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---
layout: page
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>Harvard CS 281</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:black;border-color:#000000;">
<div class="panel-heading" style="background-color:black;border-color:#2D6ED3;">
<h1>CS281: Advanced Machine Learning</h1>
<p class="lead">Jean-Baptiste Tristan & Michael L. Wick, Harvard University</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="#people_tab">People</a></li>
<li><a data-toggle="tab" href="#section_tab">Sections</a></li>
<li><a data-toggle="tab" href="#project_tab">Project</a></li>
<!--li><a data-toggle="tab" href="#grading_tab">Grading</a></li>
<li><a data-toggle="tab" href="#references_tab">References</a></li-->
<!-- <li><a href="#faq">FAQ</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 1:30-2:45pm</p>
<p><span style="font-size: 1.17em;font-weight: bold;">Location:</span> MD G115</p>
</div>
<div class="row container">
<h3 id="announcements_description">Announcements</h3>
<div class="container ">
<!-- <div class="panel-body"> -->
<ul>
<li>Warning: section time and room on Thursday has changed!</li>
<li>Office hours will start on September 9</li>
<li>First class: September 4</li>
</ul>
</div>
</div>
<div class="row container">
<h3 id="description">Course Info</h3>
<div class="container ">
<!-- <div class="panel-body"> -->
<dl>
<dt>Forum</dt>
<dd><ul>
<li><a href="https://piazza.com/class/jx40f52vrtf1fs">Piazza</a></li>
</ul></dd>
<dt>Section Times/Rooms</dt>
<dd><ul>
<li> Tuesday 3-4pm, MD323 </li>
<li> Thursday 1:30-2:30pm, Pierce 100F (except for 9/26 and 10/3 -- those dates will have to be in Northwest Building, 52 Oxford St., B166) </li>
</ul></dd>
<dt>Syllabus and Collaboration Policy</dt>
<dd>
<ul>
<li>See the course <a href="syllabus.pdf">syllabus</a>
</ul>
</dd>
<dt>Grading</dt>
<dd>
<ul>
<li> Assignments: 30% </li>
<li> Midterm exam: 10% </li>
<li> Reading exam: 10% </li>
<li> Project proposal: 10% </li>
<li> Status report: 10% </li>
<li> Project report: 25% </li>
<li> Piazza participation: 5% </li>
</ul>
</dd>
<dt>Links</dt>
<dd>
<ul>
<li><a href="https://canvas.harvard.edu/courses/61208">Canvas Site</a></li>
</ul>
</dd>
<dt>Texts</dt>
<dd><ul>
<li> Shai Shalev-Shwartz and Shai Ben-David, <a href="https://www.cs.huji.ac.il/~shais/UnderstandingMachineLearning/">Understanding Machine Learning: From Theory to Algorithms</a>
<li> Ian Goodfellow, Yoshua Bengio, and Aaron Courville, <a href="https://www.deeplearningbook.org/">Deep Learning</a>
<li> Christopher Bishop, <a href="https://www.amazon.com/Pattern-Recognition-Learning-Information-Statistics/dp/0387310738">Pattern Recognition and Machine Learning</a>
</ul></dd>
<dt>Other References</dt>
<dd><ul>
<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>
</div>
</div>
</div>
<!--div id="references_tab" class="row tab-pane fade">
<div class="row container">
<dl>
<dd><ul>
<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>
<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>
</div>
</div-->
<div id="schedule_tab" class="row tab-pane fade">
<div class="row container">
<div class="tab-content">
<table class="table table-striped table-hover">
<tr><th>Date</th> <th>Instructor</th> <th>Area</th> <th>Topic</th><th>Reference</th><th>Assignment</th><th>Project</th></tr>
{% for lecture in site.data.all.lectures %}
<tr style="line-height: 8px; height: 8px;" class = {{lecture.active|default("",true)}}>
<td> {{site.data.all.dates[forloop.index]}} </td>
<td> {{lecture.instructor | default("",true)}} </td>
<td> {{lecture.topic | default("",true)}} </td>
<td> {{lecture.subtopic|default("", true)}}</td>
<td>
<ul>
{% for paper in lecture.papers %}
<li>{{paper |default("", true)}}</li>
{% endfor %}
</ul>
</td>
<td> {{site.data.all.hw[forloop.index]}} </td>
<td> {{site.data.all.project[forloop.index]}} </td>
</tr>
{% endfor %}
</table>
</div>
</div>
</div>
<div id="section_tab" class="row tab-pane fade">
<div class="row container">
<div class="tab-content">
<table class="table">
<tr><th>Week</th> <th>Type</th> <th>Topic</th><th>TF </th><th>Reading</
th></tr>
{% for lecture in site.data.all.sections %}
<tr class = {{lecture.active|default("",true)}}>
<td> {{site.data.all.sections_dates[forloop.index]}} </td> <td>
{{lecture.topic
| default("",true)}} </td>
<td> {{lecture.subtopic|default("", true)}}</td>
<td>
{{lecture.instructor|default("", true)}}
</td>
<td> {{lecture.papers |default("", true)}} </td>
</tr>
{% endfor %}
</table>
</div>
</div>
</div>
<div id="people_tab" class="row tab-pane fade">
<div class="row container">
<dl>
<dt>Instructors</dt>
<dd> <ul>
<li><a href="mailto:[email protected]">Jean-Baptiste Tristan</a>
