Commit d3ac2c17 by zengxin

12

parent f9f2f74d
...@@ -573,7 +573,7 @@ Transformer Deep(48层) & 30.2 & 43.1 & 194$\times 10^ ...@@ -573,7 +573,7 @@ Transformer Deep(48层) & 30.2 & 43.1 & 194$\times 10^
%---------------------------------------------------------------------------------------- %----------------------------------------------------------------------------------------
% NEW SECTION 12.3 % NEW SECTION 12.3
%---------------------------------------------------------------------------------------- %----------------------------------------------------------------------------------------
\section{小结及深入阅读} \section{小结及拓展阅读}
\parinterval 编码器­-解码器框架提供了一个非常灵活的机制,因为开发者只需要设计编码器和解码器的结构就能完成机器翻译。但是,架构的设计是深度学习中最具挑战的工 \parinterval 编码器­-解码器框架提供了一个非常灵活的机制,因为开发者只需要设计编码器和解码器的结构就能完成机器翻译。但是,架构的设计是深度学习中最具挑战的工
作,优秀的架构往往需要长时间的探索和大量的实验验证,而且还需要一点点 “灵感”。前面介绍的基于循环神经网络的翻译模型和注意力机制就是研究人员通过长期 作,优秀的架构往往需要长时间的探索和大量的实验验证,而且还需要一点点 “灵感”。前面介绍的基于循环神经网络的翻译模型和注意力机制就是研究人员通过长期
...@@ -581,7 +581,7 @@ Transformer Deep(48层) & 30.2 & 43.1 & 194$\times 10^ ...@@ -581,7 +581,7 @@ Transformer Deep(48层) & 30.2 & 43.1 & 194$\times 10^
\begin{itemize} \begin{itemize}
\vspace{0.5em} \vspace{0.5em}
\item 近两年,有研究已经发现注意力机制可以捕捉一些语言现象\upcite{DBLP:journals/corr/abs-1905-09418},比如,在Transformer 的多头注意力中,不同头往往会捕捉到不同的信息,比如,有些头对低频词更加敏感,有些头更适合词意消歧,甚至有些头可以捕捉句法信息。此外,由于注意力机制增加了模型的复杂性,而且随着网络层数的增多,神经机器翻译中也存在大量的冗余,因此研发轻量的注意力模型也是具有实践意义的方向\upcite{Xiao2019SharingAW,zhang-etal-2018-accelerating}{\color{red} Weight Distillation: Transferring the Knowledge in Neural Network Parameters} \item 近两年,有研究已经发现注意力机制可以捕捉一些语言现象\upcite{DBLP:journals/corr/abs-1905-09418},比如,在Transformer 的多头注意力中,不同头往往会捕捉到不同的信息,比如,有些头对低频词更加敏感,有些头更适合词意消歧,甚至有些头可以捕捉句法信息。此外,由于注意力机制增加了模型的复杂性,而且随着网络层数的增多,神经机器翻译中也存在大量的冗余,因此研发轻量的注意力模型也是具有实践意义的方向\upcite{Xiao2019SharingAW,zhang-etal-2018-accelerating,Lin2020WeightDT}
\vspace{0.5em} \vspace{0.5em}
\item 神经机器翻译依赖成本较高的GPU设备,因此对模型的裁剪和加速也是很多系统研发人员所感兴趣的方向。比如,从工程上,可以考虑减少运算强度,比如使用低精度浮点数\upcite{Ott2018ScalingNM} 或者整数\upcite{DBLP:journals/corr/abs-1906-00532,Lin2020TowardsF8}进行计算,或者引入缓存机制来加速模型的推断\upcite{Vaswani2018Tensor2TensorFN};也可以通过对模型参数矩阵的剪枝来减小整个模型的体积\upcite{DBLP:journals/corr/SeeLM16};另一种方法是知识精炼\upcite{Hinton2015Distilling,kim-rush-2016-sequence}。 利用大模型训练小模型,这样往往可以得到比单独训练小模型更好的效果\upcite{DBLP:journals/corr/ChenLCL17} \item 神经机器翻译依赖成本较高的GPU设备,因此对模型的裁剪和加速也是很多系统研发人员所感兴趣的方向。比如,从工程上,可以考虑减少运算强度,比如使用低精度浮点数\upcite{Ott2018ScalingNM} 或者整数\upcite{DBLP:journals/corr/abs-1906-00532,Lin2020TowardsF8}进行计算,或者引入缓存机制来加速模型的推断\upcite{Vaswani2018Tensor2TensorFN};也可以通过对模型参数矩阵的剪枝来减小整个模型的体积\upcite{DBLP:journals/corr/SeeLM16};另一种方法是知识精炼\upcite{Hinton2015Distilling,kim-rush-2016-sequence}。 利用大模型训练小模型,这样往往可以得到比单独训练小模型更好的效果\upcite{DBLP:journals/corr/ChenLCL17}
\vspace{0.5em} \vspace{0.5em}
......
