IDS.136
Graphical Models: A Geometric, Algebraic, and Combinatorial Perspective
Provides instruction in the geometric, algebraic and combinatorial perspective on graphical models. Presents methods for learning the underlying graph and inferring its parameters. Topics include exponential families, duality theory, conic duality, polyhedral geometry, undirected graphical models, Bayesian networks, Markov properties, total positivity of distributions, hidden variables, and tensor decompositions.
Prerequisites & course information
Same subject as 6.7820J Prereq: 6.3702 and 18.06 G (Fall) Not offered regularly; consult department 3-0-9 units
Sources
- Course catalogue ↗2026–2027