Results 11 to 20 of about 48,693 (302)
Applied Sciences, 2019 Data mining is a set of methods used to mine hidden information from data. It mainly includes frequent pattern mining, sequential pattern mining, classification, and clustering.
Chun-Cheng Lin +5 more
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Joint Computing Resource and Bandwidth Allocation for Semantic Communication Networks [PDF]
, 2023 As a new communication paradigm, neural network-driven semantic communication (SemCom) has demonstrated considerable promise in enhancing resource efficiency by transmitting the semantics rather than all bits of source information. Using a large semantic
Zhang, Lan +5 more
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Bandwidth-constrained distributed skyline computation [PDF]
Proceedings of the Eighth ACM International Workshop on Data Engineering for Wireless and Mobile Access, 2009 Skyline queries have been studied in centralized systems, but also in distributed environments, such as web information systems and peer-to-peer networks. Most of the existing work focuses on efficient processing of skyline queries that return the exact and complete result set.
Akrivi Vlachou, Kjetil Nørvåg
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An incentive mechanism with bandwidth allocation for federated learning
物联网学报, 2022 Federated learning (FL) is an emerging machine learning paradigm that can make full use of crowd sourced mobile resources for training on decentralized data.However, it is challenging to deploy FL over a wireless network because of the limited bandwidth ...
Yingyun GUO +4 more
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qCon: QoS-Aware Network Resource Management for Fog Computing
Sensors, 2018 Fog computing is a new computing paradigm that employs computation and network resources at the edge of a network to build small clouds, which perform as small data centers.
Cheol-Ho Hong +3 more
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IET Communications, 2022 With the increasing number of fibre access users, P2P file sharing download traffic has gradually become one of the enormous bandwidth consumptions for the access network.
Yongli Tang +4 more
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Network Bandwidth Allocation Problem For Cloud Computing
CoRR, 2022 Cloud computing enables ubiquitous, convenient, and on-demand network access to a shared pool of computing resources. Cloud computing technologies create tremendous commercial values in various areas, while many scientific challenges have arisen accordingly.
Changpeng Yang +3 more
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Approximate inference of the bandwidth in multivariate kernel density estimation [PDF]
, 2011 Kernel density estimation is a popular and widely used non-parametric method for data-driven density estimation. Its appeal lies in its simplicity and ease of implementation, as well as its strong asymptotic results regarding its convergence to the true ...
Sanguinetti, G. +3 more
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Kubernetes Resource Scheduling Strategy for 5G Edge Computing [PDF]
Jisuanji gongcheng, 2021 Container cloud is a key supporting technology for 5G edge computing,but edge computing faces great resource pressure imposed by the large bandwidth,low latency,and massive connections of 5G.The scheduler of container cloud,Kubernetes,only collects ...
KONG Dejin, YAO Xiaoling
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Asynchronous Hierarchical Federated Learning Based on Bandwidth Allocation and Client Scheduling
Applied Sciences, 2023 Federated learning (FL) offers a promising solution in edge computing to overcome bandwidth limitations and privacy concerns associated with traditional cloud-based training.
Jian Yang +4 more
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