Copertina

Decentralized Sporadic Federated Learning: A Unified Algorithmic Framework with Convergence Guarantees

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Zehtabi, Shahryar, Han, Dong-Jun, Parasnis, Rohit, Hosseinalipour, Seyyedali, Brinton, Christopher G.
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Distributed, Parallel, and Cluster Computing
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Resource-Constrained Decentralized Federated Learning via Personalized Event-Triggering
di: Zehtabi, Shahryar, et al.
Pubblicazione: (2022)

Multi-Source to Multi-Target Decentralized Federated Domain Adaptation
di: Wang, Su, et al.
Pubblicazione: (2023)

Orchestrating Federated Learning in Space-Air-Ground Integrated Networks: Adaptive Data Offloading and Seamless Handover
di: Han, Dong-Jun, et al.
Pubblicazione: (2024)

Asynchronous Multi-Model Dynamic Federated Learning over Wireless Networks: Theory, Modeling, and Optimization
di: Chang, Zhan-Lun, et al.
Pubblicazione: (2023)

Device Sampling and Resource Optimization for Federated Learning in Cooperative Edge Networks
di: Wang, Su, et al.
Pubblicazione: (2023)

Sporadic Gradient Tracking over Directed Graphs: A Theoretical Perspective on Decentralized Federated Learning
di: Zehtabi, Shahryar, et al.
Pubblicazione: (2026)

Communication-Efficient Multimodal Federated Learning: Joint Modality and Client Selection
di: Yuan, Liangqi, et al.
Pubblicazione: (2024)

Using Diffusion Models as Generative Replay in Continual Federated Learning -- What will Happen?
di: Mei, Yongsheng, et al.
Pubblicazione: (2024)

Differentially-Private Multi-Tier Federated Learning
di: Chen, Evan, et al.
Pubblicazione: (2024)

Towards Seamless Hierarchical Federated Learning under Intermittent Client Participation: A Stagewise Decision-Making Methodology
di: Wu, Minghong, et al.
Pubblicazione: (2025)

Local-Cloud Inference Offloading for LLMs in Multi-Modal, Multi-Task, Multi-Dialogue Settings
di: Yuan, Liangqi, et al.
Pubblicazione: (2025)

Graph Theory Meets Federated Learning over Satellite Constellations: Spanning Aggregations, Network Formation, and Performance Optimization
di: Nadimi, Fardis, et al.
Pubblicazione: (2025)

Gradient Correction in Federated Learning with Adaptive Optimization
di: Chen, Evan, et al.
Pubblicazione: (2025)

Decentralized Domain Generalization with Style Sharing: Formal Model and Convergence Analysis
di: Zehtabi, Shahryar, et al.
Pubblicazione: (2025)

Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis
di: Lan, Guangchen, et al.
Pubblicazione: (2024)

Decentralized Federated Learning: A Survey and Perspective
di: Yuan, Liangqi, et al.
Pubblicazione: (2023)

FedMFS: Federated Multimodal Fusion Learning with Selective Modality Communication
di: Yuan, Liangqi, et al.
Pubblicazione: (2023)

Communication-Efficient and Differentially Private Vertical Federated Learning with Zeroth-Order Optimization
di: Zhang, Jianing, et al.
Pubblicazione: (2025)

A Comparative Analysis of Distributed Linear Solvers under Data Heterogeneity
di: Velasevic, Boris, et al.
Pubblicazione: (2023)

Evaluation Framework for Centralized and Decentralized Aggregation Algorithm in Federated Systems
di: Chongder, Sumit
Pubblicazione: (2025)

Convergence Analysis of Decentralized ASGD
di: Tosi, Mauro DL, et al.
Pubblicazione: (2023)

Convergence Analysis of Split Federated Learning on Heterogeneous Data
di: Han, Pengchao, et al.
Pubblicazione: (2024)

FedSR: A Semi-Decentralized Federated Learning Algorithm for Non-IIDness in IoT System
di: Huang, Jianjun, et al.
Pubblicazione: (2024)

Decentralized Federated Learning with Model Caching on Mobile Agents
di: Wang, Xiaoyu, et al.
Pubblicazione: (2024)

A Unified Convergence Analysis for Semi-Decentralized Learning: Sampled-to-Sampled vs. Sampled-to-All Communication
di: Rodio, Angelo, et al.
Pubblicazione: (2025)

Harmonizing Generalization and Personalization in Ring-topology Decentralized Federated Learning
di: Guo, Shunxin, et al.
Pubblicazione: (2025)

SDFLMQ: A Semi-Decentralized Federated Learning Framework over MQTT
di: Ali-Pour, Amir, et al.
Pubblicazione: (2025)

S-VOTE: Similarity-based Voting for Client Selection in Decentralized Federated Learning
di: Sánchez, Pedro Miguel Sánchez, et al.
Pubblicazione: (2025)

Lumos: Heterogeneity-aware Federated Graph Learning over Decentralized Devices
di: Pan, Qiying, et al.
Pubblicazione: (2023)

Two-Timescale Model Caching and Resource Allocation for Edge-Enabled AI-Generated Content Services
di: Liu, Zhang, et al.
Pubblicazione: (2024)

A Unified Solution to Diverse Heterogeneities in One-shot Federated Learning
di: Bai, Jun, et al.
Pubblicazione: (2024)

Convergence-Privacy-Fairness Trade-Off in Personalized Federated Learning
di: Zhao, Xiyu, et al.
Pubblicazione: (2025)

On the Convergence of Continual Federated Learning Using Incrementally Aggregated Gradients
di: Keshri, Satish Kumar, et al.
Pubblicazione: (2024)

On the Convergence Rates of Federated Q-Learning across Heterogeneous Environments
di: Wang, Leo Muxing, et al.
Pubblicazione: (2024)

Accelerating Hybrid Federated Learning Convergence under Partial Participation
di: Bian, Jieming, et al.
Pubblicazione: (2023)

Demo: A Practical Testbed for Decentralized Federated Learning on Physical Edge Devices
di: Feng, Chao, et al.
Pubblicazione: (2025)

Evidential Trust-Aware Model Personalization in Decentralized Federated Learning for Wearable IoT
di: Rangwala, Murtaza, et al.
Pubblicazione: (2025)

UniTrans: A Unified Vertical Federated Knowledge Transfer Framework for Enhancing Cross-Hospital Collaboration
di: Huang, Chung-ju, et al.
Pubblicazione: (2025)

Accelerating the Delivery of Data Services over Uncertain Mobile Crowdsensing Networks
di: Liwang, Minghui, et al.
Pubblicazione: (2022)

Unified Analysis of Decentralized Gradient Descent: a Contraction Mapping Framework
di: Larsson, Erik G., et al.
Pubblicazione: (2025)