2020 · Lecture notes in computer science
- Influence in Classification via Cooperative Game TheoryAmit Jyoti Datta, Anupam Datta, Ariel D. Procaccia, Yair Zick · 2015 · arXiv (Cornell University)
- Review of Mathematical frameworks for Fairness in Machine LearningEustasio del Barrio, Paula Gordaliza, Jean–Michel Loubes · 2020 · arXiv (Cornell University)
- Individual Fairness Under UncertaintyWenbin Zhang, Zichong Wang, Ju-Yong Kim, Cheng Cheng, Thomas Oommen, Pradeep Ravikumar, Jeremy Weiss · 2023 · Frontiers in artificial intelligence and applications
- Improving Academic Advising in Engineering Education with Machine Learning Using a Real-World DatasetMfowabo Maphosa, Wesley Doorsamy, Babu Sean Paul · 2024 · Algorithms
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- Discrimination Data Analysis: A Multi-disciplinary BibliographyAndrea Romei, Salvatore Ruggieri · 2012 · Studies in applied philosophy, epistemology and rational ethics
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- Fair Classification with Adversarial PerturbationsL. Elisa Celis, Anay Mehrotra, Nisheeth K. Vishnoi · 2021 · arXiv (Cornell University)
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- Coverage-Guided Fairness TestingDaniel Perez Morales, Takashi Kitamura, Shingo Takada · 2021 · Studies in computational intelligence
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- Fairness and Discrimination in Information Access SystemsMichael D. Ekstrand, Anubrata Das, Robin Burke, Fernando Díaz · 2021 · arXiv (Cornell University)
- A Near-Optimal Algorithm for Debiasing Trained Machine Learning ModelsIbrahim Alabdulmohsin, Mario Lučić · 2021 · arXiv (Cornell University)
- Unveiling Accuracy-Fairness Trade-OffsRaymond A. Opoku, Bo Pei, Wanli Xing · 2025 · Journal of Learning Analytics
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