
10702: Statistical Machine Learning GHC 4215, TR 1:302:50P Google Group Page 
Week  Date  Day  Lecture  Topic  Notes/Assignments  Due  
1  Jan 12 
T  1 (J) 
Statistical and computational thinking  Syllabus 

Jan 14 
R  2 (L) 
Linear models 
Hwk 1 R code for question Solution 

3  Jan 19 
T  3 (L) 
Model selection  
Jan 21 
R  4 (J) 
Convexity  Hwk 1 (Friday) 

3  Jan 26 
T  5 (J) 
Optimization  Hwk 2 Solutions 

Jan 28 
R  6 (J) 
Undirected graphical models  
4  Feb 2 
T  7 (L) 
Nonparametric density estimation  
Feb 4 
R  8 (L) 
Nonparametric regression (1/2)  Hwk 2 (Friday) 

5  Feb 9 
T  9 (*) 
No class  snow day  Hwk 3 Solutions 

Feb 11 
R  10 (L) 
Nonparametric regression (2/2)  
6  Feb 16 
T  11 (L) 
Nonparametric classification  Project proposals  
Feb 18 
R  12 (J) 
Nonparametric graphical models  Hwk 3 (Friday) 

7  Feb 23 
T  13 (J) 
Simulation  Hwk 4 Solutions 

Feb 25 
R  14 (J) 
Variational methods  
8  Mar 2 
T  15 (J) 
Structured prediction  
Mar 4 
R  Midterm exam 
practice midterm  
9  Mar 9 
T  Spring break; no class  
Mar 11 
R  
10  Mar 16 
T  16 (L) 
Nonparametric Bayes  
Mar 18 
R  17 (L) 
Fast rates for classification  Hwk 4 (Friday) 

11  Mar 23 
T  18 (J) 
Classification consistency  Hwk 5 Solutions 

Mar 25 
R  19 (J) 
Random projection  
12  Mar 30 
T  20 (L) 
Concentration of measure (1/2)  
Apr 1 
R  21 (L) 
Concentration of measure (2/2)  Hwk 5 (Friday) 

13  Apr 6 
T  22 (L) 
Minimax theory (1/2)  Hwk 6 Solutions 

Apr 8 
R  23 (J) 
Sparsity and high dimensional inference (1/2)  Project progress report (Friday) 

14  Apr 13 
T  24 (J) 
Sparsity and high dimensional inference (2/2)  
Apr 15 
R  25 (L) 
Clustering and dimension reduction  Hwk 6 (Friday) 

15  Apr 20 
T  26 (J) 
Manifold learning  
Apr 22 
R  27 (J) 
TBD  
16  Apr 27 
T  28 (C) 
Student project spotlights  Project spotlights  
Apr 29 
R  29 (C) 
No class  project preparation  
Final
projects due
Tuesday, May 4 