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\documentclass[
xcolor={svgnames},
hyperref={colorlinks,citecolor=DeepPink4,linkcolor=DarkRed,urlcolor=DarkBlue}
]{beamer}
% define using customized theme.
\usetheme{pas}
% define using packages
\usepackage[utf8]{inputenc}
\usepackage[T1]{fontenc}
\usepackage {minted}
% the general information.
\title[] % (optional, only for long titles)
{Citation Intent Classification}
\subtitle{Identifying the Intent of a Citation in scientific papers}
\author[tmip, hieutt] % (optional, for multiple authors)
{Isaac Riley and Pavan Mandava}
\institute[Universities Here and There] % (optional)
{
\inst{1}%
Computational Linguistics, M.Sc.\\
\and
\inst{2}%
Computational Linguistics, M.Sc.\\
}
\date[] % (optional)
{May 20, 2020}
\subject{Computational Linguistics}
% begin presentation content
\begin{document}
%%%% Slide : 1 -- INTRO
\begin{frame}
\titlepage
\end{frame}
%%%% TASK DESCRIPTION ----- Slide 2
\begin{frame}
\frametitle{Task Description}
\begin{itemize}
\item Identifying intent of a citation in scientific papers
\item Three Intent categories/classes from the data set
\begin{enumerate}
\item background (background information)
\item method (use of methods/tools)
\item result (comparing results)
\end{enumerate}
\item Classification Task
\begin{itemize}
\item Assign a discrete class (intent) for each data point
\end{itemize}
\end{itemize}
\end{frame}
%%%% DATA SET ---- Slide 3
\begin{frame}
\frametitle{Data set}
\begin{itemize}
\item Training Data: 8.2K+ data points
\begin{enumerate}
\item background - 4.8K
\item method - 2.3K
\item result - 1.1K
\end{enumerate}
\item Testing Data: 1.8K data points
\begin{enumerate}
\item background - 1K
\item method - 0.6K
\item result - 0.2K
\end{enumerate}
\end{itemize}
\end{frame}
%%%% Approach/Architectures ---- Slide 4
\begin{frame}[fragile]
\frametitle{Approach \& Architecture}
\framesubtitle{Classifier Implementation}
Base Classifier: {\bf {\color{red} Perceptron}}
\begin{itemize}
\item Linear Classifier
\item Binary Classifier
\end{itemize}
\bigskip
\begin{minted}[autogobble, breaklines,breakanywhere, fontfamily=helvetica, fontsize=\small]{python}
class Perceptron:
def __init__(self, label: str, weights: dict, theta_bias: float)
def score(self, features: list)
def update_weights(self, features: list, learning_rate: float, penalize: bool, reward: bool)
class MultiClassPerceptron:
def __init__(self, epochs: int,learning_rate: float,random_state: int)
def fit(self, X_train: list, labels: list)
def predict(self, X_test: list)
\end{minted}
\end{frame}
%%%% Approach/Architectures ---- Slide 5
\begin{frame}[fragile]
\frametitle{Approach \& Architecture}
\framesubtitle{Feature Representation}
Lexicons and Regular Expressions
\begin{itemize}
\item LEXICONS
\item REGEX
\end{itemize}
\end{frame}
\begin{frame}
\frametitle{There Is No Largest Prime Number}
\framesubtitle{The proof uses \textit{reductio ad absurdum}.}
\begin{theorem}
There is no largest prime number. \end{theorem}
\begin{enumerate}
\item<1-| alert@1> Suppose $p$ were the largest prime number.
\item<2-> Let $q$ be the product of the first $p$ numbers.
\item<3-> Then $q+1$ is not divisible by any of them.
\item<1-> But $q + 1$ is greater than $1$, thus divisible by some prime
number not in the first $p$ numbers.
\end{enumerate}
\end{frame}
\begin{frame}{A longer title}
\begin{itemize}
\item one
\item two
\end{itemize}
\end{frame}
\begin{frame}[allowframebreaks]
\frametitle{References}
\bibliographystyle{plain}
\bibliography{lib}
\end{frame}
\end{document}