Added final writeup PDF

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report/writeup.tex

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 \maketitle
 \large
 \begin{abstract}
-We present the \textit{MAD Topic Model}, which uses  syntactic and stylometric $n$-gram features (e.g., part-of-speech tags, meter) to extract the distinctive qualities of author style. MAD fits separate topic models to each of these $n$-gram vocabularies and combines the models through a multi-class logistic regression classifier. MAD breaks stylistic features into topics over vocabularies, creating a compact representation of stylistic tendency among different authors. We test MAD on several real world corpora using a variety of $n$-gram features, including part-of-speech, syllable stress, and sequences of word lengths. All relevant code, including the topic model, feature extractors, and data can be found on \href{https://github.com/dmrd/mad_topic_model}{GitHub}.
+We present the \textit{MAD Topic Model}, which uses  syntactic and stylometric $n$-gram features (e.g., part-of-speech tags, meter) to extract the distinctive qualities of author style. MAD fits separate topic models to each of these $n$-gram vocabularies and combines the models through a multi-class logistic regression classifier. MAD breaks stylistic features into topics over vocabularies, creating a compact representation of stylistic tendency among different authors. We test MAD on several real world corpora using a variety of $n$-gram features, including part-of-speech, syllable stress, and sequences of word lengths. All relevant code, including the topic model, can be found at \href{https://github.com/dmrd/mad_topic_model}{github.com/dmrd/mad\_topic\_model}.
 \end{abstract}
 
 \section{Introduction}
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