Localised Natural Causal Learning Algorithms for Weak Consistency Conditions

Kai Z. Teh, Kayvan Sadeghi, Terry Soo

Keywords: Causal Discovery, Graphical Models

TL;DR: Causal discovery algorithm that works under weak conditions

Abstract: By relaxing conditions for “natural” structure learning algorithms, a family of constraint-based algorithms containing all exact structure learning algorithms under the faithfulness assumption, we define localised natural structure learning algorithms (LoNS). We also provide a set of necessary and sufficient assumptions for consistency of LoNS, which can be thought of as a strict relaxation of the restricted faithfulness assumption. We provide a practical LoNS algorithm that runs in exponential time, which is then compared with related existing structure learning algorithms, namely PC/SGS and the relatively recent Sparsest Permutation algorithm. Simulation studies are also provided.

List Of Authors: Teh, Kai and Sadeghi, Kayvan and Soo, Terry

Submission Number: 162