{"total":20,"rows":[{"id":"2402.15638","title":"Fair Resource Allocation in Multi-Task Learning","created":"2024-02-23","cited_by_count":35,"area":null},{"id":"2406.03519","title":"Noise-Aware Algorithm for Heterogeneous Differentially Private Federated Learning","created":"2024-06-05","cited_by_count":9,"area":null},{"id":"2306.00324","title":"Achieving Fairness in Multi-Agent Markov Decision Processes Using Reinforcement Learning","created":"2023-06-01","cited_by_count":8,"area":null},{"id":"2307.13381","title":"Scaff-PD: Communication Efficient Fair and Robust Federated Learning","created":"2023-07-25","cited_by_count":6,"area":null},{"id":"2406.17102","title":"Achieving Fairness Across Local and Global Models in Federated Learning","created":"2024-06-24","cited_by_count":5,"area":null},{"id":"2301.12407","title":"Entropy-driven Fair and Effective Federated Learning","created":"2023-01-29","cited_by_count":4,"area":null},{"id":"2309.14176","title":"Federated Learning Under Restricted User Availability","created":"2023-09-25","cited_by_count":4,"area":null},{"id":"2405.19272","title":"Differentially Private Clustered Federated Learning","created":"2024-05-29","cited_by_count":4,"area":null},{"id":"2409.19431","title":"Generalization and Robustness of the Tilted Empirical Risk","created":"2024-09-28","cited_by_count":4,"area":null},{"id":"2410.21764","title":"Adaptive Online Mirror Descent for Tchebycheff Scalarization in Multi-Objective Learning","created":"2024-10-29","cited_by_count":4,"area":null},{"id":"2308.09565","title":"Understanding the Role of Layer Normalization in Label-Skewed Federated Learning","created":"2023-08-18","cited_by_count":2,"area":null},{"id":"2405.20821","title":"Pursuing Overall Welfare in Federated Learning through Sequential Decision Making","created":"2024-05-31","cited_by_count":2,"area":null},{"id":"2504.15924","title":"Achieving Distributive Justice in Federated Learning via Uncertainty Quantification","created":"2025-04-22","cited_by_count":2,"area":null},{"id":"2401.01383","title":"Predicting Infant Brain Connectivity with Federated Multi-Trajectory GNNs using Scarce Data","created":"2024-01-01","cited_by_count":1,"area":null},{"id":"2407.19331","title":"Friends in Unexpected Places: Enhancing Local Fairness in Federated Learning through Clustering","created":"2024-07-27","cited_by_count":1,"area":null},{"id":"2410.20141","title":"FedMABA: Towards Fair Federated Learning through Multi-Armed Bandits Allocation","created":"2024-10-26","cited_by_count":1,"area":null},{"id":"2412.11646","title":"Information-Geometric Barycenters for Bayesian Federated Learning","created":"2024-12-16","cited_by_count":1,"area":null},{"id":"2503.16836","title":"A Flexible Fairness Framework with Surrogate Loss Reweighting for Addressing Sociodemographic Disparities","created":"2025-03-21","cited_by_count":0,"area":null},{"id":"2509.10132","title":"Cost-Free Personalization via Information-Geometric Projection in Bayesian Federated Learning","created":"2025-09-12","cited_by_count":0,"area":null},{"id":"2610.20264","title":"FUSE: Fairness-aware Update Screening against Byzantine Exploitation in $q$-Fair Federated Learning","created":"2026-10-14","cited_by_count":0,"area":null}],"next_cursor":null}