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
The Impact of Differential Feature Under-reporting on Algorithmic Fairness Nil-Jana Akpinar Zachary C. Lipton Alexandra Chouldechova 18 4 0 16 Jan 2024
Estimating Model Performance Under Covariate Shift Without Labels Jakub Bialek W. Kuberski Nikolaos Perrakis Albert Bifet 18 2 0 16 Jan 2024
Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift Benjamin Eyre Elliot Creager David Madras Antonio Torralba Katherine Heller OOD OODD 23 1 0 29 Dec 2023
Initializing Services in Interactive ML Systems for Diverse Users Avinandan Bose Mihaela Curmei Daniel L. Jiang Jamie Morgenstern Sarah Dean Lillian J. Ratliff Maryam Fazel 11 5 0 19 Dec 2023
A Simple and Practical Method for Reducing the Disparate Impact of Differential Privacy Lucas Rosenblatt Julia Stoyanovich Christopher Musco 11 2 0 18 Dec 2023
Uncertainty-based Fairness Measures Selim Kuzucu Jiaee Cheong Hatice Gunes Sinan Kalkan UD PER 21 1 0 18 Dec 2023
Continuous Diffusion for Mixed-Type Tabular Data Markus Mueller Kathrin Gruber Dennis Fok DiffM 53 5 0 16 Dec 2023
Benchmarking Distribution Shift in Tabular Data with TableShift Josh Gardner Zoran Popovic Ludwig Schmidt OOD 13 32 0 10 Dec 2023
A Brief Tutorial on Sample Size Calculations for Fairness Audits Harvineet Singh Fan Xia Mi-Ok Kim Romain Pirracchio R. Chunara Jean Feng 10 0 0 07 Dec 2023
On the Impact of Multi-dimensional Local Differential Privacy on Fairness K. Makhlouf Héber H. Arcolezi Sami Zhioua G. B. Brahim C. Palamidessi 12 4 0 07 Dec 2023
f-FERM: A Scalable Framework for Robust Fair Empirical Risk Minimization Sina Baharlouei Shivam Patel Meisam Razaviyayn 30 4 0 06 Dec 2023
FRAPPE: A Group Fairness Framework for Post-Processing Everything Alexandru Tifrea Preethi Lahoti Ben Packer Yoni Halpern Ahmad Beirami Flavien Prost 34 6 0 05 Dec 2023
Certification of Distributional Individual Fairness Matthew Wicker Vihari Piratla Adrian Weller 19 1 0 20 Nov 2023
From Principle to Practice: Vertical Data Minimization for Machine Learning Robin Staab Nikola Jovanović Mislav Balunović Martin Vechev 21 5 0 17 Nov 2023
Fairness Hacking: The Malicious Practice of Shrouding Unfairness in Algorithms Kristof Meding Thilo Hagendorff 29 6 0 12 Nov 2023
Procedural Fairness Through Decoupling Objectionable Data Generating Components Zeyu Tang Jialu Wang Yang Liu Peter Spirtes Kun Zhang 14 2 0 05 Nov 2023
Equal Opportunity of Coverage in Fair Regression Fangxin Wang Lu Cheng Ruocheng Guo Kay Liu Philip S. Yu 19 14 0 03 Nov 2023
PPI++: Efficient Prediction-Powered Inference Anastasios Nikolas Angelopoulos John C. Duchi Tijana Zrnic 8 34 0 02 Nov 2023
Parametric Fairness with Statistical Guarantees François Hu Philipp Ratz Arthur Charpentier FaML 11 1 0 31 Oct 2023
WCLD: Curated Large Dataset of Criminal Cases from Wisconsin Circuit Courts Elliott Ash Naman Goel Nianyun Li Claudia Marangon Peiyao Sun 11 2 0 28 Oct 2023
On the Fairness ROAD: Robust Optimization for Adversarial Debiasing Vincent Grari Thibault Laugel Tatsunori Hashimoto Sylvain Lamprier Marcin Detyniecki 27 2 0 27 Oct 2023
fairret: a Framework for Differentiable Fairness Regularization Terms Maarten Buyl Marybeth Defrance T. D. Bie FedML 13 4 0 26 Oct 2023
On the Interplay between Fairness and Explainability Stephanie Brandl Emanuele Bugliarello Ilias Chalkidis FaML 22 4 0 25 Oct 2023
FairBranch: Fairness Conflict Correction on Task-group Branches for Fair Multi-Task Learning Arjun Roy C. Koutlis Symeon Papadopoulos Eirini Ntoutsi 11 0 0 20 Oct 2023
