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合并分支 'mengxia' 到 'caorunzhe' 

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Chapter4/Figures/a-deeper-and-wider-grammar-tree-means-more-complex-sentence-structures.tex deleted 100644 → 0
\begin{tikzpicture}[scale=0.5]
\Tree[.IP
[.ADVP
[.AD \node(e1){前几天};]
]
[.LCP
[.NP
[.CP
[.IP
[.VP
[.VV \node(e2){出};]
[.NP
[.NN \node(e3){事故};]
]
]
]
[.DEC \node(e4){的};]
]
[.DP
[.DT \node(e5){那};]
[.CLP
[.M \node(e6){条};]
]
]
[.NP
[.NN \node(e7){街};]
]
]
[.LC \node(e8){上};]
]
[.VP
[.VP
[.VE \node(e9){有};]
[.IP
[.NP
[.NN \node(e10){一家};]
]
[.VP
[.ADVP
[.AD \node(e11){非常};]
]
[.VP
[.VV \node(e12){气派的};]
[.NP
[.ADJP
[.JJ \node(e13){大};]
]
[.NP
[.NN \node(e14){商店};]
]
]
]
]
]
]
[.VP
[.ADVP
[.AD \node(e15){，那里};]
]
[.ADVP
[.AD \node(e16){经常};]
]
[.VP
[.VV \node(e17){出售};]
[.NP
[.QP
[.CD \node(e18){一些};]
]
[.ADJP
[.JJ \node(e19){名贵};]
]
[.NP
[.NN \node(e20){鲜花};]
]
]
]
]
]
[.PU \node(e21){.};]
]
\end{tikzpicture}
\ No newline at end of file
Chapter4/Figures/a-shallow-and-narrow-grammar-means-a-simpler-sentence-structure.tex deleted 100644 → 0
\begin{tikzpicture}[scale=0.7]
\Tree[.IP
[.NP
[.NR \node(e1){俄国};]
]
[.VP
[.VV \node(e2){希望};]
[.IP
[.NP
[.NR \node(e3){伊朗};]
]
[.VP
[.ADVP
[.AD \node(e4) {没有};]
]
[.VP
[.VV \node(e5) {制造};]
[.NP
[.NN \node(e6){核武器};]
[.NN \node(e7){计划};]
]
]
]
]
]
[.PU \node(e8){.};]
]
\end{tikzpicture}
\ No newline at end of file
Chapter4/Figures/several-common-distributed-representations.tex deleted 100644 → 0
\begin{tikzpicture}
\tikzstyle{unit1} = [inner sep=1pt,align=center,font=\footnotesize]
\tikzstyle{unit2} = [inner sep=1pt,align=center,font=\scriptsize]
\node[unit1] (n1) at (0,0){单词分布式表示};
\node[unit2,anchor=west] (n11) at ([xshift=1em,yshift=4em]n1.east){one-hot词向量};
\node[unit2,anchor=west] (n12) at ([xshift=1em,yshift=2.4em]n1.east){Word2Vec词向量};
\node[unit2,anchor=west] (n13) at ([xshift=1em,yshift=0.8em]n1.east){GloVe词向量};
\node[unit2,anchor=west] (n14) at ([xshift=1em,yshift=-0.8em]n1.east){…};
\node[unit2,anchor=west] (n15) at ([xshift=1em,yshift=-2.4em]n1.east){ELMO预训练词向量};
\node[unit2,anchor=west] (n16) at ([xshift=1em,yshift=-4em]n1.east){BERT预训练词向量};
\draw[decorate,decoration={brace,mirror,amplitude=2mm}] ([xshift=-0.3em]n11.west) -- ([xshift=-0.3em]n16.west);
\node[unit1,anchor=west] (n2) at ([xshift=9em]n1.east){句子分布式表示};
\node[unit2,anchor=west] (n21) at ([xshift=1em,yshift=4.2em]n2.east){RAE编码};
\node[unit2,anchor=west] (n22) at ([xshift=1em,yshift=2.8em]n2.east){Doc2Vec向量};
\node[unit2,anchor=west] (n23) at ([xshift=1em,yshift=1.4em]n2.east){ELMO预训练句子表示};
\node[unit2,anchor=west] (n24) at ([xshift=1em,yshift=0em]n2.east){…};
\node[unit2,anchor=west] (n25) at ([xshift=1em,yshift=-1.4em]n2.east){GPT句子表示};
