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Accelerating Certifiable Estimation with Preconditioned Eigensolvers
[article]
2022
arXiv
pre-print
Convex (specifically semidefinite) relaxation provides a powerful approach to constructing robust machine perception systems, enabling the recovery of certifiably globally optimal solutions of challenging estimation problems in many practical settings. However, solving the large-scale semidefinite relaxations underpinning this approach remains a formidable computational challenge. A dominant cost in many state-of-the-art (Burer-Monteiro factorization-based) certifiable estimation methods is
arXiv:2207.05257v1
fatcat:exjz3ixjevgmrapvwv2ivctqsq