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---
theme: none
title: Home
weight: 0
---
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<!-- The above 3 meta tags *must* come first in the head; any other head content must come *after* these tags -->
<meta name="description" content="">
<meta name="author" content="">
<link rel="icon" href="../../favicon.ico">
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.12.0/jquery.min.js"></script>
<script src="jquery.dataTables.min.js"></script>
<script src="bib-list.js"></script>
<link rel="stylesheet" href="bib-publication-list.css" type="text/css" />
<title>Cornell CS 6741</title>
<!-- Bootstrap core CSS -->
<link rel="stylesheet" href="//netdna.bootstrapcdn.com/bootstrap/3.3.5/css/bootstrap.min.css">
<script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.5/js/bootstrap.min.js"></script>
<link rel="stylesheet" href="page.css">
</head>
<body>
<div class="row">
</div>
<div class="container">
<div class="panel panel-primary" style="margin-top:10px;background-color:#B75F33;border-color:#000000;">
<div class="panel-heading" style="background-color:#B75F33;border-color:#2D6ED3;">
<h1>CS 6741: Topics in NLP and Machine Learning </h1>
<p class="lead">Sasha Rush, Cornell Tech (Spring 2020)
- <i>Discrete Variables / Deep Learning</i></p>
</div>
<div class="panel-footer">
<ul class="nav nav-tabs invert-colors">
<li class="active"><a data-toggle="tab" href="#home_tab">Home</a></li>
<li><a data-toggle="tab" href="#schedule_tab">Schedule</a></li>
<li><a data-toggle="tab" href="#resources_tab">Resources</a></li>
<li><a data-toggle="tab" href="#project_tab">Project</a></li>
</ul>
</div>
</div>
<div class="container">
<div class="tab-content">
<div id="home_tab" class="row tab-pane fade in active">
<div class="row container">
<p><span style="font-size: 1.17em;font-weight: bold;">Time:</span> Mon/Wed 1:00-2:30pm</p>
<p><span style="font-size: 1.17em;font-weight: bold;">Location:</span> Bloomberg 497 / Gates G13</p>
</div>
<div class="row container">
<h3 id="description">Course Info</h3>
<div class="container ">
<dl>
<dt>Links</dt>
<dd><ul>
<li><a href="https://cs6741.slack.com/">Slack </a></li>
<li><a href="https://paperpile.com/shared/9UubPS">Paper Links </a>
<li>
<a href="https://drive.google.com/open?id=14ND48MRLG5B1amuFagakBY2O5B3VO_fr">Materials / Notebooks</a></li>
<li><a href="https://canvas.cornell.edu/courses/14084/assignments">Canvas Site</a></li>
</ul></dd>
<dt>Instructor</dt>
<dd> <ul>
<li>Alexander "Sasha" Rush <br>
</li>
<li>Email: Slack preferred or arush at cornell.edu
</li></ul>
</dd>
<dt>Office Hours</dt>
<dd>
<ul>
<li>Monday: 2:30-4, CT 368 / <a href="https://zoom.us/j/4348004565">Zoom</a> </li>
</ul>
</dd>
<dt>Grading</dt>
<dd>
<ul>
<li> Assignments (15%) </li>
<li> Presentation and Participation (20%) </li>
<li> Midterm Exam (15%) </li>
<li> Final Project (50%) </li>
</ul>
</dd>
<dt>Description</dt>
<dd>
<ul>
<li>
<p>
CS 6741 is a topics class on the
intersection of natural language
processing and machine learning
with a rotating focus and style.
The theme of this class this
semester is <i>Discrete Variables
/ Deep Learning</i>.
The course will have three (discrete) parts.
<ol>
<li> A modern treatment of
discrete variable models and
structured prediction for
several classic problems in
NLP. (Lecture-Based) </li>
<li> A survey of current tasks
and challenges in
contermporary NLP and a
collaborative discussion of
potential research problems. (Teacher/Student-presented) </li>
<li> Project workshopping and group feedback. (Open-form) </li>
</ol>
</p>
</li>
</dd>
<dt>Preliminaries</dt>
<dd>
<ul><li>
This course is not meant to be a
comprehensive treatment of NLP or deep
learning. For NLP, I will assume a working
knowledge of basic problems such as classification
and language modeling. For deep learning,
I will assume knowledge of PyTorch and the ability
to quickly pick-up deep learning models from
tutorials.
