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CIS 8535: Probabilistic Graphical Models |
Spring 2012
Department of Computer & Information Sciences
Temple University
Instructor: Yuhong Guo, Wachman Hall 311, 215-204-8455, yuhong(at)temple.edu
Lecture Time: Thur 5:30pm-8:00pm, TL 01B
Office Hours: Thur 3:30pm-5:30pm, or by appointment
| Date | Content (please check blackboard) |
| Week 1: Jan. 19 | Introduction to Graphical Models, Bayesian Network Representations |
| Week 2: Jan. 26 | Naive Bayes, TAN, BN Parameter Learning |
| Week 3: Feb. 02 | BN Structure Learning |
| Week 4: Feb. 09 |
Multivariate Gaussian,
Linear Gaussian Networks
(Assignment 1 out, paper selection list out) |
| Week 5: Feb. 16 |
Exponential Family Models,
(Project list out, proposal assignment out) |
| Week 6: Feb. 23 |
Learning with Incomplete Data, EM
Mixture Models,
(Assignment 1 due ) |
| Week 7: Mar. 01 | Markov Networks |
| Week 8: Mar. 15 |
HMM and
Conditional Random Fields
(project proposal due) |
| Week 9: Mar. 22 | Midterm |
| Week 10: Mar. 29 |
Inference: Junction Trees
Presentations: paper 1 and 2 |
| Week 11: Apr. 05 |
Inference: Junction Trees,
Sampling
Presentations: paper 3 and 5 |
| Week 12: Apr. 12 | Paper Presentation |
| Week 13: Apr. 19 |
Paper Presentation
Paper review due |
| Week 14: Apr. 26 | Final Project Presentation |
| Week 15: May 07 | Final project report due |