15 citations · 48 across the 19 of their papers we have counts for
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cs.IT2020★ 1 cited
Adaptive Subcarrier, Parameter, and Power Allocation for Partitioned Edge Learning Over Broadband Channels
Dingzhu Wen, Ki-Jun Jeon, Mehdi Bennis +1
In this paper, we consider partitioned edge learning (PARTEL), which implements parameter-server training, a well known distributed learning method, in a wireless network. Thereby,…
cs.IT2020★ 4 cited
Scheduling for Cellular Federated Edge Learning with Importance and Channel Awareness
Jinke Ren, Yinghui He, Dingzhu Wen +3
In cellular federated edge learning (FEEL), multiple edge devices holding local data jointly train a neural network by communicating learning updates with an access point without e…
cs.IT2020★ 2 cited
Joint Parameter-and-Bandwidth Allocation for Improving the Efficiency of Partitioned Edge Learning
Dingzhu Wen, Mehdi Bennis, Kaibin Huang
To leverage data and computation capabilities of mobile devices, machine learning algorithms are deployed at the network edge for training artificial intelligence (AI) models, resu…