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20192022
most citedNAND-SPIN-Based Processing-in-MRAM Architecture for Convolutional Neural Network Acceleration

20 citations · 57 across the 6 of their papers we have counts for

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2 papers · 1 filter

cs.LG2021★ 10 cited

FedSkel: Efficient Federated Learning on Heterogeneous Systems with Skeleton Gradients Update

Junyu Luo, Jianlei Yang, Xucheng Ye +2

Federated learning aims to protect users' privacy while performing data analysis from different participants. However, it is challenging to guarantee the training efficiency on het…

cs.LG2019★ 8 cited

Accelerating CNN Training by Pruning Activation Gradients

Xucheng Ye, Pengcheng Dai, Junyu Luo +4

Sparsification is an efficient approach to accelerate CNN inference, but it is challenging to take advantage of sparsity in training procedure because the involved gradients are dy…