Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations

1 July 2017

Papers citing "Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations"

45 / 95 papers shown

Title
AI Fairness via Domain Adaptation Neil J. Joshi Philippe Burlina 29 15 0 15 Mar 2021
Estimating and Improving Fairness with Adversarial Learning Xiaoxiao Li Ziteng Cui Yifan Wu Li Gu Tatsuya Harada MedIm 35 38 0 07 Mar 2021
Understanding and Mitigating Accuracy Disparity in Regression Jianfeng Chi Yuan Tian Geoffrey J. Gordon Han Zhao 27 25 0 24 Feb 2021
Technical Challenges for Training Fair Neural Networks Valeriia Cherepanova V. Nanda Micah Goldblum John P. Dickerson Tom Goldstein FaML 25 22 0 12 Feb 2021
Towards Fair Deep Anomaly Detection Hongjing Zhang Ian Davidson FaML 55 39 0 29 Dec 2020
Latent Adversarial Debiasing: Mitigating Collider Bias in Deep Neural Networks L. N. Darlow Stanisław Jastrzębski Amos Storkey 48 24 0 19 Nov 2020
On Transferability of Bias Mitigation Effects in Language Model Fine-Tuning Xisen Jin Francesco Barbieri Brendan Kennedy Aida Mostafazadeh Davani Leonardo Neves Xiang Ren 35 5 0 24 Oct 2020
Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information Enyan Dai Suhang Wang FaML 16 241 0 03 Sep 2020
Fairness-Aware Online Personalization G. R. Lal S. Geyik K. Kenthapadi FaML 13 3 0 30 Jul 2020
Adversarial representation learning for private speech generation David Ericsson Adam Östberg Edvin Listo Zec John Martinsson Olof Mogren 27 16 0 16 Jun 2020
Review of Mathematical frameworks for Fairness in Machine Learning E. del Barrio Paula Gordaliza Jean-Michel Loubes FaML FedML 15 39 0 26 May 2020
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 49 371 0 30 Apr 2020
Fairness by Explicability and Adversarial SHAP Learning James M. Hickey Pietro G. Di Stefano V. Vasileiou FAtt FedML 33 19 0 11 Mar 2020
Algorithmic Fairness Dana Pessach E. Shmueli FaML 33 386 0 21 Jan 2020
A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications Jie Gui Zhenan Sun Yonggang Wen Dacheng Tao Jieping Ye EGVM 33 821 0 20 Jan 2020
Stereotypical Bias Removal for Hate Speech Detection Task using Knowledge-based Generalizations Pinkesh Badjatiya Manish Gupta Vasudeva Varma 17 105 0 15 Jan 2020
Fair Generative Modeling via Weak Supervision Kristy Choi Aditya Grover Trisha Singh Rui Shu Stefano Ermon 36 133 0 26 Oct 2019
On the Global Optima of Kernelized Adversarial Representation Learning Bashir Sadeghi Runyi Yu Vishnu Boddeti AAML 67 31 0 16 Oct 2019
Conditional Learning of Fair Representations Han Zhao Amanda Coston T. Adel Geoffrey J. Gordon FaML 30 106 0 16 Oct 2019
Avoiding Resentment Via Monotonic Fairness G. W. Cole Sinead Williamson FaML 16 7 0 03 Sep 2019
Wasserstein Fair Classification Ray Jiang Aldo Pacchiano T. Stepleton Heinrich Jiang Silvia Chiappa 33 173 0 28 Jul 2019
Learning Fair and Transferable Representations L. Oneto Michele Donini Andreas Maurer Massimiliano Pontil FaML 37 19 0 25 Jun 2019
Transfer of Machine Learning Fairness across Domains Candice Schumann Xuezhi Wang Alex Beutel Jilin Chen Hai Qian Ed H. Chi 35 69 0 24 Jun 2019
