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Introduction to Probabilistic Graphical Models |
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Course Information
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Time: Sundays Place: Ziskind 1 Background Material: Information Theory – you may read the preface of the e-book written by David MacKay, "Information Theory, Pattern Recognition and Neural Networks" http://vision.eng.shu.ac.uk/neural/Bayesian/wol.ra.phy.cam.ac.uk/mackay/itprnn/ You may also read the first two chapters in the book "Elements of Information Theory" by Thomas and Cover. Probability Theory – you may read the following introductory chapter from Gal Chechik's book, http://robotics.stanford.edu/~gal/Book/chap1.pdf News: > The exam from 2007 is available HERE. You can use it to study... Good luck! > You can find all of your graded ex's in the course mail box (entitled PGM) in the second floor. > The material for the exam will be all the Ex's and all the presentations. The book handouts are not included. > Exercise 9 was the last one, there is no Ex. 10. > Handouts of chapter 12 (Approx. Inference) are available at room 125. Come and get them... > People that need more handouts, please contact the TA Ohad at room 125 or phone 4303 > Mark your calendars! The exam in PGM will take place on Sunday, July 12th, between 10am-1pm
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