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Showing 1 to 2 of 2 for “"Low-rank tensor decompositions"”.
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Continuous low-rank tensor decompositions, with applications to stochastic optimal control and data assimilation
… framework tightly integrates two emerging areas: tensor decompositions and continuous computation. Tensor decompositions are able to effectively compress and operate with low-rank multidimensional arrays. Continuous computation is a paradigm for computing with functions instead of arrays, and it …
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Multivariate Rational Approximation in Action: From Data-driven Modeling to Nonlinear Eigenvalue Problems
… that improves scalability by incorporating low-rank tensor decompositions into the framework. Second, we generalize p-AAA to arbitrary data sets by deriving novel formulations of least-squares problems that incorporate interpolation constraints on scattered data sets. Several numerical …