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Activity Number: 258 - On Recent Progress in Measuring Dependence and Conditional Dependence
Type: Invited
Date/Time: Tuesday, August 9, 2022 : 10:30 AM to 12:20 PM
Sponsor: IMS
Abstract #320652
Title: Non-Parametric Local Causal Structure Learning
Author(s): Mona Azadkia* and Armeen Taeb and Peter Bühlmann
Companies: ETH Zürich and ETH Zürich and ETH Zürich
Keywords: Conditional Independence; Non-parametric; Graphical models ; Markov boundary; Structural equation models
Abstract:

With the non-parametric measure of dependence CODEC, we introduce a computationally fast algorithm to find the set of parents of a response variable of interest. We provide theoretical guarantees of our procedure when the underlying DAG does not contain cycles. We give a conservative guarantee against false positive causal claims when the set of parents is identifiable.


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