Copertina

A Data Envelopment Analysis Approach for Assessing Fairness in Resource Allocation: Application to Kidney Exchange Programs

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Kaazempur-Mofrad, Ali, Dai, Xiaowu
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computers and Society Machine Learning Methodology
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

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

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

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

Fairness-aware kidney exchange and kidney paired donation
di: Zhang, Mingrui, et al.
Pubblicazione: (2025)

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

Auditing Fairness under Unobserved Confounding
di: Byun, Yewon, et al.
Pubblicazione: (2024)

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

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

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

Post-Regularization Confidence Bands for Ordinary Differential Equations
di: Dai, Xiaowu, et al.
Pubblicazione: (2021)

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

A Statistical Market-Design Framework for Academic Job Markets
di: Kaazempur-Mofrad, Ali, et al.
Pubblicazione: (2026)

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

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

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

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

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

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

A Survey on Differential Privacy for SpatioTemporal Data in Transportation Research
di: Bhadani, Rahul
Pubblicazione: (2024)

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

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

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

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

Falsifying Predictive Algorithm
di: Coston, Amanda
Pubblicazione: (2026)

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

A Causal Analysis of CO2 Reduction Strategies in Electricity Markets Through Machine Learning-Driven Metalearners
di: Naeini, Iman Emtiazi, et al.
Pubblicazione: (2024)

DECAF: Learning to be Fair in Multi-agent Resource Allocation
di: Kumar, Ashwin, et al.
Pubblicazione: (2025)

Performance of models for monitoring sustainable development goals from remote sensing: A three-level meta-regression
di: Klingwort, Jonas, et al.
Pubblicazione: (2026)

Effect Decomposition of Functional-Output Computer Experiments via Orthogonal Additive Gaussian Processes
di: Tan, Yu, et al.
Pubblicazione: (2025)

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

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

Batch-Adaptive Causal Annotations
di: Nwankwo, Ezinne, et al.
Pubblicazione: (2025)

Interpretable Machine Learning for Resource Allocation with Application to Ventilator Triage
di: Grand-Clément, Julien, et al.
Pubblicazione: (2021)

De-amplifying Bias from Differential Privacy in Language Model Fine-tuning
di: Srivastava, Sanjari, et al.
Pubblicazione: (2024)

Decoding Digital Influence: The Role of Social Media Behavior in Scientific Stratification Through Logistic Attribution Method
di: Yue, Yang
Pubblicazione: (2024)

Ethnography and Machine Learning: Synergies and New Directions
di: Li, Zhuofan, et al.
Pubblicazione: (2024)

On the Unknowable Limits to Prediction
di: Yan, Jiani, et al.
Pubblicazione: (2024)

Revisiting the Berkeley Admissions data: Statistical Tests for Causal Hypotheses
di: Bhadane, Sourbh, et al.
Pubblicazione: (2025)

Counterfactual Explanations for Model Ensembles Using Entropic Risk Measures
di: Noorani, Erfaun, et al.
Pubblicazione: (2025)

Resource-constrained Fairness
di: Goethals, Sofie, et al.
Pubblicazione: (2024)