A Survey on Bias and Fairness in Machine Learning

23 August 2019

Papers citing "A Survey on Bias and Fairness in Machine Learning"

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Title
Debiased Contrastive Learning Ching-Yao Chuang Joshua Robinson Yen-Chen Lin Antonio Torralba Stefanie Jegelka SSL 8 552 0 01 Jul 2020
Machine learning fairness notions: Bridging the gap with real-world applications K. Makhlouf Sami Zhioua C. Palamidessi FaML 6 53 0 30 Jun 2020
Distributional Individual Fairness in Clustering Nihesh Anderson S. Bera Syamantak Das Yang Liu FedML FaML 13 20 0 22 Jun 2020
Technology Readiness Levels for AI & ML Alexander Lavin Ajay Sharma VLM 11 105 0 21 Jun 2020
Probabilistic Fair Clustering Seyed-Alireza Esmaeili Brian Brubach Leonidas Tsepenekas John P. Dickerson FaML 14 35 0 19 Jun 2020
Towards Threshold Invariant Fair Classification Mingliang Chen Min Wu FaML 14 13 0 18 Jun 2020
On Adversarial Bias and the Robustness of Fair Machine Learning Hong Chang Ta Duy Nguyen S. K. Murakonda Ehsan Kazemi Reza Shokri FaML OOD FedML 6 50 0 15 Jun 2020
Intra-Processing Methods for Debiasing Neural Networks Yash Savani Colin White G. NaveenSundar 12 43 0 15 Jun 2020
Quota-based debiasing can decrease representation of already underrepresented groups Ivan Smirnov Florian Lemmerich Markus Strohmaier 8 1 0 13 Jun 2020
How Interpretable and Trustworthy are GAMs? C. Chang S. Tan Benjamin J. Lengerich Anna Goldenberg R. Caruana FAtt 8 76 0 11 Jun 2020
Towards Integrating Fairness Transparently in Industrial Applications Emily Dodwell Cheryl J. Flynn B. Krishnamurthy S. Majumdar Ritwik Mitra 22 0 0 10 Jun 2020
Hypergraph Clustering for Finding Diverse and Experienced Groups Ilya Amburg Nate Veldt Austin R. Benson 10 5 0 10 Jun 2020
DeepFair: Deep Learning for Improving Fairness in Recommender Systems Jesús Bobadilla R. Lara-Cabrera Ángel González-Prieto Fernando Ortega FaML 17 43 0 09 Jun 2020
Beyond Leaderboards: A survey of methods for revealing weaknesses in Natural Language Inference data and models Viktor Schlegel Goran Nenadic R. Batista-Navarro ELM 25 18 0 29 May 2020
Review of Mathematical frameworks for Fairness in Machine Learning E. del Barrio Paula Gordaliza Jean-Michel Loubes FaML FedML 13 38 0 26 May 2020
Unleashing the power of disruptive and emerging technologies amid COVID-19: A detailed review Sonali Agarwal Narinder Singh Punn S. K. Sonbhadra M. Tanveer P. Nagabhushan K. K. S. Pandian Praveer Saxena 8 58 0 23 May 2020
Fair Classification via Unconstrained Optimization Ibrahim M. Alabdulmohsin FaML 12 6 0 21 May 2020
Statistical Equity: A Fairness Classification Objective Ninareh Mehrabi Yuzhong Huang Fred Morstatter FaML 12 10 0 14 May 2020
Machine Learning on Graphs: A Model and Comprehensive Taxonomy Ines Chami Sami Abu-El-Haija Bryan Perozzi Christopher Ré Kevin Patrick Murphy 20 284 0 07 May 2020
Interpretable Learning-to-Rank with Generalized Additive Models Honglei Zhuang Xuanhui Wang Michael Bendersky Alexander Grushetsky Yonghui Wu Petr Mitrichev Ethan Sterling Nathan Bell Walker Ravina Hai Qian AI4CE FAtt 21 12 0 06 May 2020
Addressing Artificial Intelligence Bias in Retinal Disease Diagnostics Philippe Burlina Neil J. Joshi William Paul Katia D. Pacheco N. Bressler MedIm 6 18 0 28 Apr 2020
Exploring Racial Bias within Face Recognition via per-subject Adversarially-Enabled Data Augmentation Seyma Yucer S. Akçay Noura Al-Moubayed T. Breckon 6 61 0 19 Apr 2020
REVISE: A Tool for Measuring and Mitigating Bias in Visual Datasets Angelina Wang Alexander Liu Ryan Zhang Anat Kleiman Leslie Kim Dora Zhao Iroha Shirai Arvind Narayanan Olga Russakovsky 25 186 0 16 Apr 2020