</li>
</ul>
</dd>
</dl>
</div>
</div>
</div>
<!--div id="references_tab" class="row tab-pane fade">
</div-->
<div id="sections_tab" class="row tab-pane fade">
<h3>Time and Location</h3>
<div class="row container">
<ul>
<li>Thursday 5-6pm: Pierce Hall 320</li>
<li>Friday 11-11:59am: MD 223</li>
</ul>
</div>
<hr>
<div class="row container">
<table class="table">
<thead>
<tr _base_target="_blank">
<th>Date</th>
<th>Location</th>
<th>Topic</th>
<th>Materials</th>
</tr>
</thead>
<tbody>
<tr class="lecture" _base_target="_blank">
<td>Sep. 1, 10-11am (Mark)</td>
<td>Pierce 301</td>
<td>
<a href="https://github.com/harvard-ml-courses/cs287-sections/tree/master/00">Math Review (Linear Algebra, Calculus, Probabilistic Theory)</a>
</td>
<td>
</td>
</tr>
<tr>
<td>Sep. 4, 5-6pm (Zhirui)</td>
<td>Pierce 301</td>
<td>
<a href="https://github.com/harvard-ml-courses/cs287-sections/tree/master/00">Math Review (Linear Algebra, Calculus, Probabilistic Theory)</a>
</td>
<td>
</td>
</tr>
<tr>
<td>Sep. 7, 5-6pm (Rachit)</td>
<td>Pierce 320</td>
<td>
Code Review (Python, Numpy, Matplotlib, PyTorch)
</td>
<td>
</td>
</tr>
<tr>
<td>Sep. 8, 11-11:59am (Rachit)</td>
<td>MD 223</td>
<td>
Code Review (Python, Numpy, Matplotlib, PyTorch)
</td>
<td>
</td>
</tr>
</tbody>
</table>
</div>
</div>
<div id="project_tab" class="row tab-pane fade">
<dt>Project</dt>
<dd>
<ul>
<li>
<p>
The goal of this class is to produce original
research in natural language processing or machine learning.
As such, we will work towards the goal of submitting a paper
to a top-tier conference. You should aim to submit an abstract
half-way through the class and a final project by the end of the term.
</p>
</li>
</ul>
</dd>
<hr>
<h3>Important Dates</h3>
<div class="row container">
<table class="table">
<thead>
<tr _base_target="_blank">
<th class="col-md-1">Date</th>
<th class="col-md-2">Due</th>
<th class="col-md-9">Descriptions</th>
</tr>
</thead>
<tbody>
<tr>
<td>March 18</td>
<td>Abstract and Status Report</td>
<td>
This is a three to four page document that contains a
draft of your final abstract, as well as a brief status report on the progress of your project.
</td>
</tr>
<tr>
<td></td>
<td></td>
<td>
</td>
</tr>
<tr>
<td>May 14</td>
<td>Final Report</td>
<td>
You will write a report of up to eight pages, in the style of a mainstream CS
conference paper. Please use the provided template (see <a href="https://github.com/harvard-ml-courses/cs287-s18/tree/master/projects/template">here</a>)
</td>
</tr>
<tr></tr>
</tbody>
</table>
</div>
</div>
<div id="resources_tab" class="row tab-pane fade">
<div class="row container">
<dl>
<dt>Machine Learning and Statistics</dt>
<dd><ul>
<li> Bishop, Pattern Recognition and Machine Learning </a>
<li> Murphy, <a href="http://harvardcoopbooks.bncollege.com/webapp/wcs/stores/servlet/BNCB_TextbookDetailView?catalogId=10001&item=N&langId=-1&productId=600005699137&storeId=52084">Machine Learning: A Probabilistic Perspective</a>
</ul> </dd>
</dl>
<dl>
<dt>Applied Statistics and Linear Algebra</dt>
<ul>
<li> Gelman et al, <a href="http://www.stat.columbia.edu/~gelman/book/"> Bayesian Data Analysis </a> </li>
<li> Petersen and Pedersen, <a href="http://www2.imm.dtu.dk/pubdb/views/edoc_download.php/3274/pdf/imm3274.pdf">The Matrix Cookbook</a>
<li> Blei et al, <a href="https://arxiv.org/pdf/1601.00670.pdf">Variational Inference: A Review for Statisticians</a>
