CAFIN: Centrality Aware Fairness inducing IN-processing for Unsupervised Representation Learning on Graphs
Fuente:
arXiv
Saved in:
| Main Authors: | Arun, Arvindh, Aanegola, Aakash, Agrawal, Amul, Narayanam, Ramasuri, Kumaraguru, Ponnurangam |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Cognac Shot To Forget Bad Memories: Corrective Unlearning for Graph Neural Networks
by: Kolipaka, Varshita, et al.
Published: (2024)
by: Kolipaka, Varshita, et al.
Published: (2024)
SEMMA: A Semantic Aware Knowledge Graph Foundation Model
by: Arun, Arvindh, et al.
Published: (2025)
by: Arun, Arvindh, et al.
Published: (2025)
HLDC: Hindi Legal Documents Corpus
by: Kapoor, Arnav, et al.
Published: (2022)
by: Kapoor, Arnav, et al.
Published: (2022)
Analyzing Patterns and Influence of Advertising in Print Newspapers
by: Vardhan, N Harsha, et al.
Published: (2025)
by: Vardhan, N Harsha, et al.
Published: (2025)
Fair CCA for Fair Representation Learning: An ADNI Study
by: Hou, Bojian, et al.
Published: (2025)
by: Hou, Bojian, et al.
Published: (2025)
Learning Fairer Representations with FairVIC
by: Barker, Charmaine, et al.
Published: (2024)
by: Barker, Charmaine, et al.
Published: (2024)
SimFair: Physics-Guided Fairness-Aware Learning with Simulation Models
by: Wang, Zhihao, et al.
Published: (2024)
by: Wang, Zhihao, et al.
Published: (2024)
X-posing Free Speech: Examining the Impact of Moderation Relaxation on Online Social Networks
by: Arun, Arvindh, et al.
Published: (2024)
by: Arun, Arvindh, et al.
Published: (2024)
Causal Manifold Fairness: Enforcing Geometric Invariance in Representation Learning
by: Rathore, Vidhi
Published: (2026)
by: Rathore, Vidhi
Published: (2026)
Dynamic Environment Responsive Online Meta-Learning with Fairness Awareness
by: Zhao, Chen, et al.
Published: (2024)
by: Zhao, Chen, et al.
Published: (2024)
Learning Fair Invariant Representations under Covariate and Correlation Shifts Simultaneously
by: Li, Dong, et al.
Published: (2024)
by: Li, Dong, et al.
Published: (2024)
Fairness-Aware Interpretable Modeling (FAIM) for Trustworthy Machine Learning in Healthcare
by: Liu, Mingxuan, et al.
Published: (2024)
by: Liu, Mingxuan, et al.
Published: (2024)
Are There Exceptions to Goodhart's Law? On the Moral Justification of Fairness-Aware Machine Learning
by: Weerts, Hilde, et al.
Published: (2022)
by: Weerts, Hilde, et al.
Published: (2022)
Counterfactual Fairness with Graph Uncertainty
by: Valério, Davi, et al.
Published: (2026)
by: Valério, Davi, et al.
Published: (2026)
I Can't Believe It's Corrupt: Evaluating Corruption in Multi-Agent Governance Systems
by: P, Vedanta S, et al.
Published: (2026)
by: P, Vedanta S, et al.
Published: (2026)
Fairness in Federated Learning: Fairness for Whom?
by: Taik, Afaf, et al.
Published: (2025)
by: Taik, Afaf, et al.
Published: (2025)
FairSample: Training Fair and Accurate Graph Convolutional Neural Networks Efficiently
by: Cong, Zicun, et al.
Published: (2024)
by: Cong, Zicun, et al.
Published: (2024)
FairMT: Fairness for Heterogeneous Multi-Task Learning
by: Hu, Guanyu, et al.
Published: (2025)
by: Hu, Guanyu, et al.
Published: (2025)
Rethinking Fair Graph Neural Networks from Re-balancing
by: Li, Zhixun, et al.
Published: (2024)
by: Li, Zhixun, et al.
Published: (2024)
Agentic AI and the Cyber Arms Race
by: Oesch, Sean, et al.
Published: (2025)
by: Oesch, Sean, et al.
Published: (2025)
On The Fairness Impacts of Hardware Selection in Machine Learning
by: Nelaturu, Sree Harsha, et al.
