Title
Demographic Fairness in Biometric Systems: What do the Experts say? Christian Rathgeb P. Drozdowski Naser Damer Dinusha Frings Christoph Busch FaML 26 23 0 31 May 2021
Fair Feature Distillation for Visual Recognition S. Jung Donggyu Lee Taeeon Park Taesup Moon 22 76 0 27 May 2021
Bias in Machine Learning Software: Why? How? What to do? Joymallya Chakraborty Suvodeep Majumder Tim Menzies FaML 19 193 0 25 May 2021
Improving Fairness of AI Systems with Lossless De-biasing Yan Zhou Murat Kantarcioglu Chris Clifton 33 12 0 10 May 2021
Transitioning from Real to Synthetic data: Quantifying the bias in model Aman Gupta Deepak L. Bhatt Anubha Pandey 17 17 0 10 May 2021
When Fair Ranking Meets Uncertain Inference Avijit Ghosh Ritam Dutt Christo Wilson 39 44 0 05 May 2021
Question-Driven Design Process for Explainable AI User Experiences Q. V. Liao Milena Pribić Jaesik Han Sarah Miller Daby M. Sow 20 52 0 08 Apr 2021
End-To-End Bias Mitigation: Removing Gender Bias in Deep Learning Tal Feldman Ashley Peake FaML 16 13 0 06 Apr 2021
fairmodels: A Flexible Tool For Bias Detection, Visualization, And Mitigation Jakub Wi'sniewski P. Biecek 24 18 0 01 Apr 2021
Individually Fair Gradient Boosting Alexander Vargo Fan Zhang Mikhail Yurochkin Yuekai Sun FaML FedML 24 15 0 31 Mar 2021
Statistical inference for individual fairness Subha Maity Songkai Xue Mikhail Yurochkin Yuekai Sun FaML 25 20 0 30 Mar 2021
DebIE: A Platform for Implicit and Explicit Debiasing of Word Embedding Spaces Niklas Friedrich Anne Lauscher Simone Paolo Ponzetto Goran Glavavs 28 7 0 11 Mar 2021
Fairness On The Ground: Applying Algorithmic Fairness Approaches to Production Systems Chloé Bakalar Renata Barreto Stevie Bergman Miranda Bogen Bobbie Chern ... J. Simons Jonathan Tannen Edmund Tong Kate Vredenburgh Jiejing Zhao FaML 11 26 0 10 Mar 2021
Estimating and Improving Fairness with Adversarial Learning Xiaoxiao Li Ziteng Cui Yifan Wu Li Gu Tatsuya Harada MedIm 17 38 0 07 Mar 2021
Exploring the Assessment List for Trustworthy AI in the Context of Advanced Driver-Assistance Systems Markus Borg Joshua Bronson Linus Christensson Fredrik Olsson Olof Lennartsson Elias Sonnsjö Hamid Ebabi Martin Karsberg 14 12 0 04 Mar 2021
CLAIMED, a visual and scalable component library for Trusted AI Romeo Kienzler I. Nesic 11 1 0 04 Mar 2021
MIMIC-IF: Interpretability and Fairness Evaluation of Deep Learning Models on MIMIC-IV Dataset Chuizheng Meng Loc Trinh Nan Xu Yan Liu 24 30 0 12 Feb 2021
Investigating Trade-offs in Utility, Fairness and Differential Privacy in Neural Networks Marlotte Pannekoek G. Spigler FedML 29 26 0 11 Feb 2021
Statistically Profiling Biases in Natural Language Reasoning Datasets and Models Shanshan Huang Kenny Q. Zhu 16 1 0 09 Feb 2021
Removing biased data to improve fairness and accuracy Sahil Verma Michael Ernst René Just FaML 16 24 0 05 Feb 2021
BeFair: Addressing Fairness in the Banking Sector Alessandro Castelnovo Riccardo Crupi Giulia Del Gamba Greta Greco A. Naseer D. Regoli Beatriz San Miguel González FaML 23 16 0 03 Feb 2021
Fairness through Social Welfare Optimization V. Chen J. N. Hooker 24 1 0 30 Jan 2021
Socially Responsible AI Algorithms: Issues, Purposes, and Challenges Lu Cheng Kush R. Varshney Huan Liu FaML 25 145 0 01 Jan 2021
A Maximal Correlation Approach to Imposing Fairness in Machine Learning Joshua K. Lee Yuheng Bu P. Sattigeri Yikang Shen G. Wornell Leonid Karlinsky Rogerio Feris FaML 13 15 0 30 Dec 2020
dalex: Responsible Machine Learning with Interactive Explainability and Fairness in Python Hubert Baniecki Wojciech Kretowicz Piotr Piątyszek J. Wiśniewski P. Biecek FaML 26 95 0 28 Dec 2020
