Computer Science 688 - Probabilistic Graphical Models

Spring
2019
01
3.00
Justin Domke
M W 4:00PM 5:15PM
UMass Amherst
12887
Goessmann Laboratory room 20
domke@cs.umass.edu
This course will cover Bayesian and Markov networks and their dynamic and relational extensions; exact and approximate inference methods; estimation of both the parameters and structure of graphical models.
Open to Graduate students only. SEATS HELD FOR INCOMING GRAD STUDENT REGISTRATION. STUDENTS NEEDING SPECIAL PERMISSION MUST REQUEST OVERRIDES VIA THE ON-LINE FORM: https://www.cics.umass.edu/overrides.
Permission is required for interchange registration during the add/drop period only.
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