FairGT: A Fairness-aware Graph Transformer
Fuente:
arXiv
Guardado en:
| Autores principales: | Luo, Renqiang, Huang, Huafei, Yu, Shuo, Zhang, Xiuzhen, Xia, Feng |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
FUGNN: Harmonizing Fairness and Utility in Graph Neural Networks
por: Luo, Renqiang, et al.
Publicado: (2024)
por: Luo, Renqiang, et al.
Publicado: (2024)
FairGP: A Scalable and Fair Graph Transformer Using Graph Partitioning
por: Luo, Renqiang, et al.
Publicado: (2024)
por: Luo, Renqiang, et al.
Publicado: (2024)
FairGU: Fairness-aware Graph Unlearning in Social Networks
por: Luo, Renqiang, et al.
Publicado: (2026)
por: Luo, Renqiang, et al.
Publicado: (2026)
FairGC: Fairness-aware Graph Condensation
por: Gao, Yihan, et al.
Publicado: (2026)
por: Gao, Yihan, et al.
Publicado: (2026)
FairWire: Fair Graph Generation
por: Kose, O. Deniz, et al.
Publicado: (2024)
por: Kose, O. Deniz, et al.
Publicado: (2024)
FedCD: A Fairness-aware Federated Cognitive Diagnosis Framework
por: Yang, Shangshang, et al.
Publicado: (2025)
por: Yang, Shangshang, et al.
Publicado: (2025)
FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods
por: Han, Xiaotian, et al.
Publicado: (2023)
por: Han, Xiaotian, et al.
Publicado: (2023)
Adaptive Boosting with Fairness-aware Reweighting Technique for Fair Classification
por: Song, Xiaobin, et al.
Publicado: (2024)
por: Song, Xiaobin, et al.
Publicado: (2024)
Fairness in Graph Learning Augmented with Machine Learning: A Survey
por: Luo, Renqiang, et al.
Publicado: (2025)
por: Luo, Renqiang, et al.
Publicado: (2025)
Fairness-aware Federated Minimax Optimization with Convergence Guarantee
por: Dunda, Gerry Windiarto Mohamad, et al.
Publicado: (2023)
por: Dunda, Gerry Windiarto Mohamad, et al.
Publicado: (2023)
FairHome: A Fair Housing and Fair Lending Dataset
por: Bagalkotkar, Anusha, et al.
Publicado: (2024)
por: Bagalkotkar, Anusha, et al.
Publicado: (2024)
FairFedMed: Benchmarking Group Fairness in Federated Medical Imaging with FairLoRA
por: Li, Minghan, et al.
Publicado: (2025)
por: Li, Minghan, et al.
Publicado: (2025)
AdapFair: Ensuring Adaptive Fairness for Machine Learning Operations
por: Huang, Yinghui, et al.
Publicado: (2024)
por: Huang, Yinghui, et al.
Publicado: (2024)
FairPFN: Transformers Can do Counterfactual Fairness
por: Robertson, Jake, et al.
Publicado: (2024)
por: Robertson, Jake, et al.
Publicado: (2024)
Fairness-Aware Graph Representation Learning with Limited Demographic Information
por: Wang, Zichong, et al.
Publicado: (2025)
por: Wang, Zichong, et al.
Publicado: (2025)
FairSIN: Achieving Fairness in Graph Neural Networks through Sensitive Information Neutralization
por: Yang, Cheng, et al.
Publicado: (2024)
por: Yang, Cheng, et al.
Publicado: (2024)
Procedural Fairness and Its Relationship with Distributive Fairness in Machine Learning
por: Wang, Ziming, et al.
Publicado: (2025)
por: Wang, Ziming, et al.
Publicado: (2025)
Fair Machine Learning in Healthcare: A Review
por: Feng, Qizhang, et al.
Publicado: (2022)
por: Feng, Qizhang, et al.
Publicado: (2022)
Algorithmic Fairness: A Tolerance Perspective
por: Luo, Renqiang, et al.
Publicado: (2024)
por: Luo, Renqiang, et al.
Publicado: (2024)
An Experimental Study on Fairness-aware Machine Learning for Credit Scoring Problems
por: Thu, Huyen Giang Thi, et al.
Publicado: (2024)
por: Thu, Huyen Giang Thi, et al.
Publicado: (2024)
BoostFGL: Boosting Fairness in Federated Graph Learning
por: Chen, Zekai, et al.
Publicado: (2026)
por: Chen, Zekai, et al.
Publicado: (2026)
On Demographic Group Fairness Guarantees in Deep Learning
por: Luo, Yan, et al.
