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Jinmian Ye

2 accepted papers

2019

Gate Decorator: Global Filter Pruning Method for Accelerating Deep Convolutional Neural Networks

NeurIPS 2019poster

Filter pruning is one of the most effective ways to accelerate and compress convolutional neural networks (CNNs). In this work, we propose a global filter pruning algorithm called Gate Decorator, which transforms a vanilla CNN module by multiplying its output by the channel-wise scaling factors (i.e…

2018

Learning Compact Recurrent Neural Networks With Block-Term Tensor Decomposition

CVPR 2018poster

Recurrent Neural Networks (RNNs) are powerful sequence modeling tools. However, when dealing with high dimensional inputs, the training of RNNs becomes computational expensive due to the large number of model parameters. This hinders RNNs from solving many important computer vision tasks, such as Ac…

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