Cover Image

On Demographic Group Fairness Guarantees in Deep Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Luo, Yan, Wen, Congcong, Shi, Min, Huang, Hao, Fang, Yi, Wang, Mengyu
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

FairFedMed: Benchmarking Group Fairness in Federated Medical Imaging with FairLoRA
by: Li, Minghan, et al.
Published: (2025)

Migrate Demographic Group For Fair GNNs
by: Hu, YanMing, et al.
Published: (2023)

Fairness Risks for Group-conditionally Missing Demographics
by: Jiang, Kaiqi, et al.
Published: (2024)

TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction
by: Gheisi, Leila, et al.
Published: (2024)

Fairness-Aware Graph Representation Learning with Limited Demographic Information
by: Wang, Zichong, et al.
Published: (2025)

Hidden or Inferred: Fair Learning-To-Rank with Unknown Demographics
by: Olulana, Oluseun, et al.
Published: (2024)

Towards Harmless Rawlsian Fairness Regardless of Demographic Prior
by: Wang, Xuanqian, et al.
Published: (2024)

Transferring Fairness using Multi-Task Learning with Limited Demographic Information
by: Aguirre, Carlos, et al.
Published: (2023)

Counterfactual Fairness Is Not Demographic Parity, and Other Observations
by: Silva, Ricardo
Published: (2024)

Learning With Multi-Group Guarantees For Clusterable Subpopulations
by: Dai, Jessica, et al.
Published: (2024)

FairDiffusion: Enhancing Equity in Latent Diffusion Models via Fair Bayesian Perturbation
by: Luo, Yan, et al.
Published: (2024)

Achievable Fairness on Your Data With Utility Guarantees
by: Taufiq, Muhammad Faaiz, et al.
Published: (2024)

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

Demo2Vec: Learning Region Embedding with Demographic Information
by: Wen, Ya, et al.
Published: (2024)

Fairness-aware Federated Minimax Optimization with Convergence Guarantee
by: Dunda, Gerry Windiarto Mohamad, et al.
Published: (2023)

Toward Fair Federated Learning under Demographic Disparities and Data Imbalance
by: Wu, Qiming, et al.
Published: (2025)

Post-Fair Federated Learning: Achieving Group and Community Fairness in Federated Learning via Post-processing
by: Duan, Yuying, et al.
Published: (2024)

Procedural Fairness and Its Relationship with Distributive Fairness in Machine Learning
by: Wang, Ziming, et al.
Published: (2025)

Positive-Sum Fairness: Leveraging Demographic Attributes to Achieve Fair AI Outcomes Without Sacrificing Group Gains
by: Belhadj, Samia, et al.
Published: (2024)

Minimax Optimal Fair Classification with Bounded Demographic Disparity
by: Zeng, Xianli, et al.
Published: (2024)

FairGT: A Fairness-aware Graph Transformer
by: Luo, Renqiang, et al.
Published: (2024)

AI Fairness Beyond Complete Demographics: Current Achievements and Future Directions
by: Wang, Zichong, et al.
Published: (2025)

FairSIN: Achieving Fairness in Graph Neural Networks through Sensitive Information Neutralization
by: Yang, Cheng, et al.
Published: (2024)

AdapFair: Ensuring Adaptive Fairness for Machine Learning Operations
by: Huang, Yinghui, et al.
Published: (2024)

FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods
by: Han, Xiaotian, et al.
Published: (2023)

Trade-offs Between Individual and Group Fairness in Machine Learning: A Comprehensive Review
by: Benítez-Peña, Sandra, et al.
Published: (2026)

Distribution-Free Fair Federated Learning with Small Samples
by: Yin, Qichuan, et al.
Published: (2024)

On the (In)Compatibility between Group Fairness and Individual Fairness
by: Xu, Shizhou, et al.
Published: (2024)

Learning Interpretable Fair Representations
by: Wang, Tianhao, et al.
Published: (2024)

KG-FairDiff: Knowledge Graph-Guided Prompt Refinement for Demographically Fair Text-to-Image Generation
by: Davoodi, Farbod, et al.
Published: (2026)

A Unified Post-Processing Framework for Group Fairness in Classification
by: Xian, Ruicheng, et al.
Published: (2024)

FRAPPE: A Group Fairness Framework for Post-Processing Everything
by: Tifrea, Alexandru, et al.
Published: (2023)

FedCD: A Fairness-aware Federated Cognitive Diagnosis Framework
by: Yang, Shangshang, et al.
Published: (2025)

A Self-Supervised Learning Pipeline for Demographically Fair Facial Attribute Classification
by: Ramachandran, Sreeraj, et al.
Published: (2024)

Debiasing Diffusion Model: Enhancing Fairness through Latent Representation Learning in Stable Diffusion Model
by: Huang, Lin-Chun, et al.
Published: (2025)

Navigating Towards Fairness with Data Selection
by: Zhang, Yixuan, et al.
Published: (2024)

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

Identities are not Interchangeable: The Problem of Overgeneralization in Fair Machine Learning
by: Wang, Angelina
Published: (2025)

GLOCALFAIR: Jointly Improving Global and Local Group Fairness in Federated Learning
by: Meerza, Syed Irfan Ali, et al.
Published: (2024)

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