:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autores principales:	Fabila, Jorge, Campello, Víctor M., Martín-Isla, Carlos, Obungoloch, Johnes, Leo, Kinyera, Ronald, Amodoi, Lekadir, Karim
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning
Acceso en línea:	https://arxiv.org/abs/2408.17216
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Federated learning in low-resource settings: A chest imaging study in Africa -- Challenges and lessons learned
por: Fabila, Jorge, et al.
Publicado: (2025)

DapperFL: Domain Adaptive Federated Learning with Model Fusion Pruning for Edge Devices
por: Jia, Yongzhe, et al.
Publicado: (2024)

SacFL: Self-Adaptive Federated Continual Learning for Resource-Constrained End Devices
por: Zhong, Zhengyi, et al.
Publicado: (2025)

FL-NAS: Towards Fairness of NAS for Resource Constrained Devices via Large Language Models
por: Qin, Ruiyang, et al.
Publicado: (2024)

In-vivo imaging with a low-cost MRI scanner and cloud data processing in low-resource settings
por: Guallart-Naval, Teresa, et al.
Publicado: (2025)

DynamicFL: Federated Learning with Dynamic Communication Resource Allocation
por: Le, Qi, et al.
Publicado: (2024)

Edge Unlearning is Not "on Edge"! An Adaptive Exact Unlearning System on Resource-Constrained Devices
por: Xia, Xiaoyu, et al.
Publicado: (2024)

Accelerated Training on Low-Power Edge Devices
por: Ahmed, Mohamed Aboelenien, et al.
Publicado: (2025)

Empirical Guidelines for Deploying LLMs onto Resource-constrained Edge Devices
por: Qin, Ruiyang, et al.
Publicado: (2024)

MetaCLBench: Meta Continual Learning Benchmark on Resource-Constrained Edge Devices
por: Li, Sijia, et al.
Publicado: (2025)

CDKT-FL: Cross-Device Knowledge Transfer using Proxy Dataset in Federated Learning
por: Le, Huy Q., et al.
Publicado: (2022)

A Perspective on Explainable Artificial Intelligence Methods: SHAP and LIME
por: Salih, Ahmed, et al.
Publicado: (2023)

GreenAuto: An Automated Platform for Sustainable AI Model Design on Edge Devices
por: Tu, Xiaolong, et al.
Publicado: (2025)

EdgeRAG: Online-Indexed RAG for Edge Devices
por: Seemakhupt, Korakit, et al.
Publicado: (2024)

EdgeFlex-Transformer: Transformer Inference for Edge Devices
por: Mohammad, Shoaib, et al.
Publicado: (2025)

Quantizing Small-Scale State-Space Models for Edge AI
por: Zhao, Leo, et al.
Publicado: (2025)

XAI-SOH-FL: Enhancing SOH-FL with Adaptive Aggregation and Explainable AI for Intrusion Detection in Heterogeneous IoT
por: Aslam, Ambreen, et al.
Publicado: (2026)

Tensor Train Low-rank Approximation (TT-LoRA): Democratizing AI with Accelerated LLMs
por: Anjum, Afia, et al.
Publicado: (2024)

QuantFL: Sustainable Federated Learning for Edge IoT via Pre-Trained Model Quantisation
por: Herath, Charuka, et al.
Publicado: (2026)

Generalized Policy Learning for Smart Grids: FL TRPO Approach
por: Li, Yunxiang, et al.
Publicado: (2024)

Breaking SafetyCore: Exploring the Risks of On-Device AI Deployment
por: Guyomard, Victor, et al.
Publicado: (2025)

Continual Error Correction on Low-Resource Devices
por: Paramonov, Kirill, et al.
Publicado: (2025)

Going Beyond the Edge: Distributed Inference of Transformer Models on Ultra-Low-Power Wireless Devices
por: Gräfe, Alexander, et al.
Publicado: (2026)

Computation- and Communication-Efficient Online FL for Resource-Constrained Aerial Vehicles
por: Pervej, Ferdous, et al.
Publicado: (2025)

Democratizing AI scientists using ToolUniverse
por: Gao, Shanghua, et al.
Publicado: (2025)

HERA: Hybrid Edge-cloud Resource Allocation for Cost-Efficient AI Agents
por: Liu, Shiyi, et al.
Publicado: (2025)

AdaptiveFL: Adaptive Heterogeneous Federated Learning for Resource-Constrained AIoT Systems
por: Jia, Chentao, et al.
Publicado: (2023)

Deploying Large AI Models on Resource-Limited Devices with Split Federated Learning
por: Qiang, Xianke, et al.
Publicado: (2025)

Privacy-Aware Multi-Device Cooperative Edge Inference with Distributed Resource Bidding
por: Zhuang, Wenhao, et al.
Publicado: (2024)

Affordable Precision Agriculture: A Deployment-Oriented Review of Low-Cost, Low-Power Edge AI and TinyML for Resource-Constrained Farming Systems
por: Samanta, Riya, et al.
Publicado: (2026)

Decentor-V: Lightweight ML Training on Low-Power RISC-V Edge Devices
por: Ribeiro, Marcelo, et al.
Publicado: (2025)

Towards Low-Energy Adaptive Personalization for Resource-Constrained Devices
por: Huang, Yushan, et al.
Publicado: (2024)

Adaptive Stream Processing on Edge Devices through Active Inference
por: Sedlak, Boris, et al.
Publicado: (2024)

Welsh Not
por: Johnes, Martin
Publicado: (2025)

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

Accelerating Local LLMs on Resource-Constrained Edge Devices via Distributed Prompt Caching
por: Matsutani, Hiroki, et al.
Publicado: (2026)

BioTrain: Sub-MB, Sub-50mW On-Device Fine-Tuning for Edge-AI on Biosignals
por: Wang, Run, et al.
Publicado: (2026)

Resource-Efficient Generative AI Model Deployment in Mobile Edge Networks
por: Liang, Yuxin, et al.
Publicado: (2024)

On Accelerating Edge AI: Optimizing Resource-Constrained Environments
por: Sander, Jacob, et al.
Publicado: (2025)

Democratizing AI Governance: Balancing Expertise and Public Participation
por: Ter-Minassian, Lucile
Publicado: (2025)