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News/Mixing-Free and Signal-Optimal Learning of Gaussian Graphical Models from Glauber Dynamics
arxiv
PublishedJuly 22, 2026 at 4:00 AM
—neutral

Mixing-Free and Signal-Optimal Learning of Gaussian Graphical Models from Glauber Dynamics

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Publisher summary· verbatim

arXiv:2607.18559v1 Announce Type: cross Abstract: Gaussian graphical model selection is usually studied under independent sampling, but in many applications the data arise as a single trajectory of a dependent stochastic process. We study exact recovery of the graph from one trajectory of random-sca

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arxiv
Read original ↗All from arxiv →
Tags
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#machine-learning#graphical-models#stochastic-process#algorithms

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