Class Website

Project specification

Notation

- means “X and Y are independent given Z”.
- means “X,Y, and Z are in a graph such that Z separates X from Y.
- “Belief in ”: posterior marginal on conditioned on all evidence.

Exhaustively enumerating all exceptions in a logical system is intractable.

Logic systems have a difficult time handling non-monotonic reasoning.

Bayesian logic addresses these issues through `explaining away`

.

When `evidence`

is known, we want to update our belief in the system by producing a posterior distribution.

Class outline:

- Graphical models
- inference: Bucket elimination for bayesian and Markov networks
- Dependency graph properties
- Inference: tree decomposition algorithms
- approximation by bounded inference
- Search: AND/OR search spaces
- Approximation by sampling
- Hybrid of search inference
- Learning and Causality

Chordal Graphs

[http://reasoning.cs.ucla.edu/samiam/ SamIam]

[http://en.wikipedia.org/wiki/Bayes_factor Bayes Factor] for soft evidence

Modeling with Bayesian Networks

[http://en.wikipedia.org/wiki/Convolution_code Convolutional Codes] (Darwiche 105)

Discuss the class project

Full OR search trees

Context Minimal OR search graph

AND-OR Trees

Pseudo-Trees

Mini-clustering

Variational Inference