Added few slides

isaac
Pavan Mandava 6 years ago
parent 9ff34905c4
commit cc1e00cb12

Binary file not shown.

@ -9,14 +9,15 @@
% define using packages
\usepackage[utf8]{inputenc}
\usepackage[T1]{fontenc}
\usepackage {minted}
% the general information.
\title[Largest Prime Number?] % (optional, only for long titles)
{Citation Analysis}
\subtitle{Classifying Links between Scientific Publications}
\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)
{Pavan Mandava and Isaac Riley}
{Isaac Riley and Pavan Mandava}
\institute[Universities Here and There] % (optional)
{
\inst{1}%
@ -34,11 +35,103 @@
% 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}.}

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