Guardado en:
| Autores principales: | Medjadji, Chaimaa, Leduc, Guilain, Kubler, Sylvain, Traon, Yves Le |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2605.16089 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Federated Imputation under Heterogeneous Feature Spaces
por: Hocine, Imane, et al.
Publicado: (2026)
por: Hocine, Imane, et al.
Publicado: (2026)
FedSparQ: Adaptive Sparse Quantization with Error Feedback for Robust & Efficient Federated Learning
por: Medjadji, Chaimaa, et al.
Publicado: (2025)
por: Medjadji, Chaimaa, et al.
Publicado: (2025)
Optimized Federated Knowledge Distillation with Distributed Neural Architecture Search
por: Medjadji, Chaimaa, et al.
Publicado: (2026)
por: Medjadji, Chaimaa, et al.
Publicado: (2026)
Leveraging External Factors in Household-Level Electrical Consumption Forecasting using Hypernetworks
por: Bernier, Fabien, et al.
Publicado: (2025)
por: Bernier, Fabien, et al.
Publicado: (2025)
One Model, Many Skills: Parameter-Efficient Fine-Tuning for Multitask Code Analysis
por: Akli, Amal, et al.
Publicado: (2026)
por: Akli, Amal, et al.
Publicado: (2026)
On the Effectiveness of Hybrid Pooling in Mixup-Based Graph Learning for Language Processing
por: Dong, Zeming, et al.
Publicado: (2022)
por: Dong, Zeming, et al.
Publicado: (2022)
Test Time Training for AC Power Flow Surrogates via Physics and Operational Constraint Refinement
por: Dogoulis, Panteleimon, et al.
Publicado: (2025)
por: Dogoulis, Panteleimon, et al.
Publicado: (2025)
Exploring Federated Learning for Thermal Urban Feature Segmentation -- A Comparison of Centralized and Decentralized Approaches
por: Duda, Leonhard, et al.
Publicado: (2025)
por: Duda, Leonhard, et al.
Publicado: (2025)
Impact of network topology on the performance of Decentralized Federated Learning
por: Palmieri, Luigi, et al.
Publicado: (2024)
por: Palmieri, Luigi, et al.
Publicado: (2024)
UA-PDFL: A Personalized Approach for Decentralized Federated Learning
por: Zhu, Hangyu, et al.
Publicado: (2024)
por: Zhu, Hangyu, et al.
Publicado: (2024)
Byzantine-Robust Aggregation for Securing Decentralized Federated Learning
por: Cajaraville-Aboy, Diego, et al.
Publicado: (2024)
por: Cajaraville-Aboy, Diego, et al.
Publicado: (2024)
PFedDST: Personalized Federated Learning with Decentralized Selection Training
por: Fan, Mengchen, et al.
Publicado: (2025)
por: Fan, Mengchen, et al.
Publicado: (2025)
From Centralized to Decentralized Federated Learning: Theoretical Insights, Privacy Preservation, and Robustness Challenges
por: Li, Qiongxiu, et al.
Publicado: (2025)
por: Li, Qiongxiu, et al.
Publicado: (2025)
Decentralized Federated Learning: A Survey on Security and Privacy
por: Hallaji, Ehsan, et al.
Publicado: (2024)
por: Hallaji, Ehsan, et al.
Publicado: (2024)
On the Limits of Momentum in Decentralized and Federated Optimization
por: Zaccone, Riccardo, et al.
Publicado: (2025)
por: Zaccone, Riccardo, et al.
Publicado: (2025)
DMPA: Model Poisoning Attacks on Decentralized Federated Learning for Model Differences
por: Feng, Chao, et al.
Publicado: (2025)
por: Feng, Chao, et al.
Publicado: (2025)
From Models to Network Topologies: A Topology Inference Attack in Decentralized Federated Learning
por: Feng, Chao, et al.
Publicado: (2025)
por: Feng, Chao, et al.
Publicado: (2025)
MultiConfederated Learning: Inclusive Non-IID Data handling with Decentralized Federated Learning
por: Duchesne, Michael, et al.
Publicado: (2024)
por: Duchesne, Michael, et al.
Publicado: (2024)
From Federated Learning to X-Learning: Breaking the Barriers of Decentrality Through Random Walks
por: Salihovic, Allan, et al.
Publicado: (2025)
por: Salihovic, Allan, et al.
Publicado: (2025)
Learning Heterogeneous Performance-Fairness Trade-offs in Federated Learning
por: Ye, Rongguang, et al.
Publicado: (2025)
por: Ye, Rongguang, et al.
Publicado: (2025)
Online Decentralized Federated Multi-task Learning With Trustworthiness in Cyber-Physical Systems
por: Odeyomi, Olusola, et al.
Publicado: (2025)
por: Odeyomi, Olusola, et al.
Publicado: (2025)
Overcoming Data and Model Heterogeneities in Decentralized Federated Learning via Synthetic Anchors
por: Huang, Chun-Yin, et al.
