Retiring Adult: New Datasets for Fair Machine Learning

10 August 2021

Papers citing "Retiring Adult: New Datasets for Fair Machine Learning"

50 / 286 papers shown

Title
FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods Xiaotian Han Jianfeng Chi Yu Chen Qifan Wang Han Zhao Na Zou Xia Hu 39 23 0 15 Jun 2023
Questioning the Survey Responses of Large Language Models Ricardo Dominguez-Olmedo Moritz Hardt Celestine Mendler-Dünner 26 30 0 13 Jun 2023
Unprocessing Seven Years of Algorithmic Fairness André F. Cruz Moritz Hardt 16 10 0 12 Jun 2023
Unraveling the Interconnected Axes of Heterogeneity in Machine Learning for Democratic and Inclusive Advancements Maryam Molamohammadi Afaf Taik Nicolas Le Roux G. Farnadi 18 1 0 11 Jun 2023
FedVal: Different good or different bad in federated learning Viktor Valadi Xinchi Qiu Pedro Gusmão Nicholas D. Lane Mina Alibeigi FedML AAML 4 2 0 06 Jun 2023
Generating Private Synthetic Data with Genetic Algorithms Terrance Liu Jin-Lin Tang G. Vietri Zhiwei Steven Wu SyDa 11 16 0 05 Jun 2023
Affinity Clustering Framework for Data Debiasing Using Pairwise Distribution Discrepancy Siamak Ghodsi Eirini Ntoutsi 17 1 0 02 Jun 2023
Adapting Fairness Interventions to Missing Values R. Feng Flavio du Pin Calmon Hao Wang FaML 19 9 0 30 May 2023
Auditing Fairness by Betting Ben Chugg Santiago Cortes-Gomez Bryan Wilder Aaditya Ramdas MLAU 19 7 0 27 May 2023
Mitigating Group Bias in Federated Learning: Beyond Local Fairness G. Wang Ali Payani Myungjin Lee Ramana Rao Kompella FedML 19 8 0 17 May 2023
WEIRD FAccTs: How Western, Educated, Industrialized, Rich, and Democratic is FAccT? Ali Akbar Septiandri Marios Constantinides Mohammad Tahaei Daniele Quercia 20 33 0 10 May 2023
Causal Information Splitting: Engineering Proxy Features for Robustness to Distribution Shifts Bijan Mazaheri Atalanti Mastakouri Dominik Janzing Mila Hardt OOD 22 3 0 10 May 2023
Statistical Inference for Fairness Auditing John J. Cherian Emmanuel J. Candès MLAU 10 7 0 05 May 2023
(Local) Differential Privacy has NO Disparate Impact on Fairness Héber H. Arcolezi K. Makhlouf C. Palamidessi 14 5 0 25 Apr 2023
Individual Fairness in Bayesian Neural Networks Alice Doherty Matthew Wicker Luca Laurenti A. Patané 11 5 0 21 Apr 2023
The Dataset Multiplicity Problem: How Unreliable Data Impacts Predictions Anna P. Meyer Aws Albarghouthi Loris Dántoni 22 13 0 20 Apr 2023
Fairness in AI and Its Long-Term Implications on Society Ondrej Bohdal Timothy M. Hospedales Philip H. S. Torr Fazl Barez 8 4 0 16 Apr 2023
Learning Optimal Fair Scoring Systems for Multi-Class Classification Julien Rouzot Julien Ferry Marie-José Huguet FaML 11 8 0 11 Apr 2023
Last-Layer Fairness Fine-tuning is Simple and Effective for Neural Networks Yuzhen Mao Zhun Deng Huaxiu Yao Ting Ye Kenji Kawaguchi James Y. Zou 36 18 0 08 Apr 2023
Non-Invasive Fairness in Learning through the Lens of Data Drift Ke Yang A. Meliou 13 0 0 30 Mar 2023
Identification of Negative Transfers in Multitask Learning Using Surrogate Models Dongyue Li Huy Le Nguyen Hongyang R. Zhang 29 12 0 25 Mar 2023
Data-centric Artificial Intelligence: A Survey Daochen Zha Zaid Pervaiz Bhat Kwei-Herng Lai Fan Yang Zhimeng Jiang Shaochen Zhong Xia Hu 8 188 0 17 Mar 2023
Explaining Groups of Instances Counterfactually for XAI: A Use Case, Algorithm and User Study for Group-Counterfactuals Greta Warren Markt. Keane Christophe Guéret Eoin Delaney 16 13 0 16 Mar 2023
Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoML Hilde J. P. Weerts Florian Pfisterer Matthias Feurer Katharina Eggensperger Eddie Bergman Noor H. Awad Joaquin Vanschoren Mykola Pechenizkiy B. Bischl Frank Hutter FaML 31 17 0 15 Mar 2023
