{"total":75,"rows":[{"id":"2111.08834","title":"Federated Learning for Smart Healthcare: A Survey","created":"2021-11-16","cited_by_count":184,"area":null},{"id":"2108.10749","title":"Federated Learning for Open Banking","created":"2021-08-24","cited_by_count":141,"area":null},{"id":"2104.02151","title":"Distributed Learning in Wireless Networks: Recent Progress and Future Challenges","created":"2021-04-05","cited_by_count":129,"area":null},{"id":"2306.01603","title":"Decentralized Federated Learning: A Survey and Perspective","created":"2023-06-02","cited_by_count":86,"area":null},{"id":"2101.05428","title":"Federated Learning: Opportunities and Challenges","created":"2021-01-14","cited_by_count":84,"area":null},{"id":"2111.01872","title":"Towards Fairness-Aware Federated Learning","created":"2021-11-02","cited_by_count":58,"area":null},{"id":"2101.06905","title":"Blockchain Assisted Decentralized Federated Learning (BLADE-FL): Performance Analysis and Resource Allocation","created":"2021-01-18","cited_by_count":56,"area":null},{"id":"2111.11850","title":"Incentive Mechanisms for Federated Learning: From Economic and Game Theoretic Perspective","created":"2021-11-20","cited_by_count":47,"area":null},{"id":"2106.15406","title":"A Comprehensive Survey of Incentive Mechanism for Federated Learning","created":"2021-06-27","cited_by_count":38,"area":null},{"id":"2404.15381","title":"Advances and Open Challenges in Federated Foundation Models","created":"2024-04-23","cited_by_count":36,"area":null},{"id":"2203.09702","title":"Federated Learning for Privacy Preservation in Smart Healthcare Systems: A Comprehensive Survey","created":"2022-03-18","cited_by_count":31,"area":null},{"id":"2101.00798","title":"Fusion of Federated Learning and Industrial Internet of Things: A Survey","created":"2021-01-04","cited_by_count":29,"area":null},{"id":"2102.03401","title":"Federated Learning on the Road: Autonomous Controller Design for Connected and Autonomous Vehicles","created":"2021-02-05","cited_by_count":26,"area":null},{"id":"2106.13039","title":"Low-Latency Federated Learning over Wireless Channels with Differential Privacy","created":"2021-06-20","cited_by_count":25,"area":null},{"id":"2103.01953","title":"Privacy Amplification for Federated Learning via User Sampling and Wireless Aggregation","created":"2021-03-02","cited_by_count":22,"area":null},{"id":"2502.12176","title":"Ten Challenging Problems in Federated Foundation Models","created":"2025-02-14","cited_by_count":20,"area":"safety"},{"id":"2102.01375","title":"Applications of Federated Learning in Smart Cities: Recent Advances, Taxonomy, and Open Challenges","created":"2021-02-02","cited_by_count":17,"area":null},{"id":"2111.06290","title":"Fairness, Integrity, and Privacy in a Scalable Blockchain-based Federated Learning System","created":"2021-11-11","cited_by_count":16,"area":null},{"id":"2108.03980","title":"Decentralized Deep Learning for Multi-Access Edge Computing: A Survey on Communication Efficiency and Trustworthiness","created":"2021-07-30","cited_by_count":15,"area":null},{"id":"2205.07855","title":"Decentral and Incentivized Federated Learning Frameworks: A Systematic Literature Review","created":"2022-05-07","cited_by_count":15,"area":null},{"id":"2108.05568","title":"A Contract Theory based Incentive Mechanism for Federated Learning","created":"2021-08-12","cited_by_count":13,"area":null},{"id":"2202.07391","title":"Exploring Deep Reinforcement Learning-Assisted Federated Learning for Online Resource Allocation in Privacy-Persevering EdgeIoT","created":"2022-02-15","cited_by_count":12,"area":null},{"id":"2103.13266","title":"Opportunistic Federated Learning: An Exploration of Egocentric Collaboration for Pervasive Computing Applications","created":"2021-03-24","cited_by_count":11,"area":null},{"id":"2301.06646","title":"Async-HFL: Efficient and Robust Asynchronous Federated Learning in Hierarchical IoT Networks","created":"2023-01-17","cited_by_count":11,"area":null},{"id":"2109.06088","title":"Concept Drift Detection in Federated Networked Systems","created":"2021-09-13","cited_by_count":10,"area":null},{"id":"2110.07567","title":"Resource-constrained