\node[unit2,anchor=west] (n26) at ([xshift=1em,yshift=-2.8em]n2.east){BERT预训练句子表示};
\node[unit2,anchor=west] (n27) at ([xshift=1em,yshift=-4.2em]n2.east){skip-thought向量};
\draw[decorate,decoration={brace,mirror,amplitude=2mm}] ([xshift=-0.3em]n21.west) -- ([xshift=-0.3em]n27.west);
\end{tikzpicture}
Chapter4/chapter4.tex
...@@ -88,7 +88,7 @@ ...@@ -88,7 +88,7 @@
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter4/Figures/logic-diagram-of-translation-quality-evaluation-method} \input{./Chapter4/Figures/figure-logic-diagram-of-translation-quality-evaluation-method}
\caption{译文质量评价方法逻辑图} \caption{译文质量评价方法逻辑图}
\label{fig:4-2} \label{fig:4-2}
\end{figure} \end{figure}
...@@ -300,8 +300,8 @@ ...@@ -300,8 +300,8 @@
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\subfigure[“绝对”匹配词对齐-1]{\input{./Chapter4/Figures/absolute-match-word-alignment-1}} \subfigure[“绝对”匹配词对齐-1]{\input{./Chapter4/Figures/figure-absolute-match-word-alignment-1}}
\subfigure[“绝对”匹配词对齐-2]{\input{./Chapter4/Figures/absolute-match-word-alignment-2}} \subfigure[“绝对”匹配词对齐-2]{\input{./Chapter4/Figures/figure-absolute-match-word-alignment-2}}
\caption{“绝对”匹配模型} \caption{“绝对”匹配模型}
\label{fig:4-3} \label{fig:4-3}
\end{figure} \end{figure}
...@@ -313,7 +313,7 @@ ...@@ -313,7 +313,7 @@
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter4/Figures/match-words-with-stem} \input{./Chapter4/Figures/figure-match-words-with-stem}
\caption{“波特词干”匹配词对齐} \caption{“波特词干”匹配词对齐}
\label{fig:4-4} \label{fig:4-4}
\end{figure} \end{figure}
...@@ -325,7 +325,7 @@ ...@@ -325,7 +325,7 @@
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter4/Figures/synonym-matching-word-alignment} \input{./Chapter4/Figures/figure-synonym-matching-word-alignment}
\caption{“同义词”匹配词对齐} \caption{“同义词”匹配词对齐}
\label{fig:4-5} \label{fig:4-5}
\end{figure} \end{figure}
...@@ -339,7 +339,7 @@ ...@@ -339,7 +339,7 @@
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter4/Figures/determine-final-word-alignment} \input{./Chapter4/Figures/figure-determine-final-word-alignment}
\caption{确定最终词对齐} \caption{确定最终词对齐}
\label{fig:4-6} \label{fig:4-6}
\end{figure} \end{figure}
...@@ -481,7 +481,7 @@ His house is on the south bank of the river. ...@@ -481,7 +481,7 @@ His house is on the south bank of the river.
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter4/Figures/representation-of-reference-answer-set-in-hyter} \input{./Chapter4/Figures/figure-representation-of-reference-answer-set-in-hyter}
\caption{HyTER中参考答案集的表示方式} \caption{HyTER中参考答案集的表示方式}
\label{fig:4-7} \label{fig:4-7}
\end{figure} \end{figure}
...@@ -497,8 +497,8 @@ His house is on the south bank of the river. ...@@ -497,8 +497,8 @@ His house is on the south bank of the river.
