M³C replaces the hard hyperparameter optimization with a sequence of simpler problems using a majorant for the log-determinant approximated via Monte Carlo, with proven high-probability convergence to a critical point under assumptions.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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math.NA 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Develops sFLSQR and sFLSMR as randomized sketched flexible variants of LSQR/LSMR that recover short recurrences and applies them to large-scale inverse problems with theoretical analysis and experiments.
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A Majorization-Minimization with Monte Carlo Approach for Hyperparameter Estimation
M³C replaces the hard hyperparameter optimization with a sequence of simpler problems using a majorant for the log-determinant approximated via Monte Carlo, with proven high-probability convergence to a critical point under assumptions.
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Randomized Flexible LSQR and LSMR with applications to inverse problems
Develops sFLSQR and sFLSMR as randomized sketched flexible variants of LSQR/LSMR that recover short recurrences and applies them to large-scale inverse problems with theoretical analysis and experiments.