Video URL

https://simons.berkeley.edu/talks/choosing-between-dags-can-be-hard

Choosing Between Dags Can Be Hard

(2022). Choosing Between Dags Can Be Hard. The Simons Institute for the Theory of Computing. https://simons.berkeley.edu/talks/choosing-between-dags-can-be-hard

Choosing Between Dags Can Be Hard. The Simons Institute for the Theory of Computing, Feb. 11, 2022, https://simons.berkeley.edu/talks/choosing-between-dags-can-be-hard 

          @misc{ scivideos_19617,
            doi = {},
            url = {https://simons.berkeley.edu/talks/choosing-between-dags-can-be-hard},
            author = {},
            keywords = {},
            language = {en},
            title = {Choosing Between Dags Can Be Hard},
            publisher = {The Simons Institute for the Theory of Computing},
            year = {2022},
            month = {feb},
            note = {19617 see, \url{https://scivideos.org/Simons-Institute/19617}}
          }
Richard Guo (University of Cambridge)
Source Repository Simons Institute
Subject

Abstract

Current methods for causal discovery typically report a single directed acyclic graph (DAG). Through an example, I hope to convince you that this might not be the best practice. In fact, depending on how two DAGs intersect and the local geometry at the intersection, the hardness of this problem can vary dramatically.