Cover Image

The Impact of Differential Feature Under-reporting on Algorithmic Fairness

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Akpinar, Nil-Jana, Lipton, Zachary C., Chouldechova, Alexandra
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Computers and Society
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

The Fragility of Fairness: Causal Sensitivity Analysis for Fair Machine Learning
by: Fawkes, Jake, et al.
Published: (2024)

Auditing Fairness under Unobserved Confounding
by: Byun, Yewon, et al.
Published: (2024)

A Unified Causal Framework for Auditing Recommender Systems for Ethical Concerns
by: Sharma, Vibhhu, et al.
Published: (2024)

A structured regression approach for evaluating model performance across intersectional subgroups
by: Herlihy, Christine, et al.
Published: (2024)

Authenticity and exclusion: social media algorithms and the dynamics of belonging in epistemic communities
by: Akpinar, Nil-Jana, et al.
Published: (2024)

Evaluating the Fairness of the MIMIC-IV Dataset and a Baseline Algorithm: Application to the ICU Length of Stay Prediction
by: Kakadiaris, Alexandra
Published: (2023)

On the Impact of Multi-dimensional Local Differential Privacy on Fairness
by: Makhlouf, Karima, et al.
Published: (2023)

Benchmarking Stochastic Approximation Algorithms for Fairness-Constrained Training of Deep Neural Networks
by: Kliachkin, Andrii, et al.
Published: (2025)

Validating LLM-as-a-Judge Systems under Rating Indeterminacy
by: Guerdan, Luke, et al.
Published: (2025)

Who's Asking? Evaluating LLM Robustness to Inquiry Personas in Factual Question Answering
by: Akpinar, Nil-Jana, et al.
Published: (2025)

What is Fair? Defining Fairness in Machine Learning for Health
by: Gao, Jianhui, et al.
Published: (2024)

Algorithmic Fairness in Performative Policy Learning: Escaping the Impossibility of Group Fairness
by: Somerstep, Seamus, et al.
Published: (2024)

Unprocessing Seven Years of Algorithmic Fairness
by: Cruz, André F., et al.
Published: (2023)

Red-Teaming for Generative AI: Silver Bullet or Security Theater?
by: Feffer, Michael, et al.
Published: (2024)

Precise Model Benchmarking with Only a Few Observations
by: Fogliato, Riccardo, et al.
Published: (2024)

FairDP: Certified Fairness with Differential Privacy
by: Tran, Khang, et al.
Published: (2023)

Bias Begins with Data: The FairGround Corpus for Robust and Reproducible Research on Algorithmic Fairness
by: Simson, Jan, et al.
Published: (2025)

Improving the Fairness of Deep-Learning, Short-term Crime Prediction with Under-reporting-aware Models
by: Wu, Jiahui, et al.
Published: (2024)

Evaluating Fair Feature Selection in Machine Learning for Healthcare
by: Zawad, Md Rahat Shahriar, et al.
Published: (2024)

OxonFair: A Flexible Toolkit for Algorithmic Fairness
by: Delaney, Eoin, et al.
Published: (2024)

Fairness in Algorithmic Recourse Through the Lens of Substantive Equality of Opportunity
by: Bell, Andrew, et al.
Published: (2024)

Auditing LLMs for Algorithmic Fairness in Casenote-Augmented Tabular Prediction
by: Lee, Xiao Qi, et al.
Published: (2026)

On the Impact of Output Perturbation on Fairness in Binary Linear Classification
by: Emelianov, Vitalii, et al.
Published: (2024)

Effects of Generative AI Errors on User Reliance Across Task Difficulty
by: Anthis, Jacy Reese, et al.
Published: (2026)

A Framework for Evaluating LLMs Under Task Indeterminacy
by: Guerdan, Luke, et al.
Published: (2024)

Differential Privacy in Two-Layer Networks: How DP-SGD Harms Fairness and Robustness
by: Xu, Ruichen, et al.
Published: (2026)

Group Fairness Meets the Black Box: Enabling Fair Algorithms on Closed LLMs via Post-Processing
by: Xian, Ruicheng, et al.
Published: (2025)

Differentially Private Post-Processing for Fair Regression
by: Xian, Ruicheng, et al.
Published: (2024)

Cost Efficient Fairness Audit Under Partial Feedback
by: Das, Nirjhar, et al.
Published: (2025)

What is Left After Distillation? How Knowledge Transfer Impacts Fairness and Bias
by: Mohammadshahi, Aida, et al.
Published: (2024)

Fair and Accurate Regression: Strong Formulations and Algorithms
by: Deza, Anna, et al.
Published: (2024)

FairHome: A Fair Housing and Fair Lending Dataset
by: Bagalkotkar, Anusha, et al.
Published: (2024)

Debias-CLR: A Contrastive Learning Based Debiasing Method for Algorithmic Fairness in Healthcare Applications
by: Agarwal, Ankita, et al.
Published: (2024)

Algorithmic Tradeoffs in Fair Lending: Profitability, Compliance, and Long-Term Impact
by: Bansal, Aayam
Published: (2025)

FairWire: Fair Graph Generation
by: Kose, O. Deniz, et al.
Published: (2024)

Quantitative Auditing of AI Fairness with Differentially Private Synthetic Data
by: Yuan, Chih-Cheng Rex, et al.
Published: (2025)

Decision Making with Differential Privacy under a Fairness Lens
by: Fioretto, Ferdinando, et al.
Published: (2021)

Supervised Algorithmic Fairness in Distribution Shifts: A Survey
by: Shao, Minglai, et al.
Published: (2024)

Fairness Hacking: The Malicious Practice of Shrouding Unfairness in Algorithms
by: Meding, Kristof, et al.
Published: (2023)

Insights From Insurance for Fair Machine Learning
by: Fröhlich, Christian, et al.
Published: (2023)