Fairer and More Accurate Tabular Models Through NAS Richeek Das Samuel Dooley 13 4 0 18 Oct 2023
Beyond Memorization: Violating Privacy Via Inference with Large Language Models Robin Staab Mark Vero Mislav Balunović Martin Vechev PILM 27 72 0 11 Oct 2023
Oracle Efficient Algorithms for Groupwise Regret Krishna Acharya Eshwar Ram Arunachaleswaran Sampath Kannan Aaron Roth Juba Ziani AI4TS 29 2 0 07 Oct 2023
Quantifying and mitigating the impact of label errors on model disparity metrics Julius Adebayo Melissa Hall Bowen Yu Bobbie Chern 11 10 0 04 Oct 2023
Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and Tools Maximilian Schambach Rakshit Naidu Rayid Ghani Kit T. Rodolfa Daniel E. Ho Hoda Heidari FaML 27 13 0 29 Sep 2023
Cross-Prediction-Powered Inference Tijana Zrnic Emmanuel J. Candès 22 23 0 28 Sep 2023
Dr. FERMI: A Stochastic Distributionally Robust Fair Empirical Risk Minimization Framework Sina Baharlouei Meisam Razaviyayn FaML OOD 30 0 0 20 Sep 2023
A Sequentially Fair Mechanism for Multiple Sensitive Attributes Franccois Hu Philipp Ratz Arthur Charpentier FaML 16 6 0 12 Sep 2023
Exploring the Benefits of Differentially Private Pre-training and Parameter-Efficient Fine-tuning for Table Transformers Xilong Wang Chia-Mu Yu Pin-Yu Chen 16 0 0 12 Sep 2023
Bias Propagation in Federated Learning Hong Chang Reza Shokri FedML 16 10 0 05 Sep 2023
Fairness in Ranking under Disparate Uncertainty Richa Rastogi Thorsten Joachims 22 3 0 04 Sep 2023
Bias Testing and Mitigation in LLM-based Code Generation Dong Huang Qingwen Bu Jie M. Zhang Xiaofei Xie Junjie Chen Heming Cui 33 20 0 03 Sep 2023
One Model Many Scores: Using Multiverse Analysis to Prevent Fairness Hacking and Evaluate the Influence of Model Design Decisions Jan Simson Florian Pfisterer Christoph Kern 17 12 0 31 Aug 2023
Environment Diversification with Multi-head Neural Network for Invariant Learning Bo-Wei Huang Keng-Te Liao Chang-Sheng Kao Shou-De Lin OOD 13 4 0 17 Aug 2023
Fairness Improvement with Multiple Protected Attributes: How Far Are We? Zhenpeng Chen Jie M. Zhang Federica Sarro Mark Harman FaML 22 4 0 25 Jul 2023
Fairness Under Demographic Scarce Regime Patrik Joslin Kenfack Samira Ebrahimi Kahou Ulrich Aivodji 26 2 0 24 Jul 2023
Collaboratively Learning Linear Models with Structured Missing Data Chen Cheng Gary Cheng John C. Duchi FedML 9 2 0 22 Jul 2023
On the Utility Gain of Iterative Bayesian Update for Locally Differentially Private Mechanisms Héber H. Arcolezi Selene Cerna C. Palamidessi 14 3 0 15 Jul 2023
Dissenting Explanations: Leveraging Disagreement to Reduce Model Overreliance Omer Reingold J. Shen Aditi Talati FAtt LRM 17 3 0 14 Jul 2023
On The Impact of Machine Learning Randomness on Group Fairness Prakhar Ganesh Hong Chang Martin Strobel Reza Shokri FaML 8 30 0 09 Jul 2023
Scalable Membership Inference Attacks via Quantile Regression Martín Bertrán Shuai Tang Michael Kearns Jamie Morgenstern Aaron Roth Zhiwei Steven Wu MIACV 30 44 0 07 Jul 2023
When Fair Classification Meets Noisy Protected Attributes Avijit Ghosh Pablo Kvitca Chris L. Wilson FaML 11 6 0 06 Jul 2023
On the Cause of Unfairness: A Training Sample Perspective Yuanshun Yao Yang Liu TDI 20 0 0 30 Jun 2023
AutoML in Heavily Constrained Applications Felix Neutatz Marius Lindauer Ziawasch Abedjan 14 4 0 29 Jun 2023
Correcting Underrepresentation and Intersectional Bias for Classification Emily Diana A. Tolbert FaML 19 1 0 19 Jun 2023
Fairness in Multi-Task Learning via Wasserstein Barycenters Franccois Hu Philipp Ratz Arthur Charpentier 26 10 0 16 Jun 2023