Explanation Shift: How Did the Distribution Shift Impact the Model? Carlos Mougan Klaus Broelemann David Masip Gjergji Kasneci Thanassis Thiropanis Steffen Staab FAtt 17 1 0 14 Mar 2023
Beyond Demographic Parity: Redefining Equal Treatment Carlos Mougan Laura State Antonio Ferrara Salvatore Ruggieri Steffen Staab FaML 17 1 0 14 Mar 2023
Learning Hybrid Interpretable Models: Theory, Taxonomy, and Methods Julien Ferry Gabriel Laberge Ulrich Aivodji 6 5 0 08 Mar 2023
Chasing Fairness Under Distribution Shift: A Model Weight Perturbation Approach Zhimeng Jiang Xiaotian Han Hongye Jin Guanchu Wang Rui Chen Na Zou Xia Hu 8 13 0 06 Mar 2023
Diagnosing Model Performance Under Distribution Shift Tiffany Cai Hongseok Namkoong Steve Yadlowsky 32 27 0 03 Mar 2023
Feature Importance Disparities for Data Bias Investigations Peter W. Chang Leor Fishman Seth Neel 4 1 0 03 Mar 2023
Domain Adaptive Decision Trees: Implications for Accuracy and Fairness J. Álvarez Kristen M. Scott Salvatore Ruggieri Bettina Berendt 11 6 0 27 Feb 2023
Classification with Trust: A Supervised Approach based on Sequential Ellipsoidal Partitioning Ranjani Niranjan Sachit Rao 8 1 0 21 Feb 2023
Certified private data release for sparse Lipschitz functions Konstantin Donhauser J. Lokna Amartya Sanyal M. Boedihardjo R. Honig Fanny Yang 13 3 0 19 Feb 2023
The Unbearable Weight of Massive Privilege: Revisiting Bias-Variance Trade-Offs in the Context of Fair Prediction Falaah Arif Khan Julia Stoyanovich FaML VLM CML 4 3 0 17 Feb 2023
The Possibility of Fairness: Revisiting the Impossibility Theorem in Practice Andrew Bell Lucius E.J. Bynum Nazarii Drushchak Tetiana Herasymova Lucas Rosenblatt Julia Stoyanovich 17 17 0 13 Feb 2023
Multi-dimensional discrimination in Law and Machine Learning -- A comparative overview Arjun Roy J. Horstmann Eirini Ntoutsi FaML 13 20 0 12 Feb 2023
On Comparing Fair Classifiers under Data Bias Mohit Sharma Amit Deshpande R. Shah 11 2 0 12 Feb 2023
On Fairness and Stability: Is Estimator Variance a Friend or a Foe? Falaah Arif Khan Denys Herasymuk Julia Stoyanovich 17 2 0 09 Feb 2023
Robustness Implies Fairness in Causal Algorithmic Recourse A. Ehyaei Amir-Hossein Karimi Bernhard Schölkopf S. Maghsudi FaML 13 12 0 07 Feb 2023
RLSbench: Domain Adaptation Under Relaxed Label Shift Saurabh Garg Nick Erickson James Sharpnack Alexander J. Smola Sivaraman Balakrishnan Zachary Chase Lipton VLM 20 31 0 06 Feb 2023
An Empirical Analysis of Fairness Notions under Differential Privacy Anderson Santana de Oliveira Caelin Kaplan Khawla Mallat Tanmay Chakraborty FedML 8 7 0 06 Feb 2023
Improving Fair Training under Correlation Shifts Yuji Roh Kangwook Lee Steven Euijong Whang Changho Suh 14 17 0 05 Feb 2023
An Operational Perspective to Fairness Interventions: Where and How to Intervene Brian Hsu Xiaotong Chen Ying Han Hongseok Namkoong Kinjal Basu 11 1 0 03 Feb 2023
On the Within-Group Fairness of Screening Classifiers Nastaran Okati Stratis Tsirtsis Manuel Gomez Rodriguez 22 1 0 31 Jan 2023
Multicalibration as Boosting for Regression Ira Globus-Harris Declan Harrison Michael Kearns Aaron Roth Jessica Sorrell 6 21 0 31 Jan 2023
Retiring $Δ$ DP: New Distribution-Level Metrics for Demographic Parity Xiaotian Han Zhimeng Jiang Hongye Jin Zirui Liu Na Zou Qifan Wang Xia Hu 16 3 0 31 Jan 2023
Aleatoric and Epistemic Discrimination: Fundamental Limits of Fairness Interventions Hao Wang Luxi He Rui Gao Flavio du Pin Calmon 6 9 0 27 Jan 2023
Incentives to Offer Algorithmic Recourse Matthew Olckers T. Walsh 13 2 0 27 Jan 2023
A Linear Reconstruction Approach for Attribute Inference Attacks against Synthetic Data Meenatchi Sundaram Muthu Selva Annamalai Andrea Gadotti Luc Rocher MIACV 11 21 0 24 Jan 2023
Prediction-Powered Inference Anastasios Nikolas Angelopoulos Stephen Bates Clara Fannjiang Michael I. Jordan Tijana Zrnic 15 78 0 23 Jan 2023