Machine learning as a model for cultural learning: Teaching an algorithm what it means to be fat Alina Arseniev-Koehler J. Foster 35 46 0 24 Mar 2020
Markovian Score Climbing: Variational Inference with KL(p\|\|q) C. A. Naesseth Fredrik Lindsten David M. Blei 112 54 0 23 Mar 2020
Getting Fairness Right: Towards a Toolbox for Practitioners Boris Ruf Chaouki Boutharouite Marcin Detyniecki FaML 10 5 0 15 Mar 2020
Neural Generators of Sparse Local Linear Models for Achieving both Accuracy and Interpretability Yuya Yoshikawa Tomoharu Iwata 8 7 0 13 Mar 2020
Fairness by Learning Orthogonal Disentangled Representations Mhd Hasan Sarhan Nassir Navab Abouzar Eslami Shadi Albarqouni FaML OOD CML 11 94 0 12 Mar 2020
Hurtful Words: Quantifying Biases in Clinical Contextual Word Embeddings H. Zhang Amy X. Lu Mohamed Abdalla Matthew B. A. McDermott Marzyeh Ghassemi 8 170 0 11 Mar 2020
Fairness by Explicability and Adversarial SHAP Learning James M. Hickey Pietro G. Di Stefano V. Vasileiou FAtt FedML 19 19 0 11 Mar 2020
Causal Interpretability for Machine Learning -- Problems, Methods and Evaluation Raha Moraffah Mansooreh Karami Ruocheng Guo A. Raglin Huan Liu CML ELM XAI 18 212 0 09 Mar 2020
Demographic Bias in Biometrics: A Survey on an Emerging Challenge P. Drozdowski Christian Rathgeb A. Dantcheva N. Damer C. Busch FaML 127 200 0 05 Mar 2020
NestedVAE: Isolating Common Factors via Weak Supervision M. Vowels Necati Cihan Camgöz Richard Bowden CML DRL 21 21 0 26 Feb 2020
DeBayes: a Bayesian Method for Debiasing Network Embeddings Maarten Buyl T. D. Bie FaML CML 21 75 0 26 Feb 2020
It's Not What Machines Can Learn, It's What We Cannot Teach Gal Yehuda Moshe Gabel Assaf Schuster FaML 6 37 0 21 Feb 2020
Weakly-supervised Multi-output Regression via Correlated Gaussian Processes Seokhyun Chung Raed Al Kontar Zhenke Wu 10 3 0 19 Feb 2020
Individual Fairness for $k$ -Clustering S. Mahabadi A. Vakilian FaML 11 82 0 17 Feb 2020
AI safety: state of the field through quantitative lens Mislav Juric A. Sandic Mario Brčič 15 24 0 12 Feb 2020
Convex Density Constraints for Computing Plausible Counterfactual Explanations André Artelt Barbara Hammer 19 47 0 12 Feb 2020
Crowdsourcing the Perception of Machine Teaching Jonggi Hong Kyungjun Lee June Xu Hernisa Kacorri HAI LRM 12 29 0 05 Feb 2020
Deceptive AI Explanations: Creation and Detection Johannes Schneider Christian Meske Michalis Vlachos 6 28 0 21 Jan 2020
Fairness in Learning-Based Sequential Decision Algorithms: A Survey Xueru Zhang M. Liu FaML 35 51 0 14 Jan 2020
Artificial Intelligence for Social Good: A Survey Zheyuan Ryan Shi Claire Wang Fei Fang AI4TS 24 81 0 07 Jan 2020
Fair Active Learning Hadis Anahideh Abolfazl Asudeh Saravanan Thirumuruganathan FaML 36 51 0 06 Jan 2020
Perfectly Parallel Fairness Certification of Neural Networks Caterina Urban M. Christakis Valentin Wüstholz Fuyuan Zhang 14 65 0 05 Dec 2019
FANNet: Formal Analysis of Noise Tolerance, Training Bias and Input Sensitivity in Neural Networks Mahum Naseer M. Minhas Faiq Khalid Muhammad Abdullah Hanif Osman Hasan Muhammad Shafique AAML 28 17 0 03 Dec 2019
FairyTED: A Fair Rating Predictor for TED Talk Data Rupam Acharyya Shouman Das Ankani Chattoraj Md. Iftekhar Tanveer 11 12 0 25 Nov 2019
Adaptive Sampling for Stochastic Risk-Averse Learning Sebastian Curi Kfir Y. Levy Stefanie Jegelka Andreas Krause 16 51 0 28 Oct 2019
Man is to Person as Woman is to Location: Measuring Gender Bias in Named Entity Recognition Ninareh Mehrabi Thamme Gowda Fred Morstatter Nanyun Peng Aram Galstyan 10 57 0 24 Oct 2019
Does Gender Matter? Towards Fairness in Dialogue Systems Haochen Liu Jamell Dacon Wenqi Fan Hui Liu Zitao Liu Jiliang Tang 25 141 0 16 Oct 2019