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Lecture 11 Slides May 2 nd , 2006

University of Washington Department of Electrical Engineering EE512 Spring, 2006 Graphical Models Jeff A. Bilmes <bilmes@ee.washington.edu>. Lecture 11 Slides May 2 nd , 2006. Announcements. READING: M. Jordan: Chapters 4,10,12,17,18 Reminder: TA discussions and office hours:

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Lecture 11 Slides May 2 nd , 2006

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  1. University of WashingtonDepartment of Electrical Engineering EE512 Spring, 2006 Graphical ModelsJeff A. Bilmes <bilmes@ee.washington.edu> Lecture 11 Slides May 2nd, 2006 EE512 - Graphical Models - J. Bilmes

  2. Announcements • READING: • M. Jordan: Chapters 4,10,12,17,18 • Reminder: TA discussions and office hours: • Office hours: Thursdays 3:30-4:30, Sieg Ground Floor Tutorial Center • Discussion Sections: Fridays 9:30-10:30, Sieg Ground Floor Tutorial Center Lecture Room • Reminder: take-home Midterm: May 5th-12th, you must work alone on this. • Note: I am gone all next week (May 8th-12th). Subsequent weeks we will have makeup classes on Mondays at 6:00pm. EE512 - Graphical Models - J. Bilmes

  3. Class Road Map • L1: Tues, 3/28: Overview, GMs, Intro BNs. • L2: Thur, 3/30: semantics of BNs + UGMs • L3: Tues, 4/4: elimination, probs, chordal I • L4: Thur, 4/6: chrdal, sep, decomp, elim • L5: Tue, 4/11: chdl/elim, mcs, triang, ci props. • L6: Thur, 4/13: MST,CI axioms, Markov prps. • L7: Tues, 4/18: Mobius, HC-thm, (F)=(G) • L8: Thur, 4/20: phylogenetic trees, HMMs • L9: Tue, 4/25: HMMs, inference on trees • L10: Thur, 4/27: Inference on trees, start poly • L11: Tues, 5/2: polytrees, start JT inference • L12: Thur, 5/4 • L13: Tues, 5/9 • L14: Thur, 5/11 • L15: Tue, 5/16 • L16: Thur, 5/18 • L17: Tues, 5/23 • L18: Thur, 5/25 • L19: Tue, 5/30 • L20: Thur, 6/1: final presentations EE512 - Graphical Models - J. Bilmes

  4. Final Project Milestone Due Dates • L1: Tues, 3/28: • L2: Thur, 3/30: • L3: Tues, 4/4: • L4: Thur, 4/6: • L5: Tue, 4/11: • L6: Thur, 4/13: • L7: Tues, 4/18: • L8: Thur, 4/20: Team Lists, short abstracts I • L9: Tue, 4/25: • L10: Thur, 4/27: short abstracts II • L11: Tues, 5/2: today • L12: Thur, 5/4: abstract II + progress • L13: Tues, 5/9 • L14: Thur, 5/11: 1 page progress report • L15: Tue, 5/16 • L16: Thur, 5/18: 1 page progress report • L17: Tues, 5/23 • L18: Thur, 5/25: 1 page progress report • L19: Tue, 5/30 • L20: Thur, 6/1: final presentations • L21: Tue, 6/6 4-page papers due (like a conference paper). • Team lists, abstracts, and progress reports must be turned in, in class and using paper (dead tree versions only). • Final reports must be turned in electronically in PDF (no other formats accepted). • Progress reports must report who did what so far!! EE512 - Graphical Models - J. Bilmes

  5. Summary of Last Time • Inference on trees • Inference on undirected trees • Example: voting tallying by message passing in trees • Begin inference on poly trees EE512 - Graphical Models - J. Bilmes

  6. Outline of Today’s Lecture • inference on poly trees • Begin exact inference on junction trees EE512 - Graphical Models - J. Bilmes

  7. Books and Sources for Today • M. Jordan: Chapters 4,10,12,17,18 • J. Pearl, Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference, 1988. EE512 - Graphical Models - J. Bilmes

  8. Bottom up Inference in undirected trees EE512 - Graphical Models - J. Bilmes

  9. Inference in undirected trees EE512 - Graphical Models - J. Bilmes

  10. Inference in undirected trees EE512 - Graphical Models - J. Bilmes

  11. Inference in undirected trees EE512 - Graphical Models - J. Bilmes

  12. Inference in undirected trees EE512 - Graphical Models - J. Bilmes

  13. Inference in polytrees EE512 - Graphical Models - J. Bilmes

  14. Inference in polytrees EE512 - Graphical Models - J. Bilmes

  15. Required Messages EE512 - Graphical Models - J. Bilmes

  16. Inference in polytrees EE512 - Graphical Models - J. Bilmes

  17. Inference in polytrees EE512 - Graphical Models - J. Bilmes

  18. Required Messages EE512 - Graphical Models - J. Bilmes

  19. Inference in polytrees EE512 - Graphical Models - J. Bilmes

  20. Inference in polytrees EE512 - Graphical Models - J. Bilmes

  21. Inference in polytrees: summary EE512 - Graphical Models - J. Bilmes

  22. What if cycles exist? EE512 - Graphical Models - J. Bilmes

  23. Ex: messages not valid EE512 - Graphical Models - J. Bilmes

  24. Inference EE512 - Graphical Models - J. Bilmes

  25. Inference: outline EE512 - Graphical Models - J. Bilmes

  26. Inference: moralization EE512 - Graphical Models - J. Bilmes

  27. Examples: assigning prob to clique potentials EE512 - Graphical Models - J. Bilmes

  28. Examples: assigning prob to clique potentials EE512 - Graphical Models - J. Bilmes

  29. Evidence EE512 - Graphical Models - J. Bilmes

  30. Goal calculation & Evidence EE512 - Graphical Models - J. Bilmes

  31. Example potentials EE512 - Graphical Models - J. Bilmes

  32. Goal EE512 - Graphical Models - J. Bilmes

  33. Potentials as marginals EE512 - Graphical Models - J. Bilmes

  34. Potentials don’t start as marginals EE512 - Graphical Models - J. Bilmes

  35. Potentials don’t start as marginals EE512 - Graphical Models - J. Bilmes

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