 |
|
|
10-702: Statistical Machine Learning WH 5409, MW 1:30-2:50P |
|||||||
| Week | Date | Day | Lecture | Topic | Notes/Assignments | Due | |
| 1 | Jan 12 |
M | 1 (J/L) |
Statistical and
computational thinking |
Syllabus |
||
| Jan 14 |
W | 2 (L) |
Probability and
statistics review |
Hwk 1 R code for question 3 Solutions |
|||
| 2 | Jan 19 |
M | No Class: MLK Day | ||||
| Jan 21 |
W | 3 (J) |
Convexity and
optimization |
Hwk 1 (Friday) |
|||
| 3 | Jan 26 |
M | 4 (L) |
Linear models |
|||
| Jan 28 |
W | 5 (L) |
Model selection |
Hwk 2 Solutions |
|||
| 4 | Feb 2 |
M | 6 (J) |
Linear
classification and Logistic Regression |
|||
| Feb 4 |
W | 7 (J) |
Mixture Models |
Hwk 2 (Friday) |
|||
| 5 | Feb 9 |
M | 8 (J) |
Undirected graphs |
|||
| Feb 11 |
W | 9 (L) |
Nonparametric
regression |
Hwk 3 Solutions |
|||
| 6 | Feb 16 |
M | 10 (L) |
Nonparametric
regression and classification |
Project proposals | ||
| Feb 18 |
W | 11 (L) |
Nonparametric
classification |
Hwk 3 (Friday) |
|||
| 7 | Feb 23 |
M | 12 (J) |
Structured prediction |
|||
| Feb 25 |
W | 13 (J) |
Kernels |
Hwk 4 flies.txt xy.Rdata Solutions |
|||
| 8 | Mar 2 |
M | 14 (J) |
Classification consistency |
|||
| Mar 4 |
W | Midterm exam |
practice midterm | ||||
| 9 | Mar 9 |
M | Spring break; no class | ||||
| Mar 11 |
W | ||||||
| 10 | Mar 16 |
M | 15 (L) |
Simulation
approximations |
|||
| Mar 18 |
W | 16 (J) |
Variational approximations |
Hwk 5 tree.txt soln 5 Low soln 5 Minh soln 5 Yuandong soln 5 Jiyan |
|||
| 11 | Mar 23 |
M | 17 (J) |
Nonparametric Bayes |
|||
| Mar 25 |
W | 18 (L) |
Minimax theory |
Hwk 4 (Friday) |
|||
| 12 | Mar 30 |
M | 19 (L) |
Minimax theory |
|||
| Apr 1 |
W | 20 (L) |
Concentration of measure |
Project Progress report (Wed) |
|||
| 13 | Apr 6 |
M | 21 (J) |
Dimension reduction |
|||
| Apr 8 |
W | 22 (L) |
Fast rates for classification | Hwk 5 (Friday) |
|||
| 14 | Apr 13 |
M | 23 (J) |
Sparsity and high dimensional inference | Hwk 6 soln 6 April soln 6 Low soln 6 Ming soln 6 Yuandong |
||
| Apr 15 |
W | 24 (L) |
Sparsity and high dimensional inference |
||||
| 15 | Apr 20 |
M | 25 (J) |
Active learning |
|||
| Apr 22 |
W | 26 (L) |
The Bootstrap |
Hwk 6 (Friday) |
|||
| 16 | Apr 27 |
M | 25 (J) |
Semisupervised Learning |
Project ads (due Apr 26) |
||
| Apr 29 |
W | 26 (J/L) |
Epilogue and student project ads |
Presentation line-up | |||
| Final
projects due
Monday, May 4 |
|||||||