Structured Canonical Forms For Products Of (Skew-) Symmetric Matrices And The Matrix Equation XAX = B

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RANDOMIZED JOINT DIAGONALIZATION OF SYMMETRIC

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Given a family of nearly commuting symmetric matrices, we consider the task of computing an orthogonal matrix that nearly diagonalizes every matrix in the family. In this paper, we propose and analyze randomized joint diagonalization (RJD) for performing t ...

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Biobased surfactant

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The present invention relates to a compound of the general formula (I), and (II)wherein one of R11 and R12 is hydrogen and the other is -CH2-R70, and one of R13 and R14 is hydrogen and the other is -CH2-R71, or wherein one of R11 and R12 is hydrogen and th ...

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Spectral Estimators for High-Dimensional Matrix Inference

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A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

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Tangent functional connectomes uncover more unique phenotypic traits

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Functional connectomes (FCs) containing pairwise estimations of functional couplings between pairs of brain regions are commonly represented by correlation matrices. As symmetric positive definite matrices, FCs can be transformed via tangent space projecti ...

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Optimal denoising of rotationally invariant rectangular matrices

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In this manuscript we consider denoising of large rectangular matrices: given a noisy observation of a signal matrix, what is the best way of recovering the signal matrix itself? For Gaussian noise and rotationally-invariant signal priors, we completely ch ...

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Fast deterministic and randomized algorithms for low-rank approximation, matrix functions, and trace estimation

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In this thesis we propose and analyze algorithms for some numerical linear algebra tasks: finding low-rank approximations of matrices, computing matrix functions, and estimating the trace of matrices. In the first part, we consider algorithms for building ...

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Unified Green's function approach for spectral and thermodynamic properties from algorithmic inversion of dynamical potentials

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Dynamical potentials appear in many advanced electronic-structure methods, including self-energies from many-body perturbation theory, dynamical mean-field theory, electronic-transport formulations, and many embedding approaches. Here, we propose a novel t ...

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Robust Differentiable SVD

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Eigendecomposition of symmetric matrices is at the heart of many computer vision algorithms. However, the derivatives of the eigenvectors tend to be numerically unstable, whether using the SVD to compute them analytically or using the Power Iteration (PI) ...

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Unified Green's function approach for spectral and thermodynamic properties from algorithmic inversion of dynamical potentials

Nicola Marzari, Tommaso Chiarotti, Andrea Ferretti

AMER PHYSICAL SOC2022