Imagen de Portada

Personalized Federated Learning via Gaussian Generative Modeling

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Hu, Peng, Ma, Jianwei
Formato:	Preprint
Publicado:	2026
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Decoupling General and Personalized Knowledge in Federated Learning via Additive and Low-Rank Decomposition
por: Wu, Xinghao, et al.
Publicado: (2024)

DualFed: Enjoying both Generalization and Personalization in Federated Learning via Hierachical Representations
por: Zhu, Guogang, et al.
Publicado: (2024)

Heterogeneous Federated Learning via Personalized Generative Networks
por: Taghiyarrenani, Zahra, et al.
Publicado: (2023)

Generalized and Personalized Federated Learning with Black-Box Foundation Models via Orthogonal Transformations
por: Kong, Eun Gyung, et al.
Publicado: (2025)

Variational Gaussian Mixture Manifold Models for Client-Specific Federated Personalization
por: Puppala, Sai, et al.
Publicado: (2025)

Federated Gaussian Process: Convergence, Automatic Personalization and Multi-fidelity Modeling
por: Yue, Xubo, et al.
Publicado: (2021)

Representation-Aligned Multi-Scale Personalization for Federated Learning
por: Liang, Wenfei, et al.
Publicado: (2026)

Harmonizing Generalization and Personalization in Federated Prompt Learning
por: Cui, Tianyu, et al.
Publicado: (2024)

FedAPM: Federated Learning via ADMM with Partial Model Personalization
por: Zhu, Shengkun, et al.
Publicado: (2025)

Fractal Flow: Hierarchical and Interpretable Normalizing Flow via Topic Modeling and Recursive Strategy
por: Zhang, Binhui, et al.
Publicado: (2025)

Personalized Subgraph Federated Learning with Sheaf Collaboration
por: Liang, Wenfei, et al.
Publicado: (2025)

Personalized Federated Learning via ADMM with Moreau Envelope
por: Zhu, Shengkun, et al.
Publicado: (2023)

Heterogeneity-Aware Personalized Federated Learning for Industrial Predictive Analytics
por: Hu, Yuhan, et al.
Publicado: (2026)

Federated Ensemble Learning with Progressive Model Personalization
por: Emrani, Ala, et al.
Publicado: (2026)

Client-supervised Federated Learning: Towards One-model-for-all Personalization
por: Yan, Peng, et al.
Publicado: (2024)

FedKPer: Tackling Generalization and Personalization in Medical Federated Learning via Knowledge Personalization
por: Fowler, Zoe, et al.
Publicado: (2026)

SPIRE: Conditional Personalization for Federated Diffusion Generative Models
por: Ozkara, Kaan, et al.
Publicado: (2025)

FedMerge: Federated Personalization via Model Merging
por: Chen, Shutong, et al.
Publicado: (2025)

The Diversity Bonus: Learning from Dissimilar Distributed Clients in Personalized Federated Learning
por: Wu, Xinghao, et al.
Publicado: (2024)

Rethinking the Personalized Relaxed Initialization in the Federated Learning: Consistency and Generalization
por: Shen, Li, et al.
Publicado: (2026)

Personalized Federated Learning via Learning Dynamic Graphs
por: Zhou, Ziran, et al.
Publicado: (2025)

Personalized Federated Learning under Model Dissimilarity Constraints
por: Erickson, Samuel, et al.
Publicado: (2025)

Personalized Federated Instruction Tuning via Neural Architecture Search
por: Zhang, Pengyu, et al.
Publicado: (2024)

Beyond the Federation: Topology-aware Federated Learning for Generalization to Unseen Clients
por: Ma, Mengmeng, et al.
Publicado: (2024)

Human-centered Interactive Learning via MLLMs for Text-to-Image Person Re-identification
por: Qin, Yang, et al.
Publicado: (2025)

Personalized Wireless Federated Learning for Large Language Models
por: Jiang, Feibo, et al.
Publicado: (2024)

FedSheafHN: Personalized Federated Learning on Graph-structured Data
por: Liang, Wenfei, et al.
Publicado: (2024)

Decentralized Dynamic Cooperation of Personalized Models for Federated Continual Learning
por: Yang, Danni, et al.
Publicado: (2025)

Federated Learning via Variational Bayesian Inference: Personalization, Sparsity and Clustering
por: Zhang, Xu, et al.
Publicado: (2023)

Personalized Federated Learning for Generative AI-Assisted Semantic Communications
por: Peng, Yubo, et al.
Publicado: (2024)

Personalized Federated Learning via Feature Distribution Adaptation
por: Mclaughlin, Connor J., et al.
Publicado: (2024)

Tackling Feature-Classifier Mismatch in Federated Learning via Prompt-Driven Feature Transformation
por: Wu, Xinghao, et al.
Publicado: (2024)

Personalized Federated Learning for Gradient Alignment
por: Kim, Dongwon, et al.
Publicado: (2026)

Federated Gaussian Mixture Models
por: Pettersson, Sophia Zhang, et al.
Publicado: (2025)

Personalized Federated Learning on Heterogeneous and Long-Tailed Data via Expert Collaborative Learning
por: Lv, Fengling, et al.
Publicado: (2024)

PeFLL: Personalized Federated Learning by Learning to Learn
por: Scott, Jonathan, et al.
Publicado: (2023)

Communication-efficient Federated Graph Classification via Generative Diffusion Modeling
por: Wang, Xiuling, et al.
Publicado: (2026)

Communication-Efficient Personalized Adaptation via Federated-Local Model Merging
por: Zou, Yinan, et al.
Publicado: (2026)

Personalized Federated Learning with Mixture of Models for Adaptive Prediction and Model Fine-Tuning
por: Ghari, Pouya M., et al.
Publicado: (2024)

On ADMM in Heterogeneous Federated Learning: Personalization, Robustness, and Fairness
por: Zhu, Shengkun, et al.
Publicado: (2024)