Fairness in Machine Learning: A Survey

4 October 2020

Papers citing "Fairness in Machine Learning: A Survey"

45 / 95 papers shown

Title
Fairness Increases Adversarial Vulnerability Cuong Tran Keyu Zhu Ferdinando Fioretto Pascal Van Hentenryck 31 6 0 21 Nov 2022
Practical Approaches for Fair Learning with Multitype and Multivariate Sensitive Attributes Tennison Liu Alex J. Chan B. V. Breugel M. Schaar FaML 25 2 0 11 Nov 2022
Mitigating Unfairness via Evolutionary Multi-objective Ensemble Learning Qingquan Zhang Jialin Liu Zeqi Zhang J. Wen Bifei Mao Xin Yao FaML 45 17 0 30 Oct 2022
Differential Privacy has Bounded Impact on Fairness in Classification Paul Mangold Michaël Perrot A. Bellet Marc Tommasi 26 17 0 28 Oct 2022
Private and Reliable Neural Network Inference Nikola Jovanović Marc Fischer Samuel Steffen Martin Vechev 19 14 0 27 Oct 2022
Group Fairness in Prediction-Based Decision Making: From Moral Assessment to Implementation Joachim Baumann Christoph Heitz 31 8 0 19 Oct 2022
FAIR-FATE: Fair Federated Learning with Momentum Teresa Salazar Miguel X. Fernandes Helder Araújo Pedro Abreu FedML 38 18 0 27 Sep 2022
Explainable Global Fairness Verification of Tree-Based Classifiers Stefano Calzavara Lorenzo Cazzaro Claudio Lucchese Federico Marcuzzi 24 2 0 27 Sep 2022
Fairness Reprogramming Guanhua Zhang Yihua Zhang Yang Zhang Wenqi Fan Qing Li Sijia Liu Shiyu Chang AAML 83 38 0 21 Sep 2022
Exploiting Fairness to Enhance Sensitive Attributes Reconstruction Julien Ferry Ulrich Aïvodji Sébastien Gambs Marie-José Huguet Mohamed Siala AAML 34 14 0 02 Sep 2022
Prisoners of Their Own Devices: How Models Induce Data Bias in Performative Prediction José P. Pombal Pedro Saleiro Mário A. T. Figueiredo P. Bizarro 26 4 0 27 Jun 2022
Transferring Fairness under Distribution Shifts via Fair Consistency Regularization Bang An Zora Che Mucong Ding Furong Huang 14 31 0 26 Jun 2022
Experts' View on Challenges and Needs for Fairness in Artificial Intelligence for Education Gianni Fenu Roberta Galici Mirko Marras 33 17 0 23 Jun 2022
FairGrad: Fairness Aware Gradient Descent Gaurav Maheshwari Michaël Perrot FaML 36 11 0 22 Jun 2022
ABCinML: Anticipatory Bias Correction in Machine Learning Applications Abdulaziz A. Almuzaini C. Bhatt David M. Pennock V. Singh FaML 27 10 0 14 Jun 2022
Challenges in Applying Explainability Methods to Improve the Fairness of NLP Models Esma Balkir S. Kiritchenko I. Nejadgholi Kathleen C. Fraser 21 36 0 08 Jun 2022
Pruning has a disparate impact on model accuracy Cuong Tran Ferdinando Fioretto Jung-Eun Kim Rakshit Naidu 39 38 0 26 May 2022
Accurate Fairness: Improving Individual Fairness without Trading Accuracy Xuran Li Peng Wu Jing Su FaML 33 17 0 18 May 2022
"There Is Not Enough Information": On the Effects of Explanations on Perceptions of Informational Fairness and Trustworthiness in Automated Decision-Making Jakob Schoeffer Niklas Kuehl Yvette Machowski FaML 28 52 0 11 May 2022
User Guide for KOTE: Korean Online Comments Emotions Dataset Duyoung Jeon Junho Lee Cheongtag Kim 31 0 0 11 May 2022
The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations Aparna Balagopalan Haoran Zhang Kimia Hamidieh Thomas Hartvigsen Frank Rudzicz Marzyeh Ghassemi 38 78 0 06 May 2022
