Lecture time: Mondays & Wednesdays

Place: Science Engineering Complex, Room 136

Instructor: Tina EliassiRad

Office hours: Mondays 5:00 Ð 6:00 PM in WVH 242

TA: Xuan Han

TA office hours: Wednesdays and Thursdays 6:00 Ð 7:00 PM in WVH 242

This 4credit graduatelevel course covers data mining and unsupervised
learning. Its prerequisites are:
This course does not have a designated textbook. The
readings are assigned in the syllabus (see below). Here are some textbooks (all
optional) related to the course.
Lec
# 
Date 
Topic 
Readings & Notes 
1 
M 1/9 
Introduction and Overview 
o Chapter 1 of http://www.mmds.org/#book 
2 
W 1/11 
Frequent Itemsets
& Association Rules 
o Chapter 6 of http://www.mmds.org/#book o Optional: Sections 6.16.6 of http://wwwusers.cs.umn.edu/~kumar/dmbook/ch6.pdf

Ð 
M 1/16 
MLK Jr Day Ð no class Ð 

3 
W 1/18 
Frequent Itemsets
& Association Rules 
o Chapter 6 of http://www.mmds.org/#book o Optional: Sections 6.16.6 of http://wwwusers.cs.umn.edu/~kumar/dmbook/ch6.pdf

4 
M 1/23 
Density Estimation 
o http://ned.ipac.caltech.edu/level5/March02/Silverman/Silver_contents.html
o http://www.stat.washington.edu/courses/stat527/s13/readings/Sheather_StatSci_2004.pdf
o Optional: Sections 6.66.9 of http://statweb.stanford.edu/~tibs/ElemStatLearn/printings/ESLII_print10.pdf

Homework
#1 o out on Monday January 23 o due on Sunday February 5 at 11:59 PM
Eastern o grade by Monday February 20 

5 
W 1/25 
Finding Similar Items 
o Chapter
3 of http://www.mmds.org/#book 
6 7 
M 1/30 W 2/1 
Mining Data Streams 
o Chapter
4 of http://www.mmds.org/#book 
8 9 
M 2/6 W 2/8 
Dimensionality Reduction (PCA, SVD,
CUR, Kernel PCA) 
o Chapter
11 of http://www.mmds.org/#book o
Section
14.5 of http://statweb.stanford.edu/~tibs/ElemStatLearn/printings/ESLII_print10.pdf

Homework
#2 o out on Wednesday February 8 o due on Tuesday February 21 at 11:59 PM
Eastern o grade by Monday March 13 

10 11 
M 2/13 W 2/15 
Clustering: 
o Chapter 9 of http://robotics.stanford.edu/~nilsson/MLBOOK.pdf
o Sections 7.17.3 of http://www.mmds.org/#book o Chapter 8 of https://www.cs.cornell.edu/jeh/book2016June9.pdf o Section 14.3 of http://statweb.stanford.edu/~tibs/ElemStatLearn o http://cs229.stanford.edu/notes/cs229notes7b.pdf o http://cs229.stanford.edu/notes/cs229notes8.pdf o Optional: https://www.cs.rutgers.edu/~mlittman/courses/lightai03/jain99data.pdf
o Optional: http://web.itu.edu.tr/sgunduz/courses/verimaden/paper/validity_survey.pdf o Optional: http://www.dbs.ifi.lmu.de/Publikationen/Papers/KDD96.final.frame.pdf

Ð 
M 2/20 
PresidentÕs Day 

12 13 
W 2/22 M 2/27 
EM, Kmediods,
Hierarchical Clustering, Evaluation Metrics and Practical Issues 
o Same readings as for 2/13 and 2/15 
14 
W 3/1 
Midterm
Exam 
Grade by Monday March 13 
Ð 
M 3/06 W 3/08 
Spring Break Ð no class Ð 

15 
M 3/13 
Project
Proposal Pitches + Review
of Midterm 

16 
W 3/15 
Spectral Clustering 
o http://ai.stanford.edu/~ang/papers/nips01spectral.pdf o http://www.cs.columbia.edu/~jebara/4772/papers/Luxburg07_tutorial.pdf 
17 
M 3/20 
Link Analysis 
o Chapter
5 of http://www.mmds.org/#book o Optional: http://bit.ly/2iYxo82 
18 
W 3/22 
Recommendation Systems 
o Chapter
9 of http://www.mmds.org/#book 
19 
M 3/27 
Matrix Factorization 
o Chapter 14.6 of http://statweb.stanford.edu/~tibs/ElemStatLearn/ o
http://papers.nips.cc/paper/1861algorithmsfornonnegativematrixfactorization.pdf
o Optional: http://www.sandia.gov/~tgkolda/pubs/pubfiles/TensorReview.pdf

Homework
#3 o out on Monday March 27 o
due
on Sunday April 9^{ }at 11:59 PM Eastern o grade by Monday April 24 

20 21 
W 3/29 M 4/3 
Topic Models 
o http://www.cs.columbia.edu/~blei/papers/Blei2012.pdf
o http://www.cs.princeton.edu/~blei/papers/Blei2011.pdf
o http://www.cs.columbia.edu/~blei/papers/BleiLafferty2009.pdf

22 
W 4/5 
Hidden Markov Models 

23 
M 4/10 
Model Selection Theory of Clustering 
o Sections 7.77.8 of http://statweb.stanford.edu/~tibs/ElemStatLearn/
o Section 8.12 of https://www.cs.cornell.edu/jeh/book2016June9.pdf

24 
W 4/12 
Final
Exam 
Grade by
Sunday April 30 
Ð 
M 4/17 
PatriotÕs Day Ð no class Ð 

25 
W 4/19 
Project
Presentations 
Last class
day 
Project
reports o due on Wednesday April 26 at 11:59 PM o grade by Sunday April 30 

Final
grades deadline on Monday May 1 at 9:00 AM 
A 
93Ð100 
A 
90Ð92 
B+ 
87Ð89 
B 
83Ð86 
B 
80Ð82 
C+ 
77Ð79 
C 
73Ð76 
C 
70Ð72 
F 
< 70 