An Algorithm for Fast Recovery of Sparse Causal Graphs

Abstract

Previous asymptotically correct algorithms for recovering causal structure from sample probabilities have been limited even in sparse graphs to a few variables. We describe an asymptotically correct algorithm whose complexity for fixed graph connectivity increases polynomially in the number of vertices, and may in practice recover sparse graphs with several hundred variables. From..

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2010-12-22

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Peter Spirtes
Carnegie Mellon University

Citations of this work

Belief networks revisited.Judea Pearl - 1993 - Artificial Intelligence 59 (1-2):49-56.
Jon Williamson bayesian nets and causality.Clark Glymour - 2009 - British Journal for the Philosophy of Science 60 (4):849-855.

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