FedSL: A Communication-Efficient Federated Learning With Split Layer Aggregation
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2024.3350241
Abstract: Federated learning (FL) can train a model collaboratively through multiple remote clients without sharing raw data. The challenge of federated learning (FL) is how to decrease network transmissions. This article aims to reduce network traffic… read more here.
Keywords: communication efficient; efficient federated; model; federated learning ... See more keywords
Toward Efficient Federated Load Forecasting: Personalization Mechanisms and Their Impact
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2025.3580378
Abstract: This article tackles the pressing challenge of load forecasting in smart buildings, aiming to enhance energy management in the light of the sector’s substantial energy consumption. Specifically, we focus on overcoming the issue of historical… read more here.
Keywords: load; toward efficient; personalization; load forecasting ... See more keywords
FLAS: Computation and Communication Efficient Federated Learning via Adaptive Sampling
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Network Science and Engineering"
DOI: 10.1109/tnse.2021.3056655
Abstract: Federated learning enables collaborative deep learning over multiple clients without sharing their local data, and it becomes increasingly popular due to the good balance between data privacy and model usability. Generally, it faces the heavy… read more here.
Keywords: communication efficient; communication; federated learning; efficient federated ... See more keywords
Communication-Efficient Federated Learning Using Censored Heavy Ball Descent
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Signal and Information Processing over Networks"
DOI: 10.1109/tsipn.2022.3212315
Abstract: Distributed machine learning enables scalability and computational offloading, but requires significant levels of communication. Consequently, communication efficiency in distributed learning settings is an important consideration, especially when the communications are wireless and battery-driven devices are… read more here.
Keywords: communication efficient; heavy ball; communication; chb ... See more keywords
Efficient Federated Learning in Resource-Constrained Edge Intelligence Networks Using Model Compression
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Vehicular Technology"
DOI: 10.1109/tvt.2023.3318080
Abstract: We investigate energy-efficient federated learning (FL) in computation and communication resource-constrained edge intelligence networks using model compression. An edge device selection strategy is designed to select appropriate edge devices for participating in FL at the… read more here.
Keywords: resource constrained; efficient federated; intelligence networks; federated learning ... See more keywords
Energy Optimization and Lightweight Design for Efficient Federated Learning in Wireless Edge Systems
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Vehicular Technology"
DOI: 10.1109/tvt.2024.3382893
Abstract: Energy-efficient federated learning (FL) is important for decentralized learning-based edge computing. The energy consumption of FL is largely affected by the efficiency of local training in edge devices and their communication efficiency to the central… read more here.
Keywords: lightweight design; energy; edge; efficient federated ... See more keywords
DualPFL: A Dual Sparse Pruning Method with Efficient Federated Learning for Edge-Based Object Detection
Sign Up to like & getrecommendations! Published in 2024 at "Applied Sciences"
DOI: 10.3390/app142210547
Abstract: With the increasing complexity of neural network models, the huge communication overhead in federated learning (FL) has become a significant issue. To mitigate resource consumption, incorporating pruning algorithms into federated learning has emerged as a… read more here.
Keywords: dual sparse; sparse pruning; dualpfl dual; efficient federated ... See more keywords