...@@ -252,12 +252,11 @@ ...@@ -252,12 +252,11 @@
year = {2010} year = {2010}
} }
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year = {2017}
} }
@book{宗成庆2013统计自然语言处理, @book{宗成庆2013统计自然语言处理,
...@@ -304,9 +303,7 @@ ...@@ -304,9 +303,7 @@
@book{邱锡鹏2020神经网络与深度学习, @book{邱锡鹏2020神经网络与深度学习,
title ={神经网络与深度学习}, title ={神经网络与深度学习},
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volume ={34},
pages ={4},
year ={2020} year ={2020}
} }
...@@ -843,8 +840,7 @@ ...@@ -843,8 +840,7 @@
%%%%% chapter 3------------------------------------------------------ %%%%% chapter 3------------------------------------------------------
@inproceedings{ng2002discriminative, @inproceedings{ng2002discriminative,
author = {Andrew Y. Ng and author = {Ng, Andrew Y and Jordan, Michael I},
Michael I. Jordan},
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regression and naive Bayes}, regression and naive Bayes},
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...@@ -852,7 +848,6 @@ ...@@ -852,7 +848,6 @@
year = {2001}, year = {2001},
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author = {Huang, Liang}, author = {Huang, Liang},
title = {Coling 2008: Advanced Dynamic Programming in Computational Linguistics: Theory, Algorithms and Applications-Tutorial notes}, title = {Coling 2008: Advanced Dynamic Programming in Computational Linguistics: Theory, Algorithms and Applications-Tutorial notes},
...@@ -900,7 +895,7 @@ ...@@ -900,7 +895,7 @@
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volume={37}, volume={37},
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...@@ -911,7 +906,7 @@ ...@@ -911,7 +906,7 @@
@article{baum1970maximization, @article{baum1970maximization,
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...@@ -920,15 +915,17 @@ ...@@ -920,15 +915,17 @@
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...@@ -956,7 +952,6 @@ ...@@ -956,7 +952,6 @@
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...@@ -968,7 +963,6 @@ ...@@ -968,7 +963,6 @@
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...@@ -1197,8 +1189,7 @@ ...@@ -1197,8 +1189,7 @@
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%%%%% chapter 3------------------------------------------------------ %%%%% chapter 3------------------------------------------------------
...@@ -1424,8 +1415,7 @@ ...@@ -1424,8 +1415,7 @@
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...@@ -1501,8 +1491,7 @@ ...@@ -1501,8 +1491,7 @@
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...@@ -1803,7 +1792,7 @@ ...@@ -1803,7 +1792,7 @@
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@article{DBLP:journals/mt/CostaLLCC15, @article{DBLP:journals/mt/CostaLLCC15,
...@@ -2221,6 +2210,7 @@ year = {2012} ...@@ -2221,6 +2210,7 @@ year = {2012}
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year={2018}
}
%%%%% chapter 4------------------------------------------------------ %%%%% chapter 4------------------------------------------------------
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%%%%% chapter 5------------------------------------------------------ %%%%% chapter 5------------------------------------------------------
@article{brown1990statistical, @article{brown1990statistical,
...@@ -2312,13 +2295,12 @@ year = {2012} ...@@ -2312,13 +2295,12 @@ year = {2012}
} }
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...@@ -2352,8 +2334,8 @@ year = {2012} ...@@ -2352,8 +2334,8 @@ year = {2012}
} }
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...@@ -2419,7 +2401,7 @@ year = {2012} ...@@ -2419,7 +2401,7 @@ year = {2012}
year={2009} year={2009}
} }
@article{DBLP:journals/coling/FraserM07, @article{DBLP:journals/coling/FraserM07,
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...@@ -2540,7 +2522,7 @@ year = {2012} ...@@ -2540,7 +2522,7 @@ year = {2012}
} }
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...@@ -2576,7 +2558,6 @@ year = {2012} ...@@ -2576,7 +2558,6 @@ year = {2012}
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year = {2005}, year = {2005},
} }
%%%%% chapter 6------------------------------------------------------ %%%%% chapter 6------------------------------------------------------
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
...@@ -2950,7 +2931,7 @@ year = {2012} ...@@ -2950,7 +2931,7 @@ year = {2012}
} }
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...@@ -3180,7 +3161,7 @@ year = {2012} ...@@ -3180,7 +3161,7 @@ year = {2012}
} }
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Translation}, Translation},
