Robert Rounthwaite

UAI Conference 2000 Conference Paper

Dependency Networks for Collaborative Filtering and Data Visualization

• David Heckerman
• Max Chickering
• Christopher Meek
• Robert Rounthwaite
• Carl Myers Kadie

JMLR Journal 2000 Journal Article

Dependency Networks for Inference, Collaborative Filtering, and Data Visualization

• David Heckerman
• David Maxwell Chickering
• Christopher Meek
• Robert Rounthwaite
• Carl Kadie

We describe a graphical model for probabilistic relationships--an alternative to the Bayesian network--called a dependency network. The graph of a dependency network, unlike a Bayesian network, is potentially cyclic. The probability component of a dependency network, like a Bayesian network, is a set of conditional distributions, one for each node given its parents. We identify several basic properties of this representation and describe a computationally efficient procedure for learning the graph and probability components from data. We describe the application of this representation to probabilistic inference, collaborative filtering (the task of predicting preferences), and the visualization of acausal predictive relationships.