Blockchain-based Framework for Scalable and Incentivized Federated Learning
Fuente:
arXiv
Guardado en:
| Autores principales: | Wu, Bijun, Seneviratne, Oshani |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Blockchain-Enabled Federated Learning
por: Rangwala, Murtaza, et al.
Publicado: (2025)
por: Rangwala, Murtaza, et al.
Publicado: (2025)
Incentive-Compatible Federated Learning with Stackelberg Game Modeling
por: Javaherian, Simin, et al.
Publicado: (2025)
por: Javaherian, Simin, et al.
Publicado: (2025)
Spectral Sentinel: Scalable Byzantine-Robust Decentralized Federated Learning via Sketched Random Matrix Theory on Blockchain
por: Mishra, Animesh
Publicado: (2025)
por: Mishra, Animesh
Publicado: (2025)
Incentive-Based Federated Learning: Architectural Elements and Future Directions
por: Kaluannakkage, Chanuka A. S. Hewa, et al.
Publicado: (2025)
por: Kaluannakkage, Chanuka A. S. Hewa, et al.
Publicado: (2025)
FEDBUD: Joint Incentive and Privacy Optimization for Resource-Constrained Federated Learning
por: Liu, Tao, et al.
Publicado: (2026)
por: Liu, Tao, et al.
Publicado: (2026)
Federated Learning Framework for Scalable AI in Heterogeneous HPC and Cloud Environments
por: Ghimire, Sangam, et al.
Publicado: (2025)
por: Ghimire, Sangam, et al.
Publicado: (2025)
Federated Koopman-Reservoir Learning for Large-Scale Multivariate Time-Series Anomaly Detection
por: Le, Long Tan, et al.
Publicado: (2025)
por: Le, Long Tan, et al.
Publicado: (2025)
A Bayesian Framework for Clustered Federated Learning
por: Wu, Peng, et al.
Publicado: (2024)
por: Wu, Peng, et al.
Publicado: (2024)
Federated Deep Equilibrium Learning: Harnessing Compact Global Representations to Enhance Personalization
por: Le, Long Tan, et al.
Publicado: (2023)
por: Le, Long Tan, et al.
Publicado: (2023)
Incentivizing Permissionless Distributed Learning of LLMs
por: Lidin, Joel, et al.
Publicado: (2025)
por: Lidin, Joel, et al.
Publicado: (2025)
Optimizing Federated Learning for Scalable Power-demand Forecasting in Microgrids
por: Banerjee, Roopkatha, et al.
Publicado: (2025)
por: Banerjee, Roopkatha, et al.
Publicado: (2025)
Simplified Swarm Learning Framework for Robust and Scalable Diagnostic Services in Cancer Histopathology
por: Wu, Yanjie, et al.
Publicado: (2025)
por: Wu, Yanjie, et al.
Publicado: (2025)
Robust Zero Trust Architecture: Joint Blockchain based Federated learning and Anomaly Detection based Framework
por: Pokhrel, Shiva Raj, et al.
Publicado: (2024)
por: Pokhrel, Shiva Raj, et al.
Publicado: (2024)
Federated Learning based on Pruning and Recovery
por: Ma, Chengjie
Publicado: (2024)
por: Ma, Chengjie
Publicado: (2024)
Rethinking Personalized Federated Learning with Clustering-based Dynamic Graph Propagation
por: Wang, Jiaqi, et al.
Publicado: (2024)
por: Wang, Jiaqi, et al.
Publicado: (2024)
Incentivizing High-quality Participation From Federated Learning Agents
por: Pang, Jinlong, et al.
Publicado: (2025)
por: Pang, Jinlong, et al.
Publicado: (2025)
Adaptive Client Selection via Q-Learning-based Whittle Index in Wireless Federated Learning
por: Li, Qiyue, et al.
Publicado: (2025)
por: Li, Qiyue, et al.
Publicado: (2025)
FedGCS: A Generative Framework for Efficient Client Selection in Federated Learning via Gradient-based Optimization
por: Ning, Zhiyuan, et al.
Publicado: (2024)
por: Ning, Zhiyuan, et al.
Publicado: (2024)
A Robust Federated Learning Framework for Undependable Devices at Scale
por: Wang, Shilong, et al.
Publicado: (2024)
por: Wang, Shilong, et al.
Publicado: (2024)
CSAFL: A Clustered Semi-Asynchronous Federated Learning Framework
por: Zhang, Yu, et al.
Publicado: (2021)
por: Zhang, Yu, et al.
Publicado: (2021)
Buffer-based Gradient Projection for Continual Federated Learning
por: Dai, Shenghong, et al.
Publicado: (2024)
por: Dai, Shenghong, et al.
Publicado: (2024)
FLsim: A Modular and Library-Agnostic Simulation Framework for Federated Learning
por: Mukherjee, Arnab, et al.
