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math.NA2021
Efficient randomized tensor-based algorithms for function approximation and low-rank kernel interactions
Arvind K. Saibaba, Rachel Minster, Misha E. Kilmer
In this paper, we introduce a method for multivariate function approximation using function evaluations, Chebyshev polynomials, and tensor-based compression techniques via the Tuck…
math.NA2020
Efficient Algorithms for Eigensystem Realization using Randomized SVD
Rachel Minster, Arvind K. Saibaba, Jishnudeep Kar +1
Eigensystem Realization Algorithm (ERA) is a data-driven approach for subspace system identification and is widely used in many areas of engineering. However, the computational cos…
math.NA2019
Randomized algorithms for low-rank tensor decompositions in the Tucker format
Rachel Minster, Arvind K. Saibaba, Misha E. Kilmer
Many applications in data science and scientific computing involve large-scale datasets that are expensive to store and compute with, but can be efficiently compressed and stored i…