Rethinking Fairness: An Interdisciplinary Survey of Critiques of Hegemonic ML Fairness Approaches Lindsay Weinberg FaML SyDa 26 58 0 06 May 2022
Neural Contrastive Clustering: Fully Unsupervised Bias Reduction for Sentiment Classification Jared Mowery SSL 20 0 0 22 Apr 2022
Fairness in Graph Mining: A Survey Yushun Dong Jing Ma Song Wang Chen Chen Jundong Li FaML 34 112 0 21 Apr 2022
CPFair: Personalized Consumer and Producer Fairness Re-ranking for Recommender Systems Mohammadmehdi Naghiaei Hossein A. Rahmani Yashar Deldjoo FaML 31 93 0 17 Apr 2022
FairNeuron: Improving Deep Neural Network Fairness with Adversary Games on Selective Neurons Xuanqi Gao Juan Zhai Shiqing Ma Chao Shen Yufei Chen Qianqian Wang 31 37 0 06 Apr 2022
Achieving Long-Term Fairness in Sequential Decision Making Yaowei Hu Lu Zhang 23 20 0 04 Apr 2022
AUC Maximization in the Era of Big Data and AI: A Survey Tianbao Yang Yiming Ying 35 179 0 28 Mar 2022
Bayes-Optimal Classifiers under Group Fairness Xianli Zeng Yan Sun Guang Cheng FaML 21 22 0 20 Feb 2022
On Learning and Enforcing Latent Assessment Models using Binary Feedback from Human Auditors Regarding Black-Box Classifiers Mukund Telukunta Venkata Sriram Siddhardh Nadendla MLAU FaML 20 0 0 16 Feb 2022
Doing Right by Not Doing Wrong in Human-Robot Collaboration Laura Londoño Adrian Rofer Tim Welschehold Abhinav Valada 6 4 0 05 Feb 2022
Learning Optimal Predictive Checklists Haoran Zhang Q. Morris Berk Ustun Marzyeh Ghassemi 26 11 0 02 Dec 2021
Deep AUC Maximization for Medical Image Classification: Challenges and Opportunities Tianbao Yang 30 3 0 01 Nov 2021
Trustworthy AI: From Principles to Practices Bo-wen Li Peng Qi Bo Liu Shuai Di Jingen Liu Jiquan Pei Jinfeng Yi Bowen Zhou 119 355 0 04 Oct 2021
How to avoid machine learning pitfalls: a guide for academic researchers M. Lones VLM FaML OnRL 62 77 0 05 Aug 2021
Trustworthy AI: A Computational Perspective Haochen Liu Yiqi Wang Wenqi Fan Xiaorui Liu Yaxin Li Shaili Jain Yunhao Liu Anil K. Jain Jiliang Tang FaML 104 196 0 12 Jul 2021
Can Active Learning Preemptively Mitigate Fairness Issues? Frederic Branchaud-Charron Parmida Atighehchian Pau Rodríguez Grace Abuhamad Alexandre Lacoste FaML 22 20 0 14 Apr 2021
Blockchain-based Digital Twins: Research Trends, Issues, and Future Challenges S. Suhail Rasheed Hussain Raja Jurdak A. Oracevic K. Salah Raimundas Matulevičius Choong Seon Hong AI4CE 21 83 0 22 Mar 2021
Adaptive Sampling for Minimax Fair Classification S. Shekhar Greg Fields Mohammad Ghavamzadeh T. Javidi FaML 35 37 0 01 Mar 2021
Investigating Trade-offs in Utility, Fairness and Differential Privacy in Neural Networks Marlotte Pannekoek G. Spigler FedML 29 26 0 11 Feb 2021
Achieving User-Side Fairness in Contextual Bandits Wen Huang Kevin Labille Xintao Wu Dongwon Lee Neil T. Heffernan FaML 84 18 0 22 Oct 2020
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 323 4,212 0 23 Aug 2019
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 233 674 0 17 Feb 2018
A statistical framework for fair predictive algorithms K. Lum J. Johndrow FaML 177 104 0 25 Oct 2016
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 207 2,084 0 24 Oct 2016