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\subfigure[英语参考答案集表示]{\input{./Chapter4/Figures/representation-of-english-reference-answer-set}} \subfigure[英语参考答案集表示]{\input{./Chapter4/Figures/figure-representation-of-english-reference-answer-set}}
\subfigure[捷克语参考答案集表示]{\input{./Chapter4/Figures/representation-of-czech-reference-answer-set}} \subfigure[捷克语参考答案集表示]{\input{./Chapter4/Figures/figure-representation-of-czech-reference-answer-set}}
\caption{使用HyTER构造的参考答案集} \caption{使用HyTER构造的参考答案集}
\label{fig:4-8} \label{fig:4-8}
\end{figure} \end{figure}
...@@ -647,7 +647,7 @@ His house is on the south bank of the river. ...@@ -647,7 +647,7 @@ His house is on the south bank of the river.
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter4/Figures/The-process-of-statistical-hypothesis-testing} \input{./Chapter4/Figures/figure-the-process-of-statistical-hypothesis-testing}
\caption{统计假设检验的流程} \caption{统计假设检验的流程}
\label{fig:4-13} \label{fig:4-13}
\end{figure} \end{figure}
...@@ -700,7 +700,7 @@ d=t \frac{s}{\sqrt{n}} ...@@ -700,7 +700,7 @@ d=t \frac{s}{\sqrt{n}}
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter4/Figures/schematic-diagram-of-word-level-quality-assessment-task} \input{./Chapter4/Figures/figure-schematic-diagram-of-word-level-quality-assessment-task}
\caption{单词级质量评估任务示意图} \caption{单词级质量评估任务示意图}
\label{fig:4-11} \label{fig:4-11}
\end{figure} \end{figure}
...@@ -745,7 +745,7 @@ d=t \frac{s}{\sqrt{n}} ...@@ -745,7 +745,7 @@ d=t \frac{s}{\sqrt{n}}
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter4/Figures/schematic-diagram-of-phrase-level-quality-assessment-task} \input{./Chapter4/Figures/figure-schematic-diagram-of-phrase-level-quality-assessment-task}
\caption{短语级质量评估任务示意图} \caption{短语级质量评估任务示意图}
\label{fig:4-12} \label{fig:4-12}
\end{figure} \end{figure}
......
Chapter9/chapter9.tex
...@@ -107,7 +107,7 @@ ...@@ -107,7 +107,7 @@
%---------------------------------------------------------------------- %----------------------------------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-the-amount-of-data-in-a-bilingual-corpus} \input{./Chapter9/Figures/figure-the-amount-of-data-in-a-bilingual-corpus}
\caption{机器翻译系统所使用的双语数据量变化趋势} \caption{机器翻译系统所使用的双语数据量变化趋势}
\label{fig:9-1} \label{fig:9-1}
\end{figure} \end{figure}
...@@ -136,14 +136,14 @@ ...@@ -136,14 +136,14 @@
\subfigure[基于特征工程的机器学习方法做图像分类]{ \subfigure[基于特征工程的机器学习方法做图像分类]{
\begin{minipage}{.9\textwidth} \begin{minipage}{.9\textwidth}
\centering \centering
\includegraphics[width=8cm]{./Chapter9/Figures/feature-engineering.jpg} \includegraphics[width=8cm]{./Chapter9/Figures/figure-feature-engineering.jpg}
\end{minipage}% \end{minipage}%
} }
\vfill \vfill
\subfigure[端到端学习方法做图像分类]{ \subfigure[端到端学习方法做图像分类]{
\begin{minipage}{.9\textwidth} \begin{minipage}{.9\textwidth}
\centering \centering
\includegraphics[width=8cm]{./Chapter9/Figures/deep-learning.jpg} \includegraphics[width=8cm]{./Chapter9/Figures/figure-deep-learning.jpg}
\end{minipage}% \end{minipage}%
} }
\caption{特征工程{\small\sffamily\bfseries{vs}}端到端学习} \caption{特征工程{\small\sffamily\bfseries{vs}}端到端学习}
...@@ -513,7 +513,7 @@ l_p({\vectorn{\emph{x}}}) & = & {\Vert{\vectorn{\emph{x}}}\Vert}_p \nonumber \\ ...@@ -513,7 +513,7 @@ l_p({\vectorn{\emph{x}}}) & = & {\Vert{\vectorn{\emph{x}}}\Vert}_p \nonumber \\
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-artificial-neuron} \input{./Chapter9/Figures/figure-artificial-neuron}
