6.438 | Fall 2014 | Graduate

Algorithms for Inference

Calendar

SES # TOPICS KEY DATES
1 Introduction, Overview, Preliminaries Problem Set 1 Out
2 Directed Graphical Models  
3 Undirected Graphical Models  
4 Factor Graphs; Generating And Converting Graphs Problem Set 2 Out, Problem Set 1 Due
5 Minimal I-Maps, Chordal Graphs, Trees And Markov Chains  
6 Gaussian Graphical Models Problem Set 3 Out, Problem Set 2 Due
7 Inference On Graphs: Elimination Algorithm  
8 Inference On Trees: Sum-Product Algorithm Problem Set 4 Out, Problem Set 3 Due
9 Forward-Backward Algorithm, Sum-Product On Factor Graphs  
10 Sum-Product On Factor Graphs, MAP Elimination  
11 The Max-Product Algorithm Problem Set 5 Out, Problem Set 4 Due
12 Midterm Evening Quiz (Through Lecture 11 And Problem Set 4)  
13 Gaussian Belief Propagation  
14 Gaussian HMMs And Kalman Filtering  
15 The Junction Tree Algorithm Problem Set 6 Out, Problem Set 5 Due
16 Loopy Belief Propagation - Part I  
17 Loopy Belief Propagation - Part II  
18 Variational Inference Problem Set 7 Out
19 MCMC Methods And Approximate MAP Problem Set 6 Due
20 Approximate Inference By Particle Methods Problem Set 8 Out, Problem Set 7 Due
21 Parameter Estimation In Directed Graphical Model  
22 Parameter Estimation In Undirected Graphical Model Problem Set 9 Out, Problem Set 8 Due
23 Estimating Structure Of Directed Graphical Model  
24 Estimating Structure Of Undirected Graphical Model / Exponential Family Problem Set 10 Out, Problem Set 9 Due
25 Parameter Estimation From Partial Observations: EM Algorithm  
26 Final Evening Quiz (Through Lecture 23 And Problem Set 9)  

Course Info

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As Taught In
Fall 2014
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