Joint parameter-and-bandwidth allocation for improving the efficiency of partitioned edge learning

D Wen, M Bennis, K Huang - IEEE Transactions on Wireless …, 2020 - ieeexplore.ieee.org
To leverage data and computation capabilities of mobile devices, machine learning
algorithms are deployed at the network edge for training artificial intelligence (AI) models …
被引用次数：44 相关文章

Joint Parameter-and-Bandwidth Allocation for Improving the Efficiency of Partitioned Edge Learning

D WEN, M Bennis, K Huang - IEEE Transactions on Wireless …, 2020 - hub.hku.hk
To leverage data and computation capabilities of mobile devices, machine learning
algorithms are deployed at the network edge for training artificial intelligence (AI) models …

Joint parameter-and-bandwidth allocation for improving the efficiency of partitioned edge learning

D Wen, M Bennis, K Huang - 2020 - oulurepo.oulu.fi
To leverage data and computation capabilities of mobile devices, machine learning
algorithms are deployed at the network edge for training artificial intelligence (AI) models …

Joint Parameter-and-Bandwidth Allocation for Improving the Efficiency of Partitioned Edge Learning

D Wen, M Bennis, K Huang - IEEE Transactions on Wireless …, 2020 - dl.acm.org
To leverage data and computation capabilities of mobile devices, machine learning
algorithms are deployed at the network edge for training artificial intelligence (AI) models …
[PDF] aueb.gr

[PDF][PDF] Joint Parameter-and-Bandwidth Allocation for Improving the Efficiency of Partitioned Edge Learning

D Wen, M Bennis, K Huang - mm.aueb.gr
To leverage data and computation capabilities of mobile devices, machine learning
algorithms are deployed at the network edge for training artificial intelligence (AI) models …

Joint Parameter-and-Bandwidth Allocation for Improving the Efficiency of Partitioned Edge Learning

D Wen, M Bennis, K Huang - arXiv e-prints, 2020 - ui.adsabs.harvard.edu
To leverage data and computation capabilities of mobile devices, machine learning
algorithms are deployed at the network edge for training artificial intelligence (AI) models …
[PDF] researchgate.net

[PDF][PDF] Joint Parameter-and-Bandwidth Allocation for Improving the Efficiency of Partitioned Edge Learning

D Wen, M Bennis, K Huang - researchgate.net
To leverage data and computation capabilities of mobile devices, machine learning
algorithms are deployed at the network edge for training artificial intelligence (AI) models …

Joint Parameter-and-Bandwidth Allocation for Improving the Efficiency of Partitioned Edge Learning

D Wen, M Bennis, K Huang - arXiv preprint arXiv:2003.04544, 2020 - arxiv.org
To leverage data and computation capabilities of mobile devices, machine learning
algorithms are deployed at the network edge for training artificial intelligence (AI) models …