Federated Edge Learning with Heterogeneous Data: Formulation and Analysis","created":"2021-10-14","cited_by_count":10,"area":null},{"id":"2207.12030","title":"Collaboration in Participant-Centric Federated Learning: A Game-Theoretical Perspective","created":"2022-07-25","cited_by_count":9,"area":null},{"id":"2301.09732","title":"Backdoor Attacks in Peer-to-Peer Federated Learning","created":"2023-01-23","cited_by_count":9,"area":null},{"id":"2306.09433","title":"Towards Practical Federated Causal Structure Learning","created":"2023-06-15","cited_by_count":9,"area":null},{"id":"2209.04184","title":"Anomaly Detection through Unsupervised Federated Learning","created":"2022-09-09","cited_by_count":8,"area":null},{"id":"2304.07981","title":"Incentive Mechanism Design for Unbiased Federated Learning with Randomized Client Participation","created":"2023-04-17","cited_by_count":8,"area":null},{"id":"2101.00191","title":"Dynamic Federated Learning-Based Economic Framework for Internet-of-Vehicles","created":"2021-01-01","cited_by_count":7,"area":null},{"id":"2108.02712","title":"On Addressing Heterogeneity in Federated Learning for Autonomous Vehicles Connected to a Drone Orchestrator","created":"2021-08-05","cited_by_count":6,"area":null},{"id":"2212.11194","title":"Free-Rider Games for Federated Learning with Selfish Clients in NextG Wireless Networks","created":"2022-12-21","cited_by_count":6,"area":null},{"id":"2311.06801","title":"A Comprehensive Survey On Client Selections in Federated Learning","created":"2023-11-12","cited_by_count":6,"area":null},{"id":"2109.00202","title":"Federated Learning: Issues in Medical Application","created":"2021-09-01","cited_by_count":4,"area":null},{"id":"2204.03326","title":"Enabling All In-Edge Deep Learning: A Literature Review","created":"2022-04-07","cited_by_count":4,"area":null},{"id":"2210.02119","title":"ISFL: Federated Learning for Non-i.i.d. Data with Local Importance Sampling","created":"2022-10-05","cited_by_count":4,"area":null},{"id":"2312.04688","title":"Federated Learning for 6G: Paradigms, Taxonomy, Recent Advances and Insights","created":"2023-12-07","cited_by_count":4,"area":null},{"id":"2404.13244","title":"Intelligent Agents for Auction-based Federated Learning: A Survey","created":"2024-04-20","cited_by_count":4,"area":null},{"id":"2411.11764","title":"Freezing of Gait Detection Using Gramian Angular Fields and Federated Learning from Wearable Sensors","created":"2024-11-18","cited_by_count":4,"area":null},{"id":"2103.04014","title":"Over-the-Air Statistical Estimation","created":"2021-03-06","cited_by_count":3,"area":null},{"id":"2404.13278","title":"Federated Transfer Learning with Task Personalization for Condition Monitoring in Ultrasonic Metal Welding","created":"2024-04-20","cited_by_count":3,"area":null},{"id":"2106.09261","title":"Federated Learning Framework with Straggling Mitigation and Privacy-Awareness for AI-based Mobile Application Services","created":"2021-06-17","cited_by_count":2,"area":null},{"id":"2107.03428","title":"Management of Resource at the Network Edge for Federated Learning","created":"2021-07-07","cited_by_count":2,"area":null},{"id":"2110.06025","title":"Federated Phish Bowl: LSTM-Based Decentralized Phishing Email Detection","created":"2021-10-12","cited_by_count":2,"area":null},{"id":"2208.07194","title":"An Efficient and Reliable Asynchronous Federated Learning Scheme for Smart Public Transportation","created":"2022-08-15","cited_by_count":2,"area":null},{"id":"2307.00233","title":"Hierarchical Federated Learning Incentivization for Gas Usage Estimation","created":"2023-07-01","cited_by_count":2,"area":null},{"id":"2308.05292","title":"Byzantine-Robust Decentralized Stochastic Optimization with Stochastic Gradient Noise-Independent Learning Error","created":"2023-08-10","cited_by_count":2,"area":null},{"id":"2310.03823","title":"ECAvg: An Edge-Cloud Collaborative Learning Approach using Averaged Weights","created":"2023-10-05","cited_by_count":2,"area":null},{"id":"2103.07150","title":"Auction Based Clustered Federated Learning in Mobile Edge Computing