\caption{人工神经元} \caption{人工神经元}
\label{fig:9-4} \label{fig:9-4}
\end{figure} \end{figure}
...@@ -536,7 +536,7 @@ y=\begin{cases} 0 & \sum_{i}{x_i\cdot w_i}-\sigma <0\\1 & \sum_{i}{x_i\cdot w_i} ...@@ -536,7 +536,7 @@ y=\begin{cases} 0 & \sum_{i}{x_i\cdot w_i}-\sigma <0\\1 & \sum_{i}{x_i\cdot w_i}
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-perceptron-mode} \input{./Chapter9/Figures/figure-perceptron-mode}
\caption{感知机模型} \caption{感知机模型}
\label{fig:9-5} \label{fig:9-5}
\end{figure} \end{figure}
...@@ -566,7 +566,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe ...@@ -566,7 +566,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-perceptron-to-predict-1} \input{./Chapter9/Figures/figure-perceptron-to-predict-1}
\caption{预测是否去剧场的感知机（权重相同）} \caption{预测是否去剧场的感知机（权重相同）}
\label{fig:9-6} \label{fig:9-6}
\end{figure} \end{figure}
...@@ -590,7 +590,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe ...@@ -590,7 +590,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-perceptron-to-predict-2} \input{./Chapter9/Figures/figure-perceptron-to-predict-2}
\caption{预测是否去剧场的感知机（改变权重）} \caption{预测是否去剧场的感知机（改变权重）}
\label{fig:9-7} \label{fig:9-7}
\end{figure} \end{figure}
...@@ -617,7 +617,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe ...@@ -617,7 +617,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-different-forms-of-neuronal-input} \input{./Chapter9/Figures/figure-different-forms-of-neuronal-input}
\caption{神经元输入的不同形式} \caption{神经元输入的不同形式}
\label{fig:9-8} \label{fig:9-8}
\end{figure} \end{figure}
...@@ -644,7 +644,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe ...@@ -644,7 +644,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-perceptron-to-predict-3} \input{./Chapter9/Figures/figure-perceptron-to-predict-3}
\caption{预测是否去剧场的决策模型（只考虑女友喜好）} \caption{预测是否去剧场的决策模型（只考虑女友喜好）}
\label{fig:9-9} \label{fig:9-9}
\end{figure} \end{figure}
...@@ -695,7 +695,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe ...@@ -695,7 +695,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-corresponence-between-matrix-element-and-output} \input{./Chapter9/Figures/figure-corresponence-between-matrix-element-and-output}
\caption{权重矩阵中的元素与输出的对应关系} \caption{权重矩阵中的元素与输出的对应关系}
\label{fig:9-10} \label{fig:9-10}
\end{figure} \end{figure}
...@@ -706,7 +706,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe ...@@ -706,7 +706,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-single-layer-of-neural-network-for-weather-prediction} \input{./Chapter9/Figures/figure-single-layer-of-neural-network-for-weather-prediction}
\caption{预测天气的单层神经网络} \caption{预测天气的单层神经网络}
\label{fig:9-11} \label{fig:9-11}
\end{figure} \end{figure}
...@@ -734,7 +734,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe ...@@ -734,7 +734,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-translation} \input{./Chapter9/Figures/figure-translation}
\caption{线性变换示意图} \caption{线性变换示意图}
\label{fig:9-13} \label{fig:9-13}
\end{figure} \end{figure}
...@@ -746,7 +746,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe ...@@ -746,7 +746,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-linear-transformation} \input{./Chapter9/Figures/figure-linear-transformation}
\caption{线性变换3维$ \rightarrow $2维数学示意} \caption{线性变换3维$ \rightarrow $2维数学示意}
\label{fig:9-14} \label{fig:9-14}