Mitigating Gender Bias in Natural Language Processing: Literature Review Tony Sun Andrew Gaut Shirlyn Tang Yuxin Huang Mai Elsherief Jieyu Zhao Diba Mirza E. Belding-Royer Kai-Wei Chang William Yang Wang AI4CE 47 543 0 21 Jun 2019
Leveraging Labeled and Unlabeled Data for Consistent Fair Binary Classification Evgenii Chzhen Christophe Denis Mohamed Hebiri L. Oneto Massimiliano Pontil FaML 19 85 0 12 Jun 2019
Differential Privacy Has Disparate Impact on Model Accuracy Eugene Bagdasaryan Vitaly Shmatikov 34 467 0 28 May 2019
Learning Fair Representations via an Adversarial Framework Rui Feng Yang Yang Yuehan Lyu Chenhao Tan Yizhou Sun Chunping Wang FaML 25 55 0 30 Apr 2019
Nuanced Metrics for Measuring Unintended Bias with Real Data for Text Classification Daniel Borkan Lucas Dixon Jeffrey Scott Sorensen Nithum Thain Lucy Vasserman 42 473 0 11 Mar 2019
Fairness in Recommendation Ranking through Pairwise Comparisons Alex Beutel Jilin Chen Tulsee Doshi Hai Qian Li Wei ... Lukasz Heldt Zhe Zhao Lichan Hong Ed H. Chi Cristos Goodrow FaML 36 373 0 02 Mar 2019
Identifying and Correcting Label Bias in Machine Learning Heinrich Jiang Ofir Nachum FaML 14 281 0 15 Jan 2019
Putting Fairness Principles into Practice: Challenges, Metrics, and Improvements Alex Beutel Jilin Chen Tulsee Doshi Hai Qian Allison Woodruff Christine Luu Pierre Kreitmann Jonathan Bischof Ed H. Chi FaML 30 150 0 14 Jan 2019
Fighting Fire with Fire: Using Antidote Data to Improve Polarization and Fairness of Recommender Systems Bashir Rastegarpanah Krishna P. Gummadi M. Crovella 24 119 0 02 Dec 2018
Balanced Datasets Are Not Enough: Estimating and Mitigating Gender Bias in Deep Image Representations Tianlu Wang Jieyu Zhao Mark Yatskar Kai-Wei Chang Vicente Ordonez FaML 34 17 0 20 Nov 2018
The Price of Fair PCA: One Extra Dimension Samira Samadi U. Tantipongpipat Jamie Morgenstern Mohit Singh Santosh Vempala FaML 22 154 0 31 Oct 2018
Discovering Fair Representations in the Data Domain Novi Quadrianto V. Sharmanska Oliver Thomas 21 3 0 15 Oct 2018
Counterfactual Fairness in Text Classification through Robustness Sahaj Garg Vincent Perot Nicole Limtiaco Ankur Taly Ed H. Chi Alex Beutel 22 258 0 27 Sep 2018
Adversarial Removal of Demographic Attributes from Text Data Yanai Elazar Yoav Goldberg FaML 30 304 0 20 Aug 2018
Achieving Fairness through Adversarial Learning: an Application to Recidivism Prediction C. Wadsworth Francesca Vera Chris Piech FaML 25 180 0 30 Jun 2018
FairGAN: Fairness-aware Generative Adversarial Networks Depeng Xu Shuhan Yuan Lu Zhang Xintao Wu GAN 33 306 0 28 May 2018
Fairness GAN P. Sattigeri Samuel C. Hoffman Vijil Chenthamarakshan Kush R. Varshney 18 93 0 24 May 2018
Probably Approximately Metric-Fair Learning G. Rothblum G. Yona FaML FedML 8 85 0 08 Mar 2018
Empirical Risk Minimization under Fairness Constraints Michele Donini L. Oneto Shai Ben-David John Shawe-Taylor Massimiliano Pontil FaML 24 439 0 23 Feb 2018
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 233 676 0 17 Feb 2018
Mitigating Unwanted Biases with Adversarial Learning B. Zhang Blake Lemoine Margaret Mitchell FaML 23 1,365 0 22 Jan 2018
InclusiveFaceNet: Improving Face Attribute Detection with Race and Gender Diversity Hee Jung Ryu Hartwig Adam Margaret Mitchell FaML 20 30 0 01 Dec 2017