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CoAxNN: Optimizing on-device deep learning with conditional approximate neural networks 期刊论文
JOURNAL OF SYSTEMS ARCHITECTURE, 2023, 卷号: 143, 页码: 14
作者:  Li, Guangli;  Ma, Xiu;  Yu, Qiuchu;  Liu, Lei;  Liu, Huaxiao;  Wang, Xueying
收藏  |  浏览/下载:16/0  |  提交时间:2023/12/04
On-device deep learning  Efficient neural networks  Model approximation and optimization  
Sampling Methods for Efficient Training of Graph Convolutional Networks: A Survey 期刊论文
IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2022, 卷号: 9, 期号: 2, 页码: 205-234
作者:  Liu, Xin;  Yan, Mingyu;  Deng, Lei;  Li, Guoqi;  Ye, Xiaochun;  Fan, Dongrui
收藏  |  浏览/下载:38/0  |  提交时间:2022/06/21
Efficient training  graph convolutional networks (GCNs)  graph neural networks (GNNs)  sampling method  
A Quantitative Exploration of Collaborative Pruning and Approximation Computing Towards Energy Efficient Neural Networks 期刊论文
IEEE DESIGN & TEST, 2020, 卷号: 37, 期号: 1, 页码: 36-45
作者:  He, Xin;  Yan, Guihai;  Lu, Wenyan;  Zhang, Xuan;  Liu, Ke
收藏  |  浏览/下载:47/0  |  提交时间:2020/12/10
Resilience  Energy consumption  Approximate computing  Collaboration  Computational modeling  Artificial neural networks  Optimization  Neural network  Energy efficient computing  Network pruning  Approximate computing