Publicado: (2025)
por: Mukherjee, Arnab, et al.
Publicado: (2025)
Flight: A FaaS-Based Framework for Complex and Hierarchical Federated Learning
por: Hudson, Nathaniel, et al.
Publicado: (2024)
por: Hudson, Nathaniel, et al.
Publicado: (2024)
Federated Learning with Integrated Sensing, Communication, and Computation: Frameworks and Performance Analysis
por: Liang, Yipeng, et al.
Publicado: (2024)
por: Liang, Yipeng, et al.
Publicado: (2024)
Drift-Aware Federated Learning: A Causal Perspective
por: Fang, Yunjie, et al.
Publicado: (2025)
por: Fang, Yunjie, et al.
Publicado: (2025)
Ranking-based Client Selection with Imitation Learning for Efficient Federated Learning
por: Tian, Chunlin, et al.
Publicado: (2024)
por: Tian, Chunlin, et al.
Publicado: (2024)
Enhancing Split Learning with Sharded and Blockchain-Enabled SplitFed Approaches
por: Sokhankhosh, Amirreza, et al.
Publicado: (2025)
por: Sokhankhosh, Amirreza, et al.
Publicado: (2025)
Benchmarking Mutual Information-based Loss Functions in Federated Learning
por: S, Sarang, et al.
Publicado: (2025)
por: S, Sarang, et al.
Publicado: (2025)
FedGA: A Fair Federated Learning Framework Based on the Gini Coefficient
por: Liu, ShanBin
Publicado: (2025)
por: Liu, ShanBin
Publicado: (2025)
Asyn2F: An Asynchronous Federated Learning Framework with Bidirectional Model Aggregation
por: Cao, Tien-Dung, et al.
Publicado: (2024)
por: Cao, Tien-Dung, et al.
Publicado: (2024)
Decentralized Sporadic Federated Learning: A Unified Algorithmic Framework with Convergence Guarantees
por: Zehtabi, Shahryar, et al.
Publicado: (2024)
por: Zehtabi, Shahryar, et al.
Publicado: (2024)
GradualDiff-Fed: A Federated Learning Specialized Framework for Large Language Model
por: Faiyaz, Amir, et al.
Publicado: (2025)
por: Faiyaz, Amir, et al.
Publicado: (2025)
FedSAE: A Novel Self-Adaptive Federated Learning Framework in Heterogeneous Systems
por: Li, Li, et al.
Publicado: (2021)
por: Li, Li, et al.
Publicado: (2021)
GPFL: A Gradient Projection-Based Client Selection Framework for Efficient Federated Learning
por: Na, Shijie, et al.
Publicado: (2024)
por: Na, Shijie, et al.
Publicado: (2024)
S-VOTE: Similarity-based Voting for Client Selection in Decentralized Federated Learning
por: Sánchez, Pedro Miguel Sánchez, et al.
Publicado: (2025)
por: Sánchez, Pedro Miguel Sánchez, et al.
Publicado: (2025)
Asymmetrical Reciprocity-based Federated Learning for Resolving Disparities in Medical Diagnosis
por: Wang, Jiaqi, et al.
Publicado: (2024)
por: Wang, Jiaqi, et al.
Publicado: (2024)
Personalized Federated Domain-Incremental Learning based on Adaptive Knowledge Matching
por: Li, Yichen, et al.
Publicado: (2024)
por: Li, Yichen, et al.
Publicado: (2024)
Vertical Federated Learning: Challenges, Methodologies and Experiments
por: Wei, Kang, et al.
Publicado: (2022)
por: Wei, Kang, et al.
Publicado: (2022)
Breaking the Memory Wall for Heterogeneous Federated Learning via Progressive Training
por: Wu, Yebo, et al.
Publicado: (2024)
por: Wu, Yebo, et al.
Publicado: (2024)
TablePuppet: A Generic Framework for Relational Federated Learning
por: Xu, Lijie, et al.
Publicado: (2024)
por: Xu, Lijie, et al.
Publicado: (2024)
Ejemplares similares
-
Blockchain-Enabled Federated Learning
por: Rangwala, Murtaza, et al.
Publicado: (2025) -
Incentive-Compatible Federated Learning with Stackelberg Game Modeling
por: Javaherian, Simin, et al.
Publicado: (2025) -
Spectral Sentinel: Scalable Byzantine-Robust Decentralized Federated Learning via Sketched Random Matrix Theory on Blockchain
por: Mishra, Animesh
Publicado: (2025) -
Incentive-Based Federated Learning: Architectural Elements and Future Directions
por: Kaluannakkage, Chanuka A. S. Hewa, et al.
Publicado: (2025) -
FEDBUD: Joint Incentive and Privacy Optimization for Resource-Constrained Federated Learning
por: Liu, Tao, et al.
Publicado: (2026)