</ul></dd>
</dl>
<dl>
<dt>PyTorch</dt>
<ul>
<li> <a href="http://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html">General Tutorial</a> </li>
<li> <a href="http://pytorch.org/tutorials/beginner/deep_learning_nlp_tutorial.html"> NLP Tutorial</a>
<li> <a href="http://pytorch.org/tutorials/intermediate/seq2seq_translation_tutorial.html"> Seq2Seq Tutorial</a>
</ul></dd>
</dl>
</div>
</div>
<div id="schedule_tab" class="row tab-pane fade">
<div class="row container">
<div class="tab-content">
<table class="table">
<tr><th>Date</th> <th>Area</th> <th>Topic</th><th>Demos </th><th>Required Readings</th><th>Assignment</th></tr>
{% for lecture in site.data.all.lectures %}
<tr class = {{lecture.active|default("",true)}}>
<td> {{site.data.all.dates[forloop.index]}} </td> <td> {{lecture.topic | default("",true)}} </td>
<td> {{lecture.subtopic|default("", true)}}</td>
<td>
{{lecture.demos|default("", true)}}
</td>
<td>
{% if lecture.papers %}
<ul>
{% for paper in lecture.papers %}
{% if paper.cite %}
<li><div><a href="#cite_{{paper.cite}}">{{paper.name}}</a></div></li>
{% endif %}
{% if paper.link %}
<li><div>
{% if paper.section %}
{{paper.section}}:
{% endif %}
<a href="{{paper.link}}">{{paper.name}}</a></div></li>
{% endif %}
{% endfor %}
{% endif %}
</ul>
</td>
<td> {{lecture.hw | default("",true)}}</td>
</tr>
{% endfor %}
</table>
</div>
</div>
<!-- <div class="row container"> -->
<!-- <h3 id="cites">Citations</h3> -->
<!-- <table id="pubTable" class="table table-hover"></table> -->
<!-- <\!-- <script> -\-> -->
<!-- <\!-- $(function(){ -\-> -->
<!-- <\!-- bibtexify("page.bib", "pubTable", {"visualization":false});} -\-> -->
<!-- <\!-- ); -\-> -->
<!-- <\!-- $(function(){ -\-> -->
<!-- <\!-- var hash = window.location.hash; -\-> -->
<!-- <\!-- hash && $('ul.nav a[href="' + hash + '"]').tab('show'); -\-> -->
<!-- <\!-- $('.nav-tabs a').click(function (e) { -\-> -->
<!-- <\!-- $(this).tab('show'); -\-> -->
<!-- <\!-- var scrollmem = $('body').scrollTop() || $('html').scrollTop(); -\-> -->
<!-- <\!-- window.location.hash = this.hash; -\-> -->
<!-- <\!-- $('html,body').scrollTop(scrollmem); -\-> -->
<!-- <\!-- }); -\-> -->
<!-- <\!-- }); -\-> -->
<!-- <\!-- </script> -\-> -->
<!-- </div> -->
</div>
<!--div id="grading_tab" class="row tab-pane fade">
<div class="row container">
<p class="container">
Grades are determined by four aspects of the class:
<ul>
<li> Assignments (35%) </li>
<li> Scribing (10%) </li>
<li> Midterm Exam (15%) </li>
<li> Final Project (40%) </li>
</ul>
</p>
</div>
</div-->
<!--div id="homework_tab" class="row tab-pane fade">
<div class="row container">
<p class="container">
<ul>
<li>T0 <a href="https://github.com/harvard-ml-courses/cs281-f17-homework/tree/master/T0">Preliminary</a> (<a href="https://canvas.harvard.edu/courses/29707/assignments/161722">submit</a>). Due on <font color="red">Sep 8 at 5pm</font>.</li>
<li>T1 <a href="https://github.com/harvard-ml-courses/cs281-f17-homework/tree/master/T1">Fundamentals</a> (<a href="https://canvas.harvard.edu/courses/29707/assignments/167410">submit</a> | <a href="">self-grading</a>)</li>
</ul>
</p>
</div>
</div-->
</div>
<!-- <div class="row container"> -->
<!-- <h3 id="faq">FAQ</h3> -->
<!-- <p class="container"> -->
<!-- <ul> -->
<!-- <li> <p> </p> -->
<!-- </ul> -->
<!-- </p> -->
<!-- </div> -->
</div> <!-- /container -->
</body>
</html>
<head>
</head>
<html>
</html>