\end{figure} \end{figure}
...@@ -758,7 +758,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe ...@@ -758,7 +758,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-activate} \input{./Chapter9/Figures/figure-activate}
\caption{几种常见的激活函数} \caption{几种常见的激活函数}
\label{fig:9-15} \label{fig:9-15}
\end{figure} \end{figure}
...@@ -776,7 +776,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe ...@@ -776,7 +776,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-four-layers-of-neural-network} \input{./Chapter9/Figures/figure-four-layers-of-neural-network}
\caption{具有四层神经元的（三层）神经网络} \caption{具有四层神经元的（三层）神经网络}
\label{fig:9-17} \label{fig:9-17}
\end{figure} \end{figure}
...@@ -801,7 +801,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe ...@@ -801,7 +801,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-two-layer-neural-network} \input{./Chapter9/Figures/figure-two-layer-neural-network}
\caption{以Sigmoid作为隐藏层激活函数的两层神经网络} \caption{以Sigmoid作为隐藏层激活函数的两层神经网络}
\label{fig:9-18} \label{fig:9-18}
\end{figure} \end{figure}
...@@ -812,7 +812,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe ...@@ -812,7 +812,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-weight} \input{./Chapter9/Figures/figure-weight}
\caption{通过调整权重$ w_{11} $改变目标函数平滑程度} \caption{通过调整权重$ w_{11} $改变目标函数平滑程度}
\label{fig:9-19} \label{fig:9-19}
\end {figure} \end {figure}
...@@ -824,7 +824,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe ...@@ -824,7 +824,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-bias} \input{./Chapter9/Figures/figure-bias}
\caption{通过调整偏置量$ b_1 $改变目标函数位置} \caption{通过调整偏置量$ b_1 $改变目标函数位置}
\label{fig:9-20} \label{fig:9-20}
\end {figure} \end {figure}
...@@ -835,8 +835,8 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe ...@@ -835,8 +835,8 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-w1} \input{./Chapter9/Figures/figure-w1}
\caption{通过改变权重$ w_{21} $将目标函数“拉高”或“压扁”} \caption{通过改变权重$ w'_{11} $将目标函数“拉高”或“压扁”}
\label{fig:9-21} \label{fig:9-21}
\end {figure} \end {figure}
%------------------------------------------- %-------------------------------------------
...@@ -846,8 +846,8 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe ...@@ -846,8 +846,8 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-w2} \input{./Chapter9/Figures/figure-w2}
\caption{通过设置第二组参数（$b_2$和$w_{22}$）将目标函数分段数增加} \caption{通过设置第二组参数（$b_2$和$w'_{21}$）将目标函数分段数增加}
\label{fig:9-22} \label{fig:9-22}
\end {figure} \end {figure}
%------------------------------------------- %-------------------------------------------
...@@ -857,7 +857,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe ...@@ -857,7 +857,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-piecewise} \input{./Chapter9/Figures/figure-piecewise}
\caption{将目标函数作分段处理} \caption{将目标函数作分段处理}
\label{fig:9-23} \label{fig:9-23}
\end {figure} \end {figure}
...@@ -870,7 +870,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe ...@@ -870,7 +870,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-fit} \input{./Chapter9/Figures/figure-fit}
\caption{扩展隐层神经元个数去拟合目标函数更多的“一小段”} \caption{扩展隐层神经元个数去拟合目标函数更多的“一小段”}
\label{fig:9-24} \label{fig:9-24}
\end {figure} \end {figure}
...@@ -927,7 +927,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe ...@@ -927,7 +927,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-tensor-sample} \input{./Chapter9/Figures/figure-tensor-sample}