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...@@ -3227,12 +3208,10 @@ year = {2012} ...@@ -3227,12 +3208,10 @@ year = {2012}
@inproceedings{2014Dynamic, @inproceedings{2014Dynamic,
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publisher = {Association for Machine Translation in the Americas}, publisher = {Association for Machine Translation in the Americas},
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} }
%%%%% chapter 7------------------------------------------------------ %%%%% chapter 7------------------------------------------------------
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
...@@ -3249,7 +3228,7 @@ year = {2012} ...@@ -3249,7 +3228,7 @@ year = {2012}
} }
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volume ={33}, volume ={33},
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...@@ -3399,7 +3377,7 @@ year = {2012} ...@@ -3399,7 +3377,7 @@ year = {2012}
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...@@ -3655,7 +3633,10 @@ year = {2012} ...@@ -3655,7 +3633,10 @@ year = {2012}
} }
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...@@ -3771,10 +3752,10 @@ year = {2012} ...@@ -3771,10 +3752,10 @@ year = {2012}
} }
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...@@ -3790,7 +3771,7 @@ year = {2012} ...@@ -3790,7 +3771,7 @@ year = {2012}
} }
@article{xiao2013bagging, @article{xiao2013bagging,
title ={Bagging and boosting statistical machine translation systems}, title ={Bagging and boosting statistical machine translation systems},
author ={Xiao, Tong and Zhu, Jingbo and Liu, Tongran}, author ={Tong Xiao and Jingbo Zhu and Tongran Liu },
publisher ={Artificial Intelligence}, publisher ={Artificial Intelligence},
volume ={195}, volume ={195},
pages ={496--527}, pages ={496--527},
...@@ -3812,7 +3793,7 @@ year = {2012} ...@@ -3812,7 +3793,7 @@ year = {2012}
Mei Yang and Mei Yang and
Jianfeng Gao and Jianfeng Gao and
Patrick Nguyen and Patrick Nguyen and
Robert Moore}, Robert C. Moore},
title = {Indirect-HMM-based Hypothesis Alignment for Combining Outputs from title = {Indirect-HMM-based Hypothesis Alignment for Combining Outputs from
Machine Translation Systems}, Machine Translation Systems},
pages = {98--107}, pages = {98--107},
...@@ -5087,6 +5068,13 @@ pages ={157-166}, ...@@ -5087,6 +5068,13 @@ pages ={157-166},
publisher = "Association for Computational Linguistics", publisher = "Association for Computational Linguistics",
pages = "1789--1798", pages = "1789--1798",
} }
@article{Lin2020WeightDT,
title={Weight Distillation: Transferring the Knowledge in Neural Network Parameters},
author={Ye Lin and Yanyang Li and Ziyang Wang and Bei Li and Quan Du and Tong Xiao and Jingbo Zhu},
journal={ArXiv},
year={2020},
volume={abs/2009.09152}
}
%%%%% chapter 12------------------------------------------------------ %%%%% chapter 12------------------------------------------------------
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
...@@ -5105,6 +5093,102 @@ pages ={157-166}, ...@@ -5105,6 +5093,102 @@ pages ={157-166},
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%% chapter 15------------------------------------------------------ %%%%% chapter 15------------------------------------------------------
@inproceedings{DBLP:conf/cvpr/YuYR18,
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Zhiding Yu and
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@inproceedings{DBLP:conf/eccv/HeZRS16,
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}
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Sergey Edunov and
Alexei Baevski and
Angela Fan and
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}
@inproceedings{KleinOpenNMT,
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Yoon Kim and
Yuntian Deng and
Jean Senellart and
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publisher = {Annual Meeting of the Association for Computational Linguistics},
year = {2017}
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author = {Lijun Wu and
Yiren Wang and
Yingce Xia and
Fei Tian and
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Tao Qin and
Jianhuang Lai and
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@inproceedings{DBLP:conf/cvpr/HuangLMW17,
author = {Gao Huang and
Zhuang Liu and
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publisher = {International Conference on Learning Representations},
year = {2017}
}
%%%%% chapter 15------------------------------------------------------ %%%%% chapter 15------------------------------------------------------
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
......
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