Published: (2023)
by: Nelaturu, Sree Harsha, et al.
Published: (2023)
Tuning Derivatives for Causal Fairness in Machine Learning
by: Edström, Filip, et al.
Published: (2026)
by: Edström, Filip, et al.
Published: (2026)
Fair Machine Learning in Healthcare: A Review
by: Feng, Qizhang, et al.
Published: (2022)
by: Feng, Qizhang, et al.
Published: (2022)
The Cost of Local and Global Fairness in Federated Learning
by: Duan, Yuying, et al.
Published: (2025)
by: Duan, Yuying, et al.
Published: (2025)
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)
Multilingual Non-Factoid Question Answering with Answer Paragraph Selection
by: Mishra, Ritwik, et al.
Published: (2024)
by: Mishra, Ritwik, et al.
Published: (2024)
Integrating Social Determinants of Health into Knowledge Graphs: Evaluating Prediction Bias and Fairness in Healthcare
by: Shang, Tianqi, et al.
Published: (2024)
by: Shang, Tianqi, et al.
Published: (2024)
Developing Fairness-Aware Task Decomposition to Improve Equity in Post-Spinal Fusion Complication Prediction
by: Yuan, Yining, et al.
Published: (2025)
by: Yuan, Yining, et al.
Published: (2025)
End-to-End Optimization and Learning of Fair Court Schedules
by: Dinh, My H, et al.
Published: (2024)
by: Dinh, My H, et al.
Published: (2024)
Representation Surgery: Theory and Practice of Affine Steering
by: Singh, Shashwat, et al.
Published: (2024)
by: Singh, Shashwat, et al.
Published: (2024)
FACTER: Fairness-Aware Conformal Thresholding and Prompt Engineering for Enabling Fair LLM-Based Recommender Systems
by: Fayyazi, Arya, et al.
Published: (2025)
by: Fayyazi, Arya, et al.
Published: (2025)
OxonFair: A Flexible Toolkit for Algorithmic Fairness
by: Delaney, Eoin, et al.
Published: (2024)
by: Delaney, Eoin, et al.
Published: (2024)
FairPFN: Transformers Can do Counterfactual Fairness
by: Robertson, Jake, et al.
Published: (2024)
by: Robertson, Jake, et al.
Published: (2024)
A Post-Processing-Based Fair Federated Learning Framework
by: Zhou, Yi, et al.
Published: (2025)
by: Zhou, Yi, et al.
Published: (2025)
BiasGuard: Guardrailing Fairness in Machine Learning Production Systems
by: Cohen-Inger, Nurit, et al.
Published: (2025)
by: Cohen-Inger, Nurit, et al.
Published: (2025)
FairFML: Fair Federated Machine Learning with a Case Study on Reducing Gender Disparities in Cardiac Arrest Outcome Prediction
by: Li, Siqi, et al.
Published: (2024)
by: Li, Siqi, et al.
Published: (2024)
Learning Representational Disparities
by: Ravishankar, Pavan, et al.
Published: (2025)
by: Ravishankar, Pavan, et al.
Published: (2025)
Remembering to Be Fair: Non-Markovian Fairness in Sequential Decision Making
by: Alamdari, Parand A., et al.
Published: (2023)
by: Alamdari, Parand A., et al.
Published: (2023)
What Is the Point of Equality in Machine Learning Fairness? Beyond Equality of Opportunity
by: Kong, Youjin
Published: (2025)
by: Kong, Youjin
Published: (2025)
Toward Fair Federated Learning under Demographic Disparities and Data Imbalance
by: Wu, Qiming, et al.
Published: (2025)
by: Wu, Qiming, et al.
Published: (2025)
Similar Items
-
A Cognac Shot To Forget Bad Memories: Corrective Unlearning for Graph Neural Networks
by: Kolipaka, Varshita, et al.
Published: (2024) -
SEMMA: A Semantic Aware Knowledge Graph Foundation Model
by: Arun, Arvindh, et al.
Published: (2025) -
HLDC: Hindi Legal Documents Corpus
by: Kapoor, Arnav, et al.
Published: (2022) -
Analyzing Patterns and Influence of Advertising in Print Newspapers
by: Vardhan, N Harsha, et al.
Published: (2025) -
Fair CCA for Fair Representation Learning: An ADNI Study
by: Hou, Bojian, et al.
Published: (2025)