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) |

## Calendar

## Course Info

##### Instructor

##### Departments

##### As Taught In

Fall
2014

##### Level

##### Topics

##### Learning Resource Types

*notes*Lecture Notes

*assignment*Problem Sets

*grading*Exams