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| 1 | De novo mutation in ATP6V1B2 impairs lysosome acidification and causes dominant deafness-onychodystrophy syndrome显示文摘 | Yongyi Yuan Jianguo Zhang Qing Chang Jin Zeng Feng Xin Jianjun Wang Qingyan Zhu Jing Wu Jingqiao Lu Weiwei Guo Xukun Yan Hui Jiang Binfei Zhou Qi Li Xue Gao Huijun Yuan Shiming Yang Dongyi Han Zixu Mao Ping Chen Xi Lin Pu Dai | 2014 | Cell Research2014，24，11： | 13 |
| 2 | Rateless Coding over Fading Channels 显示文摘 | Jeff Castura Yongyi Mao | 2006 | IEEE Communications Letters (S1089-7798)2006，10，1： | 1 |
| 3 | A factor graph approach to link loss monitoring in wireless sensor networks显示文摘 | MAO YONGYI LI BAOCHUN | 2006 | IEEE Journal on Selected Areas in Communications2006，23，4： | 1 |
| 4 | Rateless coding over fading channels显示文摘 | Castura J Mao Yongyi | 2006 | IEEE Communication Letters2006，10，1： | 1 |
| 5 | Rateless Coding for Wireless Relay Channels显示文摘 | Castura J Mao Yongyi | 2007 | IEEE Transactions on Wireless Communication2007，6，5： | 1 |
| 6 | A factor graph approach to link loss monitoring in wireless sensor networks显示文摘 | Mao Yongyi Kschischang F R Li Baochun | 2005 | IEEE Journal on Selected Areas in Communications2005，23，4： | 1 |
| 7 | A factor graph approach to link loss monitoring in wireless sensor networks显示文摘 | Mao Yongyi F R Kschischang Li Baoehun S Pasupathy | 2005 | IEEE Journal on Selected Areas in Communications2005，23，4： | 1 |
| 8 | Rateless Coding over Fading Channels显示文摘 | Jefr Castura Yongyi Mao | 2006 | IEEE Communications Let- ters(S10897798)2006，，： | 1 |
| 9 | A factor graph approach to link loss monitoring in wireless sensor networks 显示文摘 | Mao Yongyi Kschischang F R Li Baochun | 2005 | IEEE Journal on Selected Areas in Communications2005，23，4： | 1 |
| 10 | A heuristic search for good low -density parity -check codes at short block lengths显示文摘 | MAO YONGYI BANIHASHEMI A H | 2001 | IEEE International Conf on Communications2001，，1： | 1 |
| 11 | A factor graph approach to link loss monitoring in wireless sensor networks显示文摘 | Mao Yongyi Li Baochun | 2006 | IEEE Journal on Selected Areas in Communications2006，23，4： | 1 |
| 12 | A Factor Graph Approach to Link Loss Monitoring in Wireless Sensor Network 显示文摘 | MAO Yongyi Ksehisehang F R LI Baochun | 2005 | IEEE Journal on Selected Areas in Communications2005，23，4： | 1 |
| 13 | A revisit to MacKay algorithm and its application to deep network compression显示文摘An iterative procedure introduced in MacKay’s evidence framework is often used for estimating the hyperparameter in empirical Bayes.Together with the use of a particular form of prior,the estimation of the hyperparameter reduces to an automatic relevance determination model,which provides a soft way of pruning model parameters.Despite the effectiveness of this estimation procedure,it has stayed primarily as a heuristic to date and its application to deep neural network has not yet been explored.This paper formally investigates the mathematical nature of this procedure and justifies it as a well-principled algorithm framework,which we call the MacKay algorithm.As an application,we demonstrate its use in deep neural networks,which have typically complicated structure with millions of parameters and can be pruned to reduce the memory requirement and boost computational efficiency.In experiments,we adopt MacKay algorithm to prune the parameters of both simple networks such as LeNet,deep convolution VGG-like networks,and residual netowrks for large image classification task.Experimental results show that the algorithm can compress neural networks to a high level of sparsity with little loss of prediction accuracy,which is comparable with the state-of-the-art. | Chune LI Yongyi MAO Richong ZHANG Jinpeng HUAI | 2020 | Frontiers of Computer Science2020，14，4： | 0 |
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