Modularization of complex tasks

Description

Divide and conquer techniques are widespread in computer science, but have not been explored thoroughly in graphical models. A method for splitting up a Bayesian network into components that can be treated independently with respect to many of the common operations has been constructed . This method forms the foundation for various tasks such as distributed triangulation and hybrid inference. Special emphasis has been directed towards the development of algorithms for incremental compilation.
StatusActive
Effective start/end date19/05/2010 → …

Funding

  • <ingen navn>

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Network components
Bayesian networks
Triangulation
Computer science