Publicado: (2024)
por: Huang, Chun-Yin, et al.
Publicado: (2024)
Trust and Resilience in Federated Learning Through Smart Contracts Enabled Decentralized Systems
por: Cassano, Lorenzo, et al.
Publicado: (2024)
por: Cassano, Lorenzo, et al.
Publicado: (2024)
Load-Aware Training Scheduling for Model Circulation-based Decentralized Federated Learning
por: Kainuma, Haruki, et al.
Publicado: (2025)
por: Kainuma, Haruki, et al.
Publicado: (2025)
Decentralized Personalized Federated Learning based on a Conditional Sparse-to-Sparser Scheme
por: Long, Qianyu, et al.
Publicado: (2024)
por: Long, Qianyu, et al.
Publicado: (2024)
Trading-off Accuracy and Communication Cost in Federated Learning
por: Villani, Mattia Jacopo, et al.
Publicado: (2025)
por: Villani, Mattia Jacopo, et al.
Publicado: (2025)
DFML: Decentralized Federated Mutual Learning
por: Khalil, Yasser H., et al.
Publicado: (2024)
por: Khalil, Yasser H., et al.
Publicado: (2024)
Zero-Shot Decentralized Federated Learning
por: Masano, Alessio, et al.
Publicado: (2025)
por: Masano, Alessio, et al.
Publicado: (2025)
OledFL: Unleashing the Potential of Decentralized Federated Learning via Opposite Lookahead Enhancement
por: Li, Qinglun, et al.
Publicado: (2024)
por: Li, Qinglun, et al.
Publicado: (2024)
Guided Model Merging for Hybrid Data Learning: Leveraging Centralized Data to Refine Decentralized Models
por: Zhu, Junyi, et al.
Publicado: (2025)
por: Zhu, Junyi, et al.
Publicado: (2025)
Is Centralized Training with Decentralized Execution Framework Centralized Enough for MARL?
por: Zhou, Yihe, et al.
Publicado: (2023)
por: Zhou, Yihe, et al.
Publicado: (2023)
Mitigating the reconstruction-detection trade-off in VAE-based unsupervised anomaly detection
por: Senellart, Agathe, et al.
Publicado: (2026)
por: Senellart, Agathe, et al.
Publicado: (2026)
dFLMoE: Decentralized Federated Learning via Mixture of Experts for Medical Data Analysis
por: Xie, Luyuan, et al.
Publicado: (2025)
por: Xie, Luyuan, et al.
Publicado: (2025)
Privacy Preserved Blood Glucose Level Cross-Prediction: An Asynchronous Decentralized Federated Learning Approach
por: Piao, Chengzhe, et al.
Publicado: (2024)
por: Piao, Chengzhe, et al.
Publicado: (2024)
Towards Heterogeneity-Aware and Energy-Efficient Topology Optimization for Decentralized Federated Learning in Edge Environment
por: Liu, Yuze, et al.
Publicado: (2025)
por: Liu, Yuze, et al.
Publicado: (2025)
Federated Domain Generalization with Label Smoothing and Balanced Decentralized Training
por: Soltany, Milad, et al.
Publicado: (2024)
por: Soltany, Milad, et al.
Publicado: (2024)
Spiking Neural Networks in Vertical Federated Learning: Performance Trade-offs
por: Abbasihafshejani, Maryam, et al.
Publicado: (2024)
por: Abbasihafshejani, Maryam, et al.
Publicado: (2024)
Trust-Based Incentive Mechanisms in Semi-Decentralized Federated Learning Systems
por: Shrestha, Ajay Kumar
Publicado: (2026)
por: Shrestha, Ajay Kumar
Publicado: (2026)
Provable Privacy Advantages of Decentralized Federated Learning via Distributed Optimization
por: Yu, Wenrui, et al.
Publicado: (2024)
por: Yu, Wenrui, et al.
Publicado: (2024)
A Survey of Multi Agent Reinforcement Learning: Federated Learning and Cooperative and Noncooperative Decentralized Regimes
por: Cheruiyot, Kemboi, et al.
Publicado: (2025)
por: Cheruiyot, Kemboi, et al.
Publicado: (2025)
Ejemplares similares
-
Federated Imputation under Heterogeneous Feature Spaces
por: Hocine, Imane, et al.
Publicado: (2026) -
FedSparQ: Adaptive Sparse Quantization with Error Feedback for Robust & Efficient Federated Learning
por: Medjadji, Chaimaa, et al.
Publicado: (2025) -
Optimized Federated Knowledge Distillation with Distributed Neural Architecture Search
por: Medjadji, Chaimaa, et al.
Publicado: (2026) -
Leveraging External Factors in Household-Level Electrical Consumption Forecasting using Hypernetworks
por: Bernier, Fabien, et al.
Publicado: (2025) -
One Model, Many Skills: Parameter-Efficient Fine-Tuning for Multitask Code Analysis
por: Akli, Amal, et al.
Publicado: (2026)