Image de couverture de livre

Friends in Unexpected Places: Enhancing Local Fairness in Federated Learning through Clustering

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Yang, Yifan, Payani, Ali, Naghizadeh, Parinaz
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning Computers and Society
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Generalization Error Bounds for Learning under Censored Feedback
par: Yang, Yifan, et autres
Publié: (2024)

Anticipating Gaming to Incentivize Improvement: Guiding Agents in (Fair) Strategic Classification
par: Alhanouti, Sura, et autres
Publié: (2025)

Adaptive Bounded Exploration and Intermediate Actions for Data Debiasing
par: Yang, Yifan, et autres
Publié: (2025)

Achieving Fairness Across Local and Global Models in Federated Learning
par: Makhija, Disha, et autres
Publié: (2024)

GLOCALFAIR: Jointly Improving Global and Local Group Fairness in Federated Learning
par: Meerza, Syed Irfan Ali, et autres
Publié: (2024)

The Cost of Local and Global Fairness in Federated Learning
par: Duan, Yuying, et autres
Publié: (2025)

Post-Fair Federated Learning: Achieving Group and Community Fairness in Federated Learning via Post-processing
par: Duan, Yuying, et autres
Publié: (2024)

BoostFGL: Boosting Fairness in Federated Graph Learning
par: Chen, Zekai, et autres
Publié: (2026)

The Double-Edged Sword of Behavioral Responses in Strategic Classification: Theory and User Studies
par: Ebrahimi, Raman, et autres
Publié: (2024)

Fairness in Federated Learning: Fairness for Whom?
par: Taik, Afaf, et autres
Publié: (2025)

Semi-Variance Reduction for Fair Federated Learning
par: Malekmohammadi, Saber, et autres
Publié: (2024)

Fairness in Federated Learning: Trends, Challenges, and Opportunities
par: Mukhtiar, Noorain, et autres
Publié: (2025)

Learning for Dynamic Combinatorial Optimization without Training Data
par: Liao, Yiqiao, et autres
Publié: (2025)

Distribution-Free Fair Federated Learning with Small Samples
par: Yin, Qichuan, et autres
Publié: (2024)

Boosting Fairness and Robustness in Over-the-Air Federated Learning
par: Oksuz, Halil Yigit, et autres
Publié: (2024)

The Fairness-Quality Trade-off in Clustering
par: Hakim, Rashida, et autres
Publié: (2024)

Training Fair Models in Federated Learning without Data Privacy Infringement
par: Che, Xin, et autres
Publié: (2021)

Enhancing Fairness through Reweighting: A Path to Attain the Sufficiency Rule
par: Zhao, Xuan, et autres
Publié: (2024)

FairSIN: Achieving Fairness in Graph Neural Networks through Sensitive Information Neutralization
par: Yang, Cheng, et autres
Publié: (2024)

Demystifying Local and Global Fairness Trade-offs in Federated Learning Using Partial Information Decomposition
par: Hamman, Faisal, et autres
Publié: (2023)

Test-Time Adaptation for Unsupervised Combinatorial Optimization
par: Liao, Yiqiao, et autres
Publié: (2026)

Enhancing Multi-Attribute Fairness in Healthcare Predictive Modeling
par: Wang, Xiaoyang, et autres
Publié: (2025)

FedCD: A Fairness-aware Federated Cognitive Diagnosis Framework
par: Yang, Shangshang, et autres
Publié: (2025)

Fairness-aware Federated Minimax Optimization with Convergence Guarantee
par: Dunda, Gerry Windiarto Mohamad, et autres
Publié: (2023)

What is Fair? Defining Fairness in Machine Learning for Health
par: Gao, Jianhui, et autres
Publié: (2024)

A Post-Processing-Based Fair Federated Learning Framework
par: Zhou, Yi, et autres
Publié: (2025)

Fair Clustering with Minimum Representation Constraints
par: Lawless, Connor, et autres
Publié: (2024)

AdapFair: Ensuring Adaptive Fairness for Machine Learning Operations
par: Huang, Yinghui, et autres
Publié: (2024)

The Fragility of Fairness: Causal Sensitivity Analysis for Fair Machine Learning
par: Fawkes, Jake, et autres
Publié: (2024)

Procedural Fairness and Its Relationship with Distributive Fairness in Machine Learning
par: Wang, Ziming, et autres
Publié: (2025)

Identifying Dealbreakers and Robust Policies for the Energy Transition Amid Unexpected Events
par: Coppitters, Diederik, et autres
Publié: (2025)

FedFair^3: Unlocking Threefold Fairness in Federated Learning
par: Javaherian, Simin, et autres
Publié: (2024)

Toward Fair Federated Learning under Demographic Disparities and Data Imbalance
par: Wu, Qiming, et autres
Publié: (2025)

Fair Sampling in Diffusion Models through Switching Mechanism
par: Choi, Yujin, et autres
Publié: (2024)

Algorithmic Fairness in Performative Policy Learning: Escaping the Impossibility of Group Fairness
par: Somerstep, Seamus, et autres
Publié: (2024)

FairBranch: Mitigating Bias Transfer in Fair Multi-task Learning
par: Roy, Arjun, et autres
Publié: (2023)

Learning Interpretable Fair Representations
par: Wang, Tianhao, et autres
Publié: (2024)

Secure and Confidential Certificates of Online Fairness
par: Franzese, Olive, et autres
Publié: (2024)

Debiasing Diffusion Model: Enhancing Fairness through Latent Representation Learning in Stable Diffusion Model
par: Huang, Lin-Chun, et autres
Publié: (2025)

A Computational Approach to Improving Fairness in K-means Clustering
par: Zhou, Guancheng, et autres
Publié: (2025)