An Algorithm for Fast Recovery of Sparse Causal Graphs


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..



    Upload a copy of this work     Papers currently archived: 92,100

External links

Setup an account with your affiliations in order to access resources via your University's proxy server

Through your library

  • Only published works are available at libraries.

Similar books and articles


Added to PP

58 (#277,332)

6 months
3 (#981,027)

Historical graph of downloads
How can I increase my downloads?

Author's Profile

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.

View all 8 citations / Add more citations

References found in this work

No references found.

Add more references