A computational approach to maximum likelihood thresholds for colored Gaussian graphical models
This story is from 2026-09-03. It is preserved in the archive; the latest stories are on the live feed.
arXiv:2609.02382v1 Announce Type: new Abstract: Gaussian graphical models (GGMs) are essential tools for interpretable structure learning. However, in high-dimensional, small-sample regimes, the available data is often insufficient for the maximum likelihood estimator to exist. Colored Gaussian gra…
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- 2026-09-03 04:00 · arXiv stat.ML
A computational approach to maximum likelihood thresholds for colored Gaussian graphical models
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