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Client-Edge-Cloud Hierarchical Federated Learning [PDF]
ICC 2020 - 2020 IEEE International Conference on Communications (ICC), 2019 Federated Learning is a collaborative machine learning framework to train a deep learning model without accessing clients’ private data. Previous works assume one central parameter server either at the cloud or at the edge.
Lumin Liu +3 more
semanticscholar +1 more source
Multi-Armed Bandit-Based Client Scheduling for Federated Learning [PDF]
IEEE Transactions on Wireless Communications, 2020 By exploiting the computing power and local data of distributed clients, federated learning (FL) features ubiquitous properties such as reduction of communication overhead and preserving data privacy. In each communication round of FL, the clients update
Wenchao Xia +5 more
semanticscholar +1 more source
Youth susceptibility to tobacco use: is it general or specific?
BMC Public Health, 2021 Background Susceptibility to tobacco use predicts tobacco use onset among youth. The current study aimed to estimate the extent of overlap in susceptibilities across various tobacco products, investigate sociopsychological correlates with ...
Hui G. Cheng +4 more
doaj +1 more source
Quantitative Analysis of Hsp90-Client Interactions Reveals Principles of Substrate Recognition
Cell, 2012 Mikko Taipale +2 more
exaly +2 more sources
BMC Public Health, 2023 Background Tobacco use among underage individuals is a public health concern. Timely data about tobacco products, especially emerging products such as novel oral nicotine products (NPs), can provide critical information for the prevention of underage ...
Hui G. Cheng +2 more
doaj +1 more source
Client Selection for Federated Learning With Non-IID Data in Mobile Edge Computing
IEEE Access, 2021 Federated Learning (FL) has recently attracted considerable attention in internet of things, due to its capability of enabling mobile clients to collaboratively learn a global prediction model without sharing their privacy-sensitive data to the server ...
Wenyu Zhang +4 more
semanticscholar +1 more source
Stochastic Client Selection for Federated Learning With Volatile Clients [PDF]
IEEE Internet of Things Journal, 2020 Federated learning (FL), arising as a privacy-preserving machine learning paradigm, has received notable attention from the public. In each round of synchronous FL training, only a fraction of available clients are chosen to participate, and the ...
Tiansheng Huang +3 more
semanticscholar +1 more source
BMC Public Health, 2023 Background Electronic cigarettes (e-cigarettes) have become the most common tobacco product used among adolescents in the United States (US). Prior research has shown that peer e-cigarette use was associated with increased risk of own e-cigarette use ...
Hui G. Cheng +2 more
doaj +1 more source
Using secret sharing for searching in encrypted data [PDF]
, 2004 When outsourcing data to an untrusted database server, the data should be encrypted. When using thin clients or low-bandwidth networks it is best to perform most of the work at the server.
A. Shamir +3 more
core +12 more sources
Variability of TSNA in U.S. Tobacco and Moist Smokeless Tobacco Products
Toxicology Reports, 2020 Tobacco-specific nitrosamines (TSNAs) have been of concern to the public health community for decades and their reduction through agricultural practices, plant breeding, and tobacco processing has also been a decades-long industry effort.
M.J. Oldham +8 more
doaj +1 more source