
Topic 
Reading 
Aug 27 
Introduction; directed graphical models 
1, 2.1

Sep 1 
directed graphical models 
2.1

Sep 3 
undirected graphical models. Eliminate 
2.2, 2.3, 3

Sep 8 
Inference and chordal graphs 
3, Notes on chordal graphs, 4.1

Sep 10 
Factor graphs. Inference in factor trees. 
4.2, 4.3

Sep 15 
Parameter estimation 
5, 6.3

Sep 17 
Linear regression. Generative and discriminative classification.

6.4, 7.1, 7.2

Sep 22 
Logistic regression. Exponential family. 
7.3, 8.1

Sep 24 
Exponential family. Generalized Linear Models 
8.1, 8.2, 8.4

Sep 29 
Estimation in Completely Observed Graphical Models 
9,
Notes on chordal graphs

Oct 1 
IPF. Maximum likelihood. Maximum entropy 
9, Variational Inference chapter

Oct 6 
IPF as Iprojection. Generalized iterative scaling. 
9, Variational Inference chapter

Oct 8 
EM  Alekh Agarwal 
10, 11

Oct 13 
EM  Joe Neeman 
11

Oct 15 
HMMs  Alekh Agarwal 
12

Oct 22 
Multivariate Gaussians. Factor Analysis. 
13, 14.
slides

Oct 27 
Factor Analysis. State Space Models 
14, 15.
vec
notes
slides

Oct 29 
State Space Models. Kalman Filter. 
15.
slides

Nov 3 
Junction Tree Algorithm 
17.
slides

Nov 5 
Junction Tree in Trees, HMMs, SSMs 
18
slides

Nov 10 
Monte Carlo Methods 
slides

Nov 12 
Monte Carlo Methods 
slides

Nov 19 
Variational Methods 
Variational Inference chapter
slides

Nov 24 
Variational Methods 
Variational Inference chapter
slides

Nov 26 
Thanksgiving 

Dec 1 
Project Poster Session: Stat 241A 
In 306 Soda.

Dec 3 
Project Poster Session CS 281A 
In 430 Soda (Woz Lounge).
