Exact Estimation of Multiple Directed Acyclic Graphs

Publisher:
Springer Verlag
Publication Type:
Journal Article
Citation:
Statistics and Computing, 2016, 26 (4), pp. 797 - 811
Issue Date:
2016-07
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This paper considers structure learning for multiple related directed acyclic graph (DAG) models. Building on recent developments in exact estimation of DAGs using integer linear programming (ILP), we present an ILP approach for joint estimation over multiple DAGs. Unlike previous work, we do not require that the vertices in each DAG share a common ordering. Furthermore, we allow for (potentially unknown) dependency structure between the DAGs. Results are presented on both simulated data and fMRI data obtained from multiple subjects.
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