\caption{3阶张量示例（$4 \times 4 \times 4$）} \caption{3阶张量示例（$4 \times 4 \times 4$）}
\label{fig:9-25} \label{fig:9-25}
\end{figure} \end{figure}
...@@ -967,7 +967,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe ...@@ -967,7 +967,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-tensor-mul} \input{./Chapter9/Figures/figure-tensor-mul}
\caption{张量与矩阵的矩阵乘法} \caption{张量与矩阵的矩阵乘法}
\label{fig:9-27} \label{fig:9-27}
\end {figure} \end {figure}
...@@ -989,7 +989,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe ...@@ -989,7 +989,7 @@ x_1\cdot w_1+x_2\cdot w_2+x_3\cdot w_3 & = & 0\cdot 1+0\cdot 1+1\cdot 1 \nonumbe
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-broadcast} \input{./Chapter9/Figures/figure-broadcast}
\caption{广播机制} \caption{广播机制}
\label{fig:9-28} \label{fig:9-28}
\end {figure} \end {figure}
...@@ -1026,7 +1026,7 @@ f(x)=\begin{cases} 0 & x\le 0 \\x & x>0\end{cases} ...@@ -1026,7 +1026,7 @@ f(x)=\begin{cases} 0 & x\le 0 \\x & x>0\end{cases}
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-save} \input{./Chapter9/Figures/figure-save}
\caption{1阶(a)、2阶(b)、3阶张量(c)的物理存储} \caption{1阶(a)、2阶(b)、3阶张量(c)的物理存储}
\label{fig:9-29} \label{fig:9-29}
\end{figure} \end{figure}
...@@ -1087,7 +1087,7 @@ f(x)=\begin{cases} 0 & x\le 0 \\x & x>0\end{cases} ...@@ -1087,7 +1087,7 @@ f(x)=\begin{cases} 0 & x\le 0 \\x & x>0\end{cases}
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-weather} \input{./Chapter9/Figures/figure-weather}
\caption{判断穿衣指数问题的神经网络过程} \caption{判断穿衣指数问题的神经网络过程}
\label{fig:9-37} \label{fig:9-37}
\end{figure} \end{figure}
...@@ -1103,7 +1103,7 @@ y&=&{\textrm{Sigmoid}}({\textrm{Tanh}}({\vectorn{\emph{x}}}\cdot {\vectorn{\emph ...@@ -1103,7 +1103,7 @@ y&=&{\textrm{Sigmoid}}({\textrm{Tanh}}({\vectorn{\emph{x}}}\cdot {\vectorn{\emph
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-weather-forward} \input{./Chapter9/Figures/figure-weather-forward}
\caption{前向计算示例（计算图）} \caption{前向计算示例（计算图）}
\label{fig:9-38} \label{fig:9-38}
\end{figure} \end{figure}
...@@ -1146,7 +1146,7 @@ y&=&{\textrm{Sigmoid}}({\textrm{Tanh}}({\vectorn{\emph{x}}}\cdot {\vectorn{\emph ...@@ -1146,7 +1146,7 @@ y&=&{\textrm{Sigmoid}}({\textrm{Tanh}}({\vectorn{\emph{x}}}\cdot {\vectorn{\emph
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-absolute-loss} \input{./Chapter9/Figures/figure-absolute-loss}
\caption{正确答案与神经网络输出之间的偏差} \caption{正确答案与神经网络输出之间的偏差}
\label{fig:9-42} \label{fig:9-42}
\end{figure} \end{figure}
...@@ -1207,7 +1207,7 @@ y&=&{\textrm{Sigmoid}}({\textrm{Tanh}}({\vectorn{\emph{x}}}\cdot {\vectorn{\emph ...@@ -1207,7 +1207,7 @@ y&=&{\textrm{Sigmoid}}({\textrm{Tanh}}({\vectorn{\emph{x}}}\cdot {\vectorn{\emph
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-gradient-descent} \input{./Chapter9/Figures/figure-gradient-descent}
\caption{函数上一个点沿着不同方向移动的示例} \caption{函数上一个点沿着不同方向移动的示例}
\label{fig:9-43} \label{fig:9-43}
\end{figure} \end{figure}
...@@ -1367,7 +1367,7 @@ $+2x^2+x+1)$ & \ \ $(x^4+2x^3+2x^2+x+1)$ & $+6x+1$ \\ ...@@ -1367,7 +1367,7 @@ $+2x^2+x+1)$ & \ \ $(x^4+2x^3+2x^2+x+1)$ & $+6x+1$ \\
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-forward-propagation} \input{./Chapter9/Figures/figure-forward-propagation}
\caption{前向计算示意图} \caption{前向计算示意图}
\label{fig:9-44} \label{fig:9-44}
\end{figure} \end{figure}
...@@ -1388,7 +1388,7 @@ $+2x^2+x+1)$ & \ \ $(x^4+2x^3+2x^2+x+1)$ & $+6x+1$ \\ ...@@ -1388,7 +1388,7 @@ $+2x^2+x+1)$ & \ \ $(x^4+2x^3+2x^2+x+1)$ & $+6x+1$ \\
