Exploring Neural Network Structure through Sparse Recurrent Neural Networks: A Recasting and Distillation of Neural Network Hyperparameters
Author:
Affiliation:
1. Data Science, Worcester Polytechnic Institute,Worcester,United States
2. Mathematical Sciences, Computer Science, and Data Science Worcester Polytechnic Institute,Worcester,United States
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10459339/10459727/10459970.pdf?arnumber=10459970
Reference18 articles.
1. Block-sparse recurrent neural networks;Narang,2017
2. Sparsity in deep learning: Pruning and growth for efficient inference and training in neural networks;Hoefler;CoRR,2021
3. RNN Architecture Learning with Sparse Regularization
4. Efficient and effective training of sparse recurrent neural networks
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