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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..Author's Profile
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Citations of this work
Detection of unfaithfulness and robust causal inference.Jiji Zhang & Peter Spirtes - 2008 - Minds and Machines 18 (2):239-271.
Learning Bayesian networks from data: An information-theory based approach.Jie Cheng, Russell Greiner, Jonathan Kelly, David Bell & Weiru Liu - 2002 - Artificial Intelligence 137 (1-2):43-90.
A local method for identifying causal relations under Markov equivalence.Zhuangyan Fang, Yue Liu, Zhi Geng, Shengyu Zhu & Yangbo He - 2022 - Artificial Intelligence 305 (C):103669.
Decomposition of structural learning about directed acyclic graphs.Xianchao Xie, Zhi Geng & Qiang Zhao - 2006 - Artificial Intelligence 170 (4-5):422-439.
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