
Lectures on Randomized Numerical Linear Algebra
This chapter is based on lectures on Randomized Numerical Linear Algebra...
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Tensor ArnoldiTikhonov and GMREStype methods for illposed problems with a tproduct structure
This paper describes solution methods for linear discrete illposed prob...
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Simplification of tensor expressions in computer algebra
Computer algebra is widely used in various fields of mathematics, physic...
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An Attempt to Generate Code for Symmetric Tensor Computations
This document describes an attempt to develop a compilerbased approach ...
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Tensors Come of Age: Why the AI Revolution will help HPC
This article discusses how the automation of tensor algorithms, based on...
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MoA Interpretation of the Iterative Conjugate Gradient Method with Psi Reduction  A Tutorial to teach the Mathematically literate in Linear and Tensor Algebra: Part I
It is often difficult to learn new mathematics semantically and syntacti...
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Chain Rules for Hessian and Higher Derivatives Made Easy by Tensor Calculus
Computing multivariate derivatives of matrixlike expressions in the com...
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Tensors in computations
The notion of a tensor captures three great ideas: equivariance, multilinearity, separability. But trying to be three things at once makes the notion difficult to understand. We will explain tensors in an accessible and elementary way through the lens of linear algebra and numerical linear algebra, elucidated with examples from computational and applied mathematics.
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