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Information Theoretically Optimal Sample Complexity of Learning Dynamical Directed Acyclic Graphs
April 2, 2024, 7:45 p.m. | Mishfad Shaikh Veedu, Deepjyoti Deka, Murti V. Salapaka
cs.LG updates on arXiv.org arxiv.org
Abstract: In this article, the optimal sample complexity of learning the underlying interactions or dependencies of a Linear Dynamical System (LDS) over a Directed Acyclic Graph (DAG) is studied. We call such a DAG underlying an LDS as dynamical DAG (DDAG). In particular, we consider a DDAG where the nodal dynamics are driven by unobserved exogenous noise sources that are wide-sense stationary (WSS) in time but are mutually uncorrelated, and have the same {power spectral density …
abstract article arxiv call complexity cs.lg cs.sy dag dependencies eess.sy graph graphs information interactions linear math.oc sample stat.ml type
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