EECS 281a / STAT 241a
Statistical Learning Theory --- Graphical Models

• Practical information
• Course description
• Updates
• Supplementary reading
• Handouts

Practical information

Lectures: Tues/Thurs 14:00--15:30, LeConte Hall 2.

Recitations (optional): Wednesday 09:00--10:30, 306 Soda Hall.

Course reader: An Introduction to Probabilistic Graphical Models, by M. Jordan. Available at Copy Central, 44 Shattuck Square, starting 8/28.

Grading: Homework (60%) and Course Projects (40%), OR Homework (60%), Course Project (20%) and Exam (20%)

Instructors:

Martin Wainwright

Office Hours: Tues, Thurs 3:30--4:30, 263 Cory

Email: wainwrig AT eecs DOT berkeley DOT edu

Phone: 643-1978

Office: 263 Cory Hall

Graduate student instructors:

Andre Wibisono

Office Hours: Monday 4--5 pm, 411 Soda Hall

Email: wibisono AT eecs DOT berkeley DOT edu

Hongwei Li

Office Hours: Friday 2--3 pm, 307 Evans Hall

Email: hwli AT stat DOT berkeley DOT edu

• Basics on graphical models, Markov properties, recursive decomposability, elimination algorithms
• Sum-product algorithm, factor graphs, semi-rings
• Markov properties of graphical models
• Junction tree algorithm
• Chains, trees, factorial models, coupled models, layered models
• Kalman filtering and Rauch-Tung-Striebel smoothing
• Hidden Markov models (HMM) and forward-backward
• Exponential family, sufficiency, conjugacy
• Frequentist and Bayesian methods
• The EM algorithm
• Conditional mixture models, hierarchical mixture models
• Factor analysis, principal component analysis (PCA), canonical correlation analysis (CCA), independent component analysis (ICA)
• Importance sampling, Gibbs sampling, Metropolis-Hastings
• Variational algorithms: mean field, belief propagation, convex relaxations
• Dynamical graphical models
• Model selection, marginal likelihood, AIC, BIC, and MDL
• Applications to signal processing, bioinformatics, communication, computer vision, etc.

Homework: Although it is acceptable for students to discuss the homework assignments with one another, each student must write up his/her homework on an individual basis. Each student must indicate with whom (if anyone) they discussed the homework problems. Homeworks must be turned in at the beginning of class on the due date. Late homeworks will not be accepted. We will not accept electronic submissions.

Course project: The course project will involve independent work on a topic of the student's own choosing. Course projects will be presented in an informal poster session at the end of semester, and the work will be summarized in a write-up.

Back to top

Updates and Announcements