Publicado: (2024)
por: Luo, Yan, et al.
Publicado: (2024)
Unraveling Privacy Risks of Individual Fairness in Graph Neural Networks
por: Zhang, He, et al.
Publicado: (2023)
por: Zhang, He, et al.
Publicado: (2023)
Fairness and/or Privacy on Social Graphs
por: Surma, Bartlomiej, et al.
Publicado: (2025)
por: Surma, Bartlomiej, et al.
Publicado: (2025)
SimFair: Physics-Guided Fairness-Aware Learning with Simulation Models
por: Wang, Zhihao, et al.
Publicado: (2024)
por: Wang, Zhihao, et al.
Publicado: (2024)
Navigating Towards Fairness with Data Selection
por: Zhang, Yixuan, et al.
Publicado: (2024)
por: Zhang, Yixuan, et al.
Publicado: (2024)
FairPFN: A Tabular Foundation Model for Causal Fairness
por: Robertson, Jake, et al.
Publicado: (2025)
por: Robertson, Jake, et al.
Publicado: (2025)
GFairHint: Improving Individual Fairness for Graph Neural Networks via Fairness Hint
por: Xu, Paiheng, et al.
Publicado: (2023)
por: Xu, Paiheng, et al.
Publicado: (2023)
Counterfactual Fairness with Graph Uncertainty
por: Valério, Davi, et al.
Publicado: (2026)
por: Valério, Davi, et al.
Publicado: (2026)
Fair Submodular Cover
por: Chen, Wenjing, et al.
Publicado: (2024)
por: Chen, Wenjing, et al.
Publicado: (2024)
What is Fair? Defining Fairness in Machine Learning for Health
por: Gao, Jianhui, et al.
Publicado: (2024)
por: Gao, Jianhui, et al.
Publicado: (2024)
FairSample: Training Fair and Accurate Graph Convolutional Neural Networks Efficiently
por: Cong, Zicun, et al.
Publicado: (2024)
por: Cong, Zicun, et al.
Publicado: (2024)
Toward Fair Graph Neural Networks Via Dual-Teacher Knowledge Distillation
por: Li, Chengyu, et al.
Publicado: (2024)
por: Li, Chengyu, et al.
Publicado: (2024)
How Robust is your Fair Model? Exploring the Robustness of Diverse Fairness Strategies
por: Small, Edward, et al.
Publicado: (2022)
por: Small, Edward, et al.
Publicado: (2022)
Bias Mitigation in Fine-tuning Pre-trained Models for Enhanced Fairness and Efficiency
por: Zhang, Yixuan, et al.
Publicado: (2024)
por: Zhang, Yixuan, et al.
Publicado: (2024)
The Fragility of Fairness: Causal Sensitivity Analysis for Fair Machine Learning
por: Fawkes, Jake, et al.
Publicado: (2024)
por: Fawkes, Jake, et al.
Publicado: (2024)
Fair for a few: Improving Fairness in Doubly Imbalanced Datasets
por: Yalcin, Ata, et al.
Publicado: (2025)
por: Yalcin, Ata, et al.
Publicado: (2025)
Be Intentional About Fairness!: Fairness, Size, and Multiplicity in the Rashomon Set
por: Dai, Gordon, et al.
Publicado: (2025)
por: Dai, Gordon, et al.
Publicado: (2025)
FairDD: Enhancing Fairness with domain-incremental learning in dermatological disease diagnosis
por: Luo, Yiqin, et al.
Publicado: (2024)
por: Luo, Yiqin, et al.
Publicado: (2024)
Effort-aware Fairness: Incorporating a Philosophy-informed, Human-centered Notion of Effort into Algorithmic Fairness Metrics
por: Nguyen, Tin Trung, et al.
Publicado: (2025)
por: Nguyen, Tin Trung, et al.
Publicado: (2025)
Ejemplares similares
-
FUGNN: Harmonizing Fairness and Utility in Graph Neural Networks
por: Luo, Renqiang, et al.
Publicado: (2024) -
FairGP: A Scalable and Fair Graph Transformer Using Graph Partitioning
por: Luo, Renqiang, et al.
Publicado: (2024) -
FairGU: Fairness-aware Graph Unlearning in Social Networks
por: Luo, Renqiang, et al.
Publicado: (2026) -
FairGC: Fairness-aware Graph Condensation
por: Gao, Yihan, et al.
Publicado: (2026) -
FairWire: Fair Graph Generation
por: Kose, O. Deniz, et al.
Publicado: (2024)