Canonical Schur Tree

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papersSEP 10 04:00 UTC

CAST: New Canonical Schur Tree Method for Approximate Cholesky on Graphs

An arXiv preprint introduces CAST, a data structure for building approximate Cholesky factorizations of graph-structured matrices. It targets settings where many linear systems share a single Laplacian or SDDM coefficient matrix, which arises in tasks like diffusion estimation, ranking, and semi-supervised learning. The method aims to reduce the cost of repeated solves in large-scale graph processing pipelines.

linear-algebra/graph-ml/algorithms