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-back-propagation} \input{./Chapter9/Figures/figure-back-propagation}
\caption{反向计算示意图} \caption{反向计算示意图}
\label{fig:9-45} \label{fig:9-45}
\end{figure} \end{figure}
...@@ -1435,7 +1435,7 @@ v_t&=&\beta v_{t-1}+(1-\beta)\frac{\partial J}{\partial \theta_t} ...@@ -1435,7 +1435,7 @@ v_t&=&\beta v_{t-1}+(1-\beta)\frac{\partial J}{\partial \theta_t}
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-sawtooth} \input{./Chapter9/Figures/figure-sawtooth}
\caption{Momentum梯度下降 vs 普通梯度下降} \caption{Momentum梯度下降 vs 普通梯度下降}
\label{fig:9-46} \label{fig:9-46}
\end{figure} \end{figure}
...@@ -1529,7 +1529,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f ...@@ -1529,7 +1529,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-parallel} \input{./Chapter9/Figures/figure-parallel}
\caption{同步更新与异步更新对比} \caption{同步更新与异步更新对比}
\label{fig:9-47} \label{fig:9-47}
\end {figure} \end {figure}
...@@ -1592,7 +1592,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f ...@@ -1592,7 +1592,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-residual-structure} \input{./Chapter9/Figures/figure-residual-structure}
\caption{残差网络的结构} \caption{残差网络的结构}
\label{fig:9-51} \label{fig:9-51}
\end{figure} \end{figure}
...@@ -1637,7 +1637,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f ...@@ -1637,7 +1637,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-multilayer-neural-network-example} \input{./Chapter9/Figures/figure-multilayer-neural-network-example}
\caption{多层神经网络实例} \caption{多层神经网络实例}
\label{fig:9-52} \label{fig:9-52}
\end{figure} \end{figure}
...@@ -1699,7 +1699,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f ...@@ -1699,7 +1699,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-forward-propagation-output} \input{./Chapter9/Figures/figure-forward-propagation-output}
\caption{输出层的前向计算过程} \caption{输出层的前向计算过程}
\label{fig:9-53} \label{fig:9-53}
\end{figure} \end{figure}
...@@ -1723,7 +1723,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f ...@@ -1723,7 +1723,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-back-propagation-output1} \input{./Chapter9/Figures/figure-back-propagation-output1}
\caption{从损失到中间状态的反向传播（输出层）} \caption{从损失到中间状态的反向传播（输出层）}
\label{fig:9-54} \label{fig:9-54}
\end{figure} \end{figure}
...@@ -1756,7 +1756,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f ...@@ -1756,7 +1756,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-back-propagation-output2} \input{./Chapter9/Figures/figure-back-propagation-output2}
\caption{从中间状态到输入的反向传播（输出层）} \caption{从中间状态到输入的反向传播（输出层）}
\label{fig:9-55} \label{fig:9-55}
\end{figure} \end{figure}
...@@ -1802,7 +1802,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f ...@@ -1802,7 +1802,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-forward-propagation-hid} \input{./Chapter9/Figures/figure-forward-propagation-hid}
\caption{隐藏层的前向计算过程} \caption{隐藏层的前向计算过程}
\label{fig:9-56} \label{fig:9-56}
\end{figure} \end{figure}
...@@ -1837,7 +1837,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f ...@@ -1837,7 +1837,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-back-propagation-hid} \input{./Chapter9/Figures/figure-back-propagation-hid}
\caption{隐藏层的反向传播} \caption{隐藏层的反向传播}
\label{fig:9-57} \label{fig:9-57}
\end{figure} \end{figure}