</li>
<li><a href="mailto:[email protected]">Michael L. Wick</a>
</li></ul>
</dd>
<dt>Head Teaching Fellow</dt>
<dd> <ul>
<li><a href="mailto:[email protected]">Jason Ma</a>
</li>
</dd>
<dt>Teaching Fellows</dt>
<dd>
<ul>
{% for ta in site.data.all.tas %}
<li>
{{ta.name}}
</li>
{% endfor %}
</ul>
</dd>
<dt>Office Hours</dt>
<dd>
<ul>
{% for oh in site.data.all.ohs %}
<li>{{oh.time}}: {{oh.location}}</li>
{% endfor %}
</ul>
</dd>
</dl>
</div>
</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/cs281-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/cs281-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">
<div class="row container">
<h3 id="announcements_description">Objective</h3>
<div class="container ">
<p>
The objective of this final project is to
explore new research in machine
learning. The ideal outcome would be a
paper that could be submitted a top
machine learning conferences.
</p>
<div class="row container">
<h4 id="announcements_description">Types of projects (Examples)</h4>
<div class="container ">
<div class="row container">
<h5 id="announcements_description">Advanced application</h5>
<div class="container ">
Use advanced machine learning techniques to provide a new solution to a problem.
</div>
</div>
<div class="row container">
<h5 id="announcements_description">Scalability</h5>
<div class="container ">
Improve an existing machine
learning algorithm to work under
constraints such as limited
memory, large datasets, or exotic
computing models. For example, you
could attempt to implement an
algorithm on a GPU, distribute it,
or use dimentionality reduction to
reduce its memory footprint.
</div>
</div>
<div class="row container">
<h5 id="announcements_description">Advanced experimentation</h5>
<div class="container ">
Compare different models. Devise new evaluation metrics.
</div>
</div>
<div class="row container">
<h5 id="announcements_description">Theory</h5>
<div class="container ">
</div>
</div>
</div>
</div>
</div>
</div>
<div class="row container">
<h3 id="announcements_description">Collaboration</h3>
<div class="container ">
<!-- <div class="panel-body"> -->
<p>
You should work in a group of 3 or 4 people.
Groups of 2 will be considered with permission.
Larger groups will not be permitted.
</p>
</div>
</div>
<div class="row container">
<h3 id="announcements_description">Deliverables</h3>
<div class="container ">
<!-- <div class="panel-body"> -->
<p>
There are three deliverables.
</p>
</div>
</div>
<div class="row container">
<h4 id="announcements_description">Proposal</h4>
<div class="container ">
<!-- <div class="panel-body"> -->
<p>
Write a two-page document
describing the plan for your
project. This should clearly state
what problem you are trying to
solve. If you have developed a new
model, explain what models this work
will build on and how it resolves
deficiencies. If it is a new
algorithm for inference, explain the
regimes for which you think it well
be well-suited. If you are
developing a new theoretical
contribution, discuss the theorems
you will prove. For problem-driven
papers, discuss the data and the
unique challenges that make this
interesting. Identify relevant work
and algorithms you intend to
implement as baselines. This does
not need to be a comprehensive
document and I expect that it will
be speculative. Your focus should be
on identifying the questions you
wish to answer about your data or
your method and specifying clearly
what success will mean.
</p>
</div>
</div>
<div class="row container">
<h4 id="announcements_description">Status report</h4>
<div class="container ">
<!-- <div class="panel-body"> -->
<p>
Write a four-page document to describe the
status of your project. What have you proved?
What baselines have you established? Have there
been unexpected results, good or bad?
</p>
</div>
</div>
<div class="row container">
<h4 id="announcements_description">Final report</h4>
<div class="container ">
<!-- <div class="panel-body"> -->
<p>
Using the NeurIPS conference paper
format (available at http://nips.cc), write a paper of up to
ten pages. This paper should have a
typical conference style, with
abstract, introduction, etc. You
should clearly state what problem
you are trying to solve, introduce
and explain your approach, and
review the relevant literature. It
should explain in detail the
experiments that were run, show
their results and discuss
conclusions that can be drawn.
</p>
</div>
</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>
<script>
$(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);
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</script>
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