Develops structured random sketching for Hilbert-Schmidt operators to enable low-dimensional approximation and preconditioner construction with high-probability embedding and error bounds.
Robust model reductio n by L1-norm minimization and approximation via dictionaries: application to nonlinear hyperbolic pro blems
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Random sketching of operators with application to learning preconditioners
Develops structured random sketching for Hilbert-Schmidt operators to enable low-dimensional approximation and preconditioner construction with high-probability embedding and error bounds.