Cover Image

Auditing Fairness under Unobserved Confounding

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Byun, Yewon, Sam, Dylan, Oberst, Michael, Lipton, Zachary C., Wilder, Bryan
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Computers and Society Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Causal Fairness under Unobserved Confounding: A Neural Sensitivity Framework
by: Schröder, Maresa, et al.
Published: (2023)

Auditing Fairness by Betting
by: Chugg, Ben, et al.
Published: (2023)

Robust Design and Evaluation of Predictive Algorithms under Unobserved Confounding
by: Rambachan, Ashesh, et al.
Published: (2022)

Expert Routing with Synthetic Data for Continual Learning
by: Byun, Yewon, et al.
Published: (2024)

Predictive Performance Comparison of Decision Policies Under Confounding
by: Guerdan, Luke, et al.
Published: (2024)

Causal Inference with Categorical Unobserved Confounder via Mixture Learning
by: Saha, Aytijhya, et al.
Published: (2026)

Sensitivity Analysis to Unobserved Confounding with Copula-based Normalizing Flows
by: Balgi, Sourabh, et al.
Published: (2025)

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

Valid Inference with Imperfect Synthetic Data
by: Byun, Yewon, et al.
Published: (2025)

Causal Discovery of Linear Non-Gaussian Causal Models with Unobserved Confounding
by: Schkoda, Daniela, et al.
Published: (2024)

The Impact of Differential Feature Under-reporting on Algorithmic Fairness
by: Akpinar, Nil-Jana, et al.
Published: (2024)

Counterfactually Fair Reinforcement Learning via Sequential Data Preprocessing
by: Wang, Jitao, et al.
Published: (2025)

A Computational Approach to Improving Fairness in K-means Clustering
by: Zhou, Guancheng, et al.
Published: (2025)

A Data Envelopment Analysis Approach for Assessing Fairness in Resource Allocation: Application to Kidney Exchange Programs
by: Kaazempur-Mofrad, Ali, et al.
Published: (2024)

Peer Effect Estimation in the Presence of Simultaneous Feedback and Unobserved Confounders
by: Du, Xiaojing, et al.
Published: (2025)

Decision-Focused Evaluation of Worst-Case Distribution Shift
by: Ren, Kevin, et al.
Published: (2024)

Penalized Fair Regression for Multiple Groups in Chronic Kidney Disease
by: Nakamoto, Carter H., et al.
Published: (2025)

Fair Risk Control: A Generalized Framework for Calibrating Multi-group Fairness Risks
by: Zhang, Lujing, et al.
Published: (2024)

Partial Identification Approach to Counterfactual Fairness Assessment
by: Rho, Saeyoung, et al.
Published: (2025)

Learning treatment effects while treating those in need
by: Wilder, Bryan, et al.
Published: (2024)

What Hides behind Unfairness? Exploring Dynamics Fairness in Reinforcement Learning
by: Deng, Zhihong, et al.
Published: (2024)

Local Causal Discovery for Estimating Causal Effects
by: Gupta, Shantanu, et al.
Published: (2023)

Fostering the Ecosystem of AI for Social Impact Requires Expanding and Strengthening Evaluation Standards
by: Wilder, Bryan, et al.
Published: (2025)

$ρ$-GNF: A Copula-based Sensitivity Analysis to Unobserved Confounding Using Normalizing Flows
by: Balgi, Sourabh, et al.
Published: (2022)

Benchmarking Observational Studies with Experimental Data under Right-Censoring
by: Demirel, Ilker, et al.
Published: (2024)

Federated Epidemic Surveillance
by: Lyu, Ruiqi, et al.
Published: (2023)

Statistical learning for constrained functional parameters in infinite-dimensional models
by: Nabi, Razieh, et al.
Published: (2024)

The Missing Link: Allocation Performance in Causal Machine Learning
by: Fischer-Abaigar, Unai, et al.
Published: (2024)

From Correlation to Causation: Understanding Climate Change through Causal Analysis and LLM Interpretations
by: Shan, Shan
Published: (2024)

Practical Guide for Causal Pathways and Sub-group Disparity Analysis
by: Kohankhaki, Farnaz, et al.
Published: (2024)

Understanding overfitting in random forest for probability estimation: a visualization and simulation study
by: Barreñada, Lasai, et al.
Published: (2024)

Statistical Guarantees in the Search for Less Discriminatory Algorithms
by: Hays, Chris, et al.
Published: (2025)

Falsifying Predictive Algorithm
by: Coston, Amanda
Published: (2026)

Bias and Identifiability in the Bounded Confidence Model
by: Borile, Claudio, et al.
Published: (2025)

Comparing Data Assimilation and Likelihood-Based Inference on Latent State Estimation in Agent-Based Models
by: Kolic, Blas, et al.
Published: (2025)

Accounting for Missing Covariates in Heterogeneous Treatment Estimation
by: Yamin, Khurram, et al.
Published: (2024)

Learning Treatment Effects during Resource Allocation via Priority-Queue Randomization
by: Lee, JungHo, et al.
Published: (2026)

Who Are We Missing? A Principled Approach to Characterizing the Underrepresented Population
by: Parikh, Harsh, et al.
Published: (2024)

A Mixed-Methods Analysis of Repression and Mobilization in Bangladesh's July Revolution Using Machine Learning and Statistical Modeling
by: Siddiqui, Md. Saiful Bari, et al.
Published: (2025)

Discretion in the Loop: Human Expertise in Algorithm-Assisted College Advising
by: Schechtman, Kara, et al.
Published: (2025)