Poster
in
Workshop: New Frontiers in Graph Learning
antGLasso: An Efficient Tensor Graphical Lasso Algorithm
Bailey Andrew · David Westhead · Luisa Cutillo
Keywords: [ Gaussian Graphical models ] [ Network inference ] [ bigraphical lasso ]
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 directly 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.