System","created":"2021-03-12","cited_by_count":1,"area":null},{"id":"2103.08308","title":"Machine Learning for Massive Industrial Internet of Things","created":"2021-03-10","cited_by_count":1,"area":null},{"id":"2110.08330","title":"Nothing Wasted: Full Contribution Enforcement in Federated Edge Learning","created":"2021-10-15","cited_by_count":1,"area":null},{"id":"2207.00041","title":"DP$^2$-NILM: A Distributed and Privacy-preserving Framework for Non-intrusive Load Monitoring","created":"2022-06-30","cited_by_count":1,"area":null},{"id":"2209.06210","title":"Scheduling Algorithms for Federated Learning with Minimal Energy Consumption","created":"2022-09-13","cited_by_count":1,"area":null},{"id":"2303.10254","title":"Multi-Task Model Personalization for Federated Supervised SVM in Heterogeneous Networks","created":"2023-03-17","cited_by_count":1,"area":null},{"id":"2305.10852","title":"Q-SHED: Distributed Optimization at the Edge via Hessian Eigenvectors Quantization","created":"2023-05-18","cited_by_count":1,"area":null},{"id":"2410.09107","title":"Federated Learning for Data Market: Shapley-UCB for Seller Selection and Incentives","created":"2024-10-10","cited_by_count":1,"area":null},{"id":"2410.15620","title":"Acoustic Model Optimization over Multiple Data Sources: Merging and Valuation","created":"2024-10-21","cited_by_count":1,"area":null},{"id":"2104.06670","title":"Towards Explainable Multi-Party Learning: A Contrastive Knowledge Sharing Framework","created":"2021-04-14","cited_by_count":0,"area":null},{"id":"2310.02559","title":"Semi-Federated Learning: Convergence Analysis and Optimization of A Hybrid Learning Framework","created":"2023-10-04","cited_by_count":0,"area":null},{"id":"2311.10832","title":"Exploring Machine Learning Models for Federated Learning: A Review of Approaches, Performance, and Limitations","created":"2023-11-17","cited_by_count":0,"area":null},{"id":"2312.08096","title":"An Incentive Mechanism for Federated Learning Based on Multiple Resource Exchange","created":"2023-12-13","cited_by_count":0,"area":null},{"id":"2402.08769","title":"FLASH: Federated Learning Across Simultaneous Heterogeneities","created":"2024-02-13","cited_by_count":0,"area":null},{"id":"2408.10664","title":"Federated Clustering: An Unsupervised Cluster-Wise Training for Decentralized Data Distributions","created":"2024-08-20","cited_by_count":0,"area":null},{"id":"2409.11442","title":"A Green Multi-Attribute Client Selection for Over-The-Air Federated Learning: A Grey-Wolf-Optimizer Approach","created":"2024-09-16","cited_by_count":0,"area":null},{"id":"2411.11793","title":"Nonlinear Equilibrium Transitions in a Potential Game Model for Federated Learning","created":"2024-11-18","cited_by_count":0,"area":null},{"id":"2412.03950","title":"BEFL: Balancing Energy Consumption in Federated Learning for Mobile Edge IoT","created":"2024-12-05","cited_by_count":0,"area":null},{"id":"2502.09303","title":"Towards Seamless Hierarchical Federated Learning under Intermittent Client Participation: A Stagewise Decision-Making Methodology","created":"2025-02-13","cited_by_count":0,"area":null},{"id":"2505.21219","title":"Addressing Data Quality Decompensation in Federated Learning via Dynamic Client Selection","created":"2025-05-27","cited_by_count":0,"area":null},{"id":"2506.16731","title":"Incentivizing High-quality Participation From Federated Learning Agents","created":"2025-06-20","cited_by_count":0,"area":null},{"id":"2508.09181","title":"Long-Term Client Selection for Federated Learning with Non-IID Data: A Truthful Auction Approach","created":"2025-08-07","cited_by_count":0,"area":null},{"id":"2601.04648","title":"Mechanism Design for Federated Learning with Non-Monotonic Network Effects","created":"2026-01-08","cited_by_count":0,"area":null},{"id":"2609.15389","title":"A Game-Theoretic Framework for Incentive-Compatible AI training Under Renewable-Energy Constraints","created":"2026-09-14","cited_by_count":0,"area":null},{"id":"2609.19695","title":"Opinion Dynamics-based Coalition Formation for Federated Learning in Heterogeneous IoT Systems","created":"2026-09-17","cited_by_count":0,"area":null}],"next_cursor":null}