Saved in:
| Main Authors: | Hou, Aryana, Lin, Li, Li, Justin, Hu, Shu |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.14326 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Preserving Fairness Generalization in Deepfake Detection
by: Lin, Li, et al.
Published: (2024)
by: Lin, Li, et al.
Published: (2024)
Robust Fair Disease Diagnosis in CT Images
by: Li, Justin, et al.
Published: (2026)
by: Li, Justin, et al.
Published: (2026)
Analyzing Fairness in Deepfake Detection With Massively Annotated Databases
by: Xu, Ying, et al.
Published: (2022)
by: Xu, Ying, et al.
Published: (2022)
Data-Driven Fairness Generalization for Deepfake Detection
by: Ezeakunne, Uzoamaka, et al.
Published: (2024)
by: Ezeakunne, Uzoamaka, et al.
Published: (2024)
Monotone Individual Fairness
by: Bechavod, Yahav
Published: (2024)
by: Bechavod, Yahav
Published: (2024)
Efficient k-means with Individual Fairness via Exponential Tilting
by: Zhu, Shengkun, et al.
Published: (2024)
by: Zhu, Shengkun, et al.
Published: (2024)
Causal Fair Metric: Bridging Causality, Individual Fairness, and Adversarial Robustness
by: Ehyaei, Ahmad-Reza, et al.
Published: (2023)
by: Ehyaei, Ahmad-Reza, et al.
Published: (2023)
On the (In)Compatibility between Group Fairness and Individual Fairness
by: Xu, Shizhou, et al.
Published: (2024)
by: Xu, Shizhou, et al.
Published: (2024)
Rethinking Fair Representation Learning for Performance-Sensitive Tasks
by: Jones, Charles, et al.
Published: (2024)
by: Jones, Charles, et al.
Published: (2024)
Rethinking Fair Graph Neural Networks from Re-balancing
by: Li, Zhixun, et al.
Published: (2024)
by: Li, Zhixun, et al.
Published: (2024)
Bridging the Fairness Divide: Achieving Group and Individual Fairness in Graph Neural Networks
by: Zhan, Duna, et al.
Published: (2024)
by: Zhan, Duna, et al.
Published: (2024)
Perturbation Effects on Accuracy and Fairness among Similar Individuals
by: Li, Xuran, et al.
Published: (2024)
by: Li, Xuran, et al.
Published: (2024)
One Size Fits None: Rethinking Fairness in Medical AI
by: Roller, Roland, et al.
Published: (2025)
by: Roller, Roland, et al.
Published: (2025)
Unraveling Privacy Risks of Individual Fairness in Graph Neural Networks
by: Zhang, He, et al.
Published: (2023)
by: Zhang, He, et al.
Published: (2023)
Counterpart Fairness -- Addressing Systematic between-group Differences in Fairness Evaluation
by: Wang, Yifei, et al.
Published: (2023)
by: Wang, Yifei, 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)
by: Benítez-Peña, Sandra, et al.
Published: (2026)
Fair CCA for Fair Representation Learning: An ADNI Study
by: Hou, Bojian, et al.
Published: (2025)
by: Hou, Bojian, et al.
Published: (2025)
Equalised Odds is not Equal Individual Odds: Post-processing for Group and Individual Fairness
by: Small, Edward A., et al.
Published: (2023)
by: Small, Edward A., et al.
Published: (2023)
GFairHint: Improving Individual Fairness for Graph Neural Networks via Fairness Hint
by: Xu, Paiheng, et al.
Published: (2023)
by: Xu, Paiheng, et al.
Published: (2023)
A Scalable Algorithm for Individually Fair K-means Clustering
by: Bateni, MohammadHossein, et al.
Published: (2024)
by: Bateni, MohammadHossein, et al.
Published: (2024)
Multi-Output Distributional Fairness via Post-Processing
by: Li, Gang, et al.
Published: (2024)
by: Li, Gang, et al.
Published: (2024)
BoostFGL: Boosting Fairness in Federated Graph Learning
by: Chen, Zekai, et al.
