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antGLasso: An Efficient Tensor Graphical Lasso Algorithm. (arXiv:2211.02920v1 [stat.ML])
Nov. 8, 2022, 2:11 a.m. | Bailey Andrew, David Westhead, Luisa Cutillo
cs.LG updates on arXiv.org arxiv.org
The class of bigraphical lasso algorithms (and, more broadly,
'tensor'-graphical lasso algorithms) has been used to estimate dependency
structures within matrix and tensor data. However, all current methods to do so
take prohibitively long on modestly sized datasets. We present a novel
tensor-graphical lasso algorithm that analytically estimates the dependency
structure, unlike its iterative predecessors. This provides a speedup of
multiple orders of magnitude, allowing this class of algorithms to be used on
large, real-world datasets.
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