# Questions tagged [linear-algebra]

Questions on the algorithmic/computational aspects of linear algebra, including the solution of linear systems, least squares problems, eigenproblems, and other such matters.

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### Fast Eigenvalue and SVD Solver for Structured Matrices

I am looking for a fast Eigenvalue and SVD solver for small dense structured matrices (Hankel and Toeplitz). I have searched for efficient implementations in libraries like MKL but I am not able to ...
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### Why are fast Givens rotations mentioned so little in the recent literature?

Fast Givens rotations seem like a nice upgrade from standard Givens rotations. They take fewer multiplications to apply and avoid the calculation of a square root. They are, however, given very little ...
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### Decomposing a banded matrix

Suppose we have a linear algebra problem with a banded matrix A which has nonzero entries on the main diagonal, two nearest sub-diagonals, and two other sub-diagonals (such band structure often arises ...
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### Check if LinearOperator is symmetric

I have a scipy.sparse.linalg.LinearOperator object. I'd like to check if its associated matrix is symmetric without actually instantiating the matrix in the most ...
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### Inverse problem with uncertain forward operator

Suppose I want to solve a linear inverse problem. In this example we take a convolution with the kernel: $$\frac{1}{(y^2+z^2)^{3/2}}$$ We only take a fixed $z$ for the computation and convolve with ...
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### Explanation of subspace strategy regarding CG described in Golub's book

I was wondering about the last paragraph in Matrix Computations (4th edition) by Golub, Chapter 11 (11.3.3), specifically his explanation of subspace strategy for Conjugate Gradient. Note that in ...
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### Trying to understand splitting-based iterative method for 2D Laplace problem

I am trying to understand the theory behind a splitting based iterative method which uses the incomplete Cholesky factorization. Before giving the specific details, let me first give the problem ...
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### Optimize linear equation using inner products and subject to L1 norm

I have a linear system of the form $A x = b$ where $A$ and $b$ are known, $A$ is "square", and $\lvert b \rvert_1 = \lvert x \rvert_1 = 1$. Unfortunately, I am working in a framework that ...
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### Fastest matrix library for Android (with GPU is possible)

I was working on an Android app that requires some linear algebra with matrices. The matrices will be somewhat medium-sized as they are not too small or too big. I was originally using jBlas because ...
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### What algorithm do BLAS and ATLAS use for matrix multiplication?

I have searched and what I understood was that they use the naive one with several memory and cache optimizations. However, I wanted to know whether they are using the Strassen or the Coppersmith-...
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### Block matrix and DSYRK

I want to compute the matrix $$A = \sum_{i=1}^N v_i v_i^T$$ where each $v_i$ is a given vector of length $2500$, so that $A$ is $2500 \times 2500$, and my $N$ is about 2 million. Rather than call ...
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### How to stochastically estimate the trace of a matrix?

Specifically, the diagonal elements (can possibly both positive and negative) of the matrix can be computed efficiently but the total number is large ($\mathcal O(10^{18})$). My first thought about ...
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### Fixing a near singular covariance matrix

Given a near singular covariance matrix, the standard method of 'fixing' it seems to be to add a small damping coefficient $c>0$ to the diagonal, which serves to bump all the eigenvalues up by this ...
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### When would one choose un-pivoted $LDL^T$ instead of $LL^T$ for a Positive Definite Matrix?

Background I am decomposing (and then operating on) a symmetric positive definite matrix (a covariance matrix) as part of a larger system. Dimensions range from O(10) to O(300). The covariance ...
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### Approximating eigenvalues of DPR1 matrix with special properties

In my application, I have a sum of diagonal $A$ and rank-1 $B$ $$T=\underbrace{\text{diag}(1-2\alpha h+2\alpha^2 h^2)}_A + \underbrace{\alpha^2 hh^T}_B$$ Where $h$ is a vector $\in \mathbb{R}^d$ with ...
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