...@@ -1902,7 +1902,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f ...@@ -1902,7 +1902,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-4-gram} \input{./Chapter9/Figures/figure-4-gram}
\caption{4-gram前馈神经网络语言架构} \caption{4-gram前馈神经网络语言架构}
\label{fig:9-60} \label{fig:9-60}
\end{figure} \end{figure}
...@@ -1964,7 +1964,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f ...@@ -1964,7 +1964,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-softmax} \input{./Chapter9/Figures/figure-softmax}
\caption{ Softmax函数（一维）所对应的曲线} \caption{ Softmax函数（一维）所对应的曲线}
\label{fig:softmax} \label{fig:softmax}
\end{figure} \end{figure}
...@@ -2019,7 +2019,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f ...@@ -2019,7 +2019,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-rnn-lm} \input{./Chapter9/Figures/figure-rnn-lm}
\caption{基于循环神经网络的语言模型结构} \caption{基于循环神经网络的语言模型结构}
\label{fig:9-62} \label{fig:9-62}
\end{figure} \end{figure}
...@@ -2058,7 +2058,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f ...@@ -2058,7 +2058,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-one-hot} \input{./Chapter9/Figures/figure-one-hot}
\caption{单词的One-hot表示 } \caption{单词的One-hot表示 }
\label{fig:9-64} \label{fig:9-64}
\end{figure} \end{figure}
...@@ -2079,7 +2079,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f ...@@ -2079,7 +2079,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-embedding} \input{./Chapter9/Figures/figure-embedding}
\caption{单词的分布式表示(词嵌入) } \caption{单词的分布式表示(词嵌入) }
\label{fig:9-65} \label{fig:9-65}
\end{figure} \end{figure}
...@@ -2101,7 +2101,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f ...@@ -2101,7 +2101,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\includegraphics[width=6cm]{./Chapter9/Figures/word-graph.jpg} \includegraphics[width=6cm]{./Chapter9/Figures/figure-word-graph.jpg}
\caption{分布式表示的可视化} \caption{分布式表示的可视化}
\label{fig:9-66} \label{fig:9-66}
\end{figure} \end{figure}
...@@ -2112,7 +2112,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f ...@@ -2112,7 +2112,7 @@ z_t&=&\gamma z_{t-1}+(1-\gamma) \frac{\partial J}{\partial {\theta}_t} \cdot \f
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-embedding-matrix} \input{./Chapter9/Figures/figure-embedding-matrix}
\caption{词嵌入矩阵${\vectorn{\emph{C}}}$} \caption{词嵌入矩阵${\vectorn{\emph{C}}}$}
\label{fig:9-67} \label{fig:9-67}
\end{figure} \end{figure}
...@@ -2143,7 +2143,7 @@ Jobs was the CEO of {\red{\underline{apple}}}. ...@@ -2143,7 +2143,7 @@ Jobs was the CEO of {\red{\underline{apple}}}.
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-rnn-model} \input{./Chapter9/Figures/figure-rnn-model}
\caption{基于RNN的表示模型（词+上下文）} \caption{基于RNN的表示模型（词+上下文）}
\label{fig:9-68} \label{fig:9-68}
\end{figure} \end{figure}
...@@ -2156,7 +2156,7 @@ Jobs was the CEO of {\red{\underline{apple}}}. ...@@ -2156,7 +2156,7 @@ Jobs was the CEO of {\red{\underline{apple}}}.
%---------------------------------------------- %----------------------------------------------
\begin{figure}[htp] \begin{figure}[htp]
\centering \centering
\input{./Chapter9/Figures/fig-model-training} \input{./Chapter9/Figures/figure-model-training}
\caption{表示模型的训练方法（与目标任务联合训练 vs 用外部任务预训练）} \caption{表示模型的训练方法（与目标任务联合训练 vs 用外部任务预训练）}
\label{fig:9-69} \label{fig:9-69}
\end{figure} \end{figure}
......
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