“Zhiyong Zhang”版本间的差异
来自cslt Wiki
(→Technical Report To Write) |
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=Papers To Read = | =Papers To Read = | ||
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* Testing on 100h-Ch+100h-En, better performance observed. | * Testing on 100h-Ch+100h-En, better performance observed. | ||
* Now testing the source code on 1400h_8k data, but stange decoding results got.Need to further investigate. | * Now testing the source code on 1400h_8k data, but stange decoding results got.Need to further investigate. | ||
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+ | =Reading Lists= | ||
+ | *[[媒体文件:Efficient_mini-batch_training_for_stochastic_optimization.pdf |苏圣 2015-10-29 Efficient_mini-batch_training_for_stochastic_optimization ]] | ||
+ | *[[媒体文件:2015_Fitnets-Hints for thin deep nets.pdf |张之勇 2015-10-29 2015_Fitnets-Hints for thin deep nets ]] | ||
+ | *http://www.cs.cmu.edu/~muli/file/minibatch_sgd.pdf |
2015年10月29日 (四) 07:14的最后版本
目录
Papers To Read
- 1, Learned-Norm pooling for deep feedforward and recurrent neural networks
Task schedules
Summary
-------------------------------------------------------------------------------------------------------- Priority | Tasks name | Status | Notions -------------------------------------------------------------------------------------------------------- 1 | Bi-Softmax | ■■■□□□□□□□ | 1400h am training and problem fixing -------------------------------------------------------------------------------------------------------- 2 | RNN+DAE | □□□□□□□□□□ | --------------------------------------------------------------------------------------------------------
Speech Recognition
Multi-lingual Am training
Bi-Softmax
- Using two distinct softmax for English and Chinese data.
- Testing on 100h-Ch+100h-En, better performance observed.
- Now testing the source code on 1400h_8k data, but stange decoding results got.Need to further investigate.