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20172025
most citedStructured Probabilistic Pruning for Convolutional Neural Network Acceleration

57 citations · 69 across the 4 of their papers we have counts for

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Showing 2018Show all

2 papers · 1 filter

cs.CV2018★ 8 cited

Structured Pruning for Efficient ConvNets via Incremental Regularization

Huan Wang, Qiming Zhang, Yuehai Wang +1

Parameter pruning is a promising approach for CNN compression and acceleration by eliminating redundant model parameters with tolerable performance loss. Despite its effectiveness,…

cs.LG2018★ 4 cited

Structured Pruning for Efficient ConvNets via Incremental Regularization

Huan Wang, Qiming Zhang, Yuehai Wang +2

Parameter pruning is a promising approach for CNN compression and acceleration by eliminating redundant model parameters with tolerable performance degrade. Despite its effectivene…