Federated learning with stochastic quantization
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Intelligent Systems"
DOI: 10.1002/int.23056
Abstract: This paper studies the distributed federated learning problem when the exchanged information between the server and the workers is quantized. A novel quantized federated averaging algorithm is developed by applying stochastic quantization scheme to the… read more here.
Keywords: model parameters; stochastic quantization; federated learning; model ... See more keywords
Solar forcing on the ionosphere: Global model of the F2 layer peak parameters driven by re-calibrated sunspot numbers
Sign Up to like & getrecommendations! Published in 2021 at "Acta Astronautica"
DOI: 10.1016/j.actaastro.2020.10.029
Abstract: Abstract Global empirical models (GMF2 – the F2 layer Global Model) of the critical frequency, foF2, of the ionospheric F2-layer and the peak height, hmF2, are built up with the re-calibrated sunspot number time series,… read more here.
Keywords: layer peak; calibrated sunspot; global model;
EC-DNN: A new method for parallel training of deep neural networks
Sign Up to like & getrecommendations! Published in 2018 at "Neurocomputing"
DOI: 10.1016/j.neucom.2018.01.072
Abstract: Abstract Parallelization framework has become a necessity to speed up the training of deep neural networks (DNN) recently. In the typical parallelization framework, called MA-DNN, the parameters of local models are periodically averaged to get… read more here.
Keywords: training deep; deep neural; neural networks; global model ... See more keywords
Global 3D model of mantle attenuation using seismic normal modes
Sign Up to like & getrecommendations! Published in 2025 at "Nature"
DOI: 10.1038/s41586-024-08322-y
Abstract: Seismic tomographic models based only on wave velocities have limited ability to distinguish between a thermal or compositional origin for Earth’s 3D structure1. Complementing wave velocities with attenuation observations can make that distinction, which is… read more here.
Keywords: grain size; model mantle; model; global model ... See more keywords
A Global Model for Predicting Vacuum Drying of Used Nuclear Fuel Assemblies
Sign Up to like & getrecommendations! Published in 2021 at "Nuclear Technology"
DOI: 10.1080/00295450.2021.1936863
Abstract: Abstract A global model is proposed to simulate the drying process of used nuclear fuel assemblies under vacuum drying conditions. The transient model consists of a coupled mass and energy conservation equation with appropriate source… read more here.
Keywords: global model; nuclear fuel; model; vacuum drying ... See more keywords
Implementing the global model of the research university in a national context: perspectives of deans and departments heads
Sign Up to like & getrecommendations! Published in 2020 at "International Journal of Educational Management"
DOI: 10.1108/ijem-01-2020-0026
Abstract: This article aims to explore the implications of means–ends decoupling at the state level for the implementation of the global model of the research university by the deans and department heads. Means–ends decoupling at the… read more here.
Keywords: model research; global model; level; ends decoupling ... See more keywords
FL-Incentivizer: FL-NFT and FL-Tokens for Federated Learning Model Trading and Training
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3235484
Abstract: Federated learning (FL) is an on-device distributed learning scheme that does not require training devices to transfer their data to a centralized facility. The goal of federated learning is to learn a global model over… read more here.
Keywords: incentivizer; federated learning; training; incentivizer nft ... See more keywords
Privacy-Enhanced and Verification-Traceable Aggregation for Federated Learning
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2022.3194930
Abstract: Federated learning (FL) is a distributed machine learning framework, which allows multiple users to collaboratively train and obtain a global model with high accuracy. Currently, FL is paid more attention by researchers and a growing… read more here.
Keywords: aggregation; federated learning; privacy; verification ... See more keywords
An Efficient Asynchronous Federated Learning Protocol for Edge Devices
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2024.3406634
Abstract: Recent studies highlight the significant potential of edge computing and federated learning (FL) in advancing artificial intelligence. However, challenges, such as unstable device performance and the heterogeneously distributed feature of local data, pose threats to… read more here.
Keywords: efficiency; edge; federated learning; global model ... See more keywords
Assessing Sustainable Development in Guilin: A Localized Indicator System for a Global Model
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2025.3603168
Abstract: In the context of globalization and urbanization, urban ecological environments are becoming increasingly vulnerable, presenting significant challenges to ecological security. These challenges have a significant impact on the advancement of sustainable development. As an innovative… read more here.
Keywords: guilin; indicator system; development; global model ... See more keywords
Intermittent Pulling With Local Compensation for Communication-Efficient Distributed Learning
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Emerging Topics in Computing"
DOI: 10.1109/tetc.2020.3043300
Abstract: As a widely used iterative algorithm, the distributed Stochastic Gradient Descent (SGD) has shown great advances in training machine learning models due to the reduced time of the gradients computation. However, the huge number of… read more here.
Keywords: communication; compensation; pulling reduction; local compensation ... See more keywords