18997

Video URL

https://simons.berkeley.edu/talks/introduction-causal-discovery-methods

Classical Strategies and Concepts in Causal Discovery

(2022). Classical Strategies and Concepts in Causal Discovery. The Simons Institute for the Theory of Computing. https://simons.berkeley.edu/talks/introduction-causal-discovery-methods

Classical Strategies and Concepts in Causal Discovery. The Simons Institute for the Theory of Computing, Jan. 19, 2022, https://simons.berkeley.edu/talks/introduction-causal-discovery-methods 

          @misc{ scivideos_18997,
            doi = {},
            url = {https://simons.berkeley.edu/talks/introduction-causal-discovery-methods},
            author = {},
            keywords = {},
            language = {en},
            title = {Classical Strategies and Concepts in Causal Discovery},
            publisher = {The Simons Institute for the Theory of Computing},
            year = {2022},
            month = {jan},
            note = {18997 see, \url{https://scivideos.org/Simons-Institute/18997}}
          }
Daniel Malinsky (Columbia University)
Talk number18997
Source RepositorySimons Institute
Subject

Abstract

An overview of the classical strategies (constraint-based algorithms, score-based algorithms) in learning causal DAGs. Relevant graphical and statistical concepts will be discussed, including Markov equivalence, faithfulness, conditional independence testing, consistency of the BIC score for selection, and theoretical properties of methods such as the PC algorithm and GES algorithm.