Fairkit, Fairkit, on the Wall, Who's the Fairest of Them All? Supporting Data Scientists in Training Fair Models Brittany Johnson Jesse Bartola Rico Angell Katherine Keith Sam Witty S. Giguere Yuriy Brun FaML 22 18 0 17 Dec 2020
Developing Future Human-Centered Smart Cities: Critical Analysis of Smart City Security, Interpretability, and Ethical Challenges Kashif Ahmad Majdi Maabreh M. Ghaly Khalil Khan Junaid Qadir Ala I. Al-Fuqaha 27 142 0 14 Dec 2020
A Statistical Test for Probabilistic Fairness Bahar Taşkesen Jose H. Blanchet Daniel Kuhn Viet Anh Nguyen FaML 14 38 0 09 Dec 2020
Mitigating Bias in Federated Learning Annie Abay Yi Zhou Nathalie Baracaldo Shashank Rajamoni Ebube Chuba Heiko Ludwig AI4CE 8 87 0 04 Dec 2020
Fair Attribute Classification through Latent Space De-biasing V. V. Ramaswamy Sunnie S. Y. Kim Olga Russakovsky 17 163 0 02 Dec 2020
Towards Fairness in Classifying Medical Conversations into SOAP Sections Elisa Ferracane Sandeep Konam FaML 16 4 0 02 Dec 2020
Fair Densities via Boosting the Sufficient Statistics of Exponential Families Alexander Soen Hisham Husain Richard Nock FedML 31 1 0 01 Dec 2020
Uncovering the Bias in Facial Expressions J. Deuschel Bettina Finzel Ines Rieger CVBM 13 13 0 23 Nov 2020
Augmented Fairness: An Interpretable Model Augmenting Decision-Makers' Fairness Tong Wang M. Saar-Tsechansky 26 11 0 17 Nov 2020
FairLens: Auditing Black-box Clinical Decision Support Systems Cecilia Panigutti Alan Perotti Andre' Panisson P. Bajardi D. Pedreschi 17 66 0 08 Nov 2020
On the Privacy Risks of Algorithmic Fairness Hong Chang Reza Shokri FaML 33 109 0 07 Nov 2020
Making ML models fairer through explanations: the case of LimeOut Guilherme Alves Vaishnavi Bhargava Miguel Couceiro A. Napoli FaML 6 7 0 01 Nov 2020
Linear Classifiers that Encourage Constructive Adaptation Yatong Chen Jialu Wang Yang Liu 33 16 0 31 Oct 2020
"What We Can't Measure, We Can't Understand": Challenges to Demographic Data Procurement in the Pursuit of Fairness Mckane Andrus Elena Spitzer Jeffrey Brown Alice Xiang 27 126 0 30 Oct 2020
One-vs.-One Mitigation of Intersectional Bias: A General Method to Extend Fairness-Aware Binary Classification Kenji Kobayashi Yuri Nakao FaML 30 8 0 26 Oct 2020
Do's and Don'ts for Human and Digital Worker Integration Vinod Muthusamy Merve Unuvar Hagen Volzer Justin D. Weisz 14 2 0 15 Oct 2020
Explainability for fair machine learning T. Begley Tobias Schwedes Christopher Frye Ilya Feige FaML FedML 6 47 0 14 Oct 2020
FaiR-N: Fair and Robust Neural Networks for Structured Data Shubham Sharma Alan H. Gee D. Paydarfar Joydeep Ghosh 26 18 0 13 Oct 2020
Metrics and methods for a systematic comparison of fairness-aware machine learning algorithms Gareth Jones James M. Hickey Pietro G. Di Stefano C. Dhanjal Laura C. Stoddart V. Vasileiou FaML 33 21 0 08 Oct 2020
Fairness in Machine Learning: A Survey Simon Caton C. Haas FaML 32 615 0 04 Oct 2020
Towards a Measure of Individual Fairness for Deep Learning Krystal Maughan Joseph P. Near TDI FaML 21 5 0 28 Sep 2020
Legally grounded fairness objectives Dylan Holden-Sim Gavin Leech Laurence Aitchison AILaw FaML 22 0 0 24 Sep 2020
Addressing Cognitive Biases in Augmented Business Decision Systems Thomas Baudel Manon Verbockhaven Guillaume Roy Victoire Cousergue Rida Laarach 14 3 0 17 Sep 2020
FairFace Challenge at ECCV 2020: Analyzing Bias in Face Recognition Tomás Sixta Julio C. S. Jacques Junior Pau Buch-Cardona Neil M. Robertson E. Vazquez Sergio Escalera CVBM 30 34 0 16 Sep 2020
Justicia: A Stochastic SAT Approach to Formally Verify Fairness Bishwamittra Ghosh D. Basu Kuldeep S. Meel 19 36 0 14 Sep 2020