Published: (2026)
by: Chen, Zekai, et al.
Published: (2026)
Fairness in Multi-Task Learning via Wasserstein Barycenters
by: Hu, François, et al.
Published: (2023)
by: Hu, François, et al.
Published: (2023)
A Sequentially Fair Mechanism for Multiple Sensitive Attributes
by: Hu, François, et al.
Published: (2023)
by: Hu, François, et al.
Published: (2023)
Fairness Risks for Group-conditionally Missing Demographics
by: Jiang, Kaiqi, et al.
Published: (2024)
by: Jiang, Kaiqi, et al.
Published: (2024)
Fairness Hub Technical Briefs: Definition and Detection of Distribution Shift
by: Acevedo, Nicolas, et al.
Published: (2024)
by: Acevedo, Nicolas, et al.
Published: (2024)
FairHome: A Fair Housing and Fair Lending Dataset
by: Bagalkotkar, Anusha, et al.
Published: (2024)
by: Bagalkotkar, Anusha, et al.
Published: (2024)
FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods
by: Han, Xiaotian, et al.
Published: (2023)
by: Han, Xiaotian, et al.
Published: (2023)
Navigating Towards Fairness with Data Selection
by: Zhang, Yixuan, et al.
Published: (2024)
by: Zhang, Yixuan, et al.
Published: (2024)
Fair Text-to-Image Diffusion via Fair Mapping
by: Li, Jia, et al.
Published: (2023)
by: Li, Jia, et al.
Published: (2023)
FairWire: Fair Graph Generation
by: Kose, O. Deniz, et al.
Published: (2024)
by: Kose, O. Deniz, et al.
Published: (2024)
Migrate Demographic Group For Fair GNNs
by: Hu, YanMing, et al.
Published: (2023)
by: Hu, YanMing, et al.
Published: (2023)
Toward Fair Graph Neural Networks Via Dual-Teacher Knowledge Distillation
by: Li, Chengyu, et al.
Published: (2024)
by: Li, Chengyu, et al.
Published: (2024)
Provable Optimization for Adversarial Fair Self-supervised Contrastive Learning
by: Qi, Qi, et al.
Published: (2024)
by: Qi, Qi, et al.
Published: (2024)
Measuring Individual User Fairness with User Similarity and Effectiveness Disparity
by: Rampisela, Theresia Veronika, et al.
Published: (2026)
by: Rampisela, Theresia Veronika, et al.
Published: (2026)
Long-Term Fair Decision Making through Deep Generative Models
by: Hu, Yaowei, et al.
Published: (2024)
by: Hu, Yaowei, et al.
Published: (2024)
FairRAG: Fair Human Generation via Fair Retrieval Augmentation
by: Shrestha, Robik, et al.
Published: (2024)
by: Shrestha, Robik, et al.
Published: (2024)
FairSHAP: Preprocessing for Fairness Through Attribution-Based Data Augmentation
by: Zhu, Lin, et al.
Published: (2025)
by: Zhu, Lin, et al.
Published: (2025)
Towards Harmless Rawlsian Fairness Regardless of Demographic Prior
by: Wang, Xuanqian, et al.
Published: (2024)
by: Wang, Xuanqian, et al.
Published: (2024)
Supervised Algorithmic Fairness in Distribution Shifts: A Survey
by: Shao, Minglai, et al.
Published: (2024)
by: Shao, Minglai, et al.
Published: (2024)
Similar Items
-
Preserving Fairness Generalization in Deepfake Detection
by: Lin, Li, et al.
Published: (2024) -
Robust Fair Disease Diagnosis in CT Images
by: Li, Justin, et al.
Published: (2026) -
Analyzing Fairness in Deepfake Detection With Massively Annotated Databases
by: Xu, Ying, et al.
Published: (2022) -
Data-Driven Fairness Generalization for Deepfake Detection
by: Ezeakunne, Uzoamaka, et al.
Published: (2024) -
Monotone Individual Fairness
by: Bechavod, Yahav
Published: (2024)