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38 votes
10 answers
18k views

Fast matrix multiplication

Suppose we have two $n$ by $n$ matrices over particular ring. We want to multiply them as fast as possible. According to wikipedia there is an algorithm of Coppersmith and Winograd that can do it in $...
ilyaraz's user avatar
  • 1,791
34 votes
3 answers
6k views

Why is uncomputability of the spectral decomposition not a problem?

Below, we compute with exact real numbers using a realistic / conservative model of computability like Type Two Effectivity. Assume that there is an algorithm that, given a symmetric real matrix $M$, ...
wlad's user avatar
  • 4,943
34 votes
3 answers
3k views

Quickly determining if a matrix has any PSD completion

Given $m$ entries of an $n \times n$ matrix, is it possible to determine in $O(m n)$ time whether there is any positive semidefinite completion? Slightly more precisely: for simplicity let's assume ...
Paul Christiano's user avatar
21 votes
3 answers
51k views

What is the time complexity of truncated SVD?

Full SVD, on an $m \times n$ matrix $A$, [U,S,V] = svd(A), would cost $O(m^2n + mn^2 + n^3)$ time. But what is the time complexity if we only need the $k$ largest ...
user40484's user avatar
  • 327
21 votes
2 answers
18k views

Complexity of linear solvers vs matrix inversion

Solving linear equations can be reduced to a matrix-inversion problem, implying that the time complexity of the former problem is not greater than the time complexity of the latter. Conversely, given ...
Alm's user avatar
  • 1,207
15 votes
9 answers
9k views

Exponential of large matrices

I want to make a diffusion kernel, which involves $e^{\beta A}$, where A is a large matrix (25k by 25k). It is an adjacency matrix, so it's symmetric and very sparse. Does anyone have a ...
Xodarap's user avatar
  • 151
15 votes
2 answers
7k views

Efficient rank-two updates of an eigenvalue decomposition (or more generally SVD)

Let $A$ be a symmetric matrix with eigenvalue decomposition $UDU^T$. Golub, et al.1 and Bunch, et al.2 have shown that given such an $A$, the eigenvalue decomposition of $A+\rho xx^t$ may be computed ...
Lepidopterist's user avatar
12 votes
2 answers
9k views

What is the time complexity of the matrix exponential?

While trying to compute the Matrix Exponential of an $n \times n$ array I decided to take advantage of a Python function called scipy.linalg.expm(). According to ...
FaCoffee's user avatar
  • 241
11 votes
2 answers
821 views

Determinant and eigenvalues of a specific matrix

This came up in a conversation with an engineer friend of mine. Let $c>0$ be a constant. Let $A_{ij}$ be an $n$ by $n$ matrix with entries $$ A_{ij} = e^{-c(i-j)^2}. $$ Is there a name for this ...
Lev Borisov's user avatar
  • 5,186
11 votes
1 answer
896 views

Decide if a matrix is transposable

A matrix $M$ is called transposable if it can be transformed into its transpose $M^t$ via row and column permutations. Is there an efficient a way/algorithm to decide if a given matrix is ...
Stefan Blausberg's user avatar
11 votes
3 answers
9k views

Eigenvectors of a symmetric positive definite Toeplitz matrix

I wish to efficiently compute the eigenvectors of an n x n symmetric positive definite Toeplitz matrix K. A full eigendecomposition would be even better. Although I assumed this would be a well ...
Sodalite's user avatar
  • 111
11 votes
0 answers
764 views

Fast computation of matrix product $AXA^T$ with fixed $A$?

Suppose we have two $n$-by-$n$ matrices $X$ and $A$, where $A$ is known and $X$ may change in different invocations, and we want to compute $AXA^T$. Is there an algorithm that beats the naive one of ...
hao chen's user avatar
9 votes
1 answer
1k views

Computation time of Smith normal form in Maple

I am using Maple to compute the Smith normal form (SNF) of a $120 \times 120$ matrix and it seems that I will never get an answer back. I have checked my code for small cases and I believe that it is ...
Yibo Gao's user avatar
  • 356
9 votes
1 answer
472 views

$M = AA^t$ where $A$ has unit norm columns

Let $M \in \mathbb{R}^{k\times k}$ positive definite with $\operatorname{tr} M = m$, where $m$ is an integer such that $m \geq k$. I have found a way (using this answer) to decompose $M = AA^t$ with $...
Yair Daon's user avatar
  • 185
8 votes
1 answer
2k views

Finding Toeplitz matrix nearest to a given matrix

For an arbitrary $N\times N$ Hermitian matrix $A$, I want to derive a Toeplitz matrix from $A$ such that the eigenvectors of both matrices have minimal change. Specifically I want find the Toeplitz ...
Creator's user avatar
  • 495
8 votes
1 answer
1k views

Norm of inverse confluent Vandermonde matrix

Let $\{x_1,\dots,x_n\}$ be pairwise distinct complex numbers and $l_1+l_2+\dots+l_n=N$. The $N\times N$ confluent Vandermonde matrix is defined as $$V= \begin{bmatrix} v_{1,0}&v_{2,0}&\dots&...
dima's user avatar
  • 959
7 votes
3 answers
1k views

Checking positive semi-definiteness of integer matrix

Key Problem : Is there any theorem about eigenvalues or positive semi-definiteness of small size matrices with small integer elements? I have to check positive semi-definiteness of many symmetric ...
SIM2's user avatar
  • 73
7 votes
1 answer
305 views

Efficiently solve the Sylvester equation $AX+XA = C$ where $X$ is skew-symmetric

Is there a way (more efficient than the standard vectorization) to solve the following Sylvester equation in the skew-symmetric matrix $X$ $$AX+XA = C$$ where the matrix $A$ is symmetric positive ...
Gabi's user avatar
  • 173
7 votes
2 answers
3k views

Factorizing a block symmetric matrix

Let $X,Y\in\mathbb{R}^{n\times n}$ be symmetric matrices. You may assume that $X$ is positive semidefinite and $Y$ negative semidefinite, if needed, but not that they are invertible. I would like to ...
Federico Poloni's user avatar
7 votes
2 answers
244 views

Finding $\theta$ such that at least one eigenvalue of $A(\theta)$ is real

Is there a known method to find a set of $\theta$ such that at least one eigenvalue of $A(\theta)$ is purely real? Assume $A(\theta)$ is a real square matrix whose elements are linear functions of a ...
CWC's user avatar
  • 433
6 votes
1 answer
830 views

Dominant eigenvector of a real symmetric tridiagonal matrix

What is the most efficient way to calculate the dominant eigenvector of a real symmetric tridiagonal matrix? What's the corresponding time complexity bound? Could someone give me a reference for ...
tom's user avatar
  • 61
6 votes
1 answer
305 views

For a set of matrices $S$, find $X$ such that the elements of $SX$ commute

Let $S := \{A_0, A_1, \dots, A_d\}$, where $A_k \in \mathbb{C}^{n \times n}$, be a set of (generally noncommuting) matrices. I am interested in finding a nonsingular $X \in \mathbb{C}^{n \times n}$ ...
Vedran Šego's user avatar
6 votes
0 answers
141 views

Algorithm to check a conjectural value for the rank of a large matrix

Feel free to suggest a different title, I'm not sure how to phrase this. I'm in the following somewhat specific situation: I'm checking a conjecture which at the end of the day boils down to the ...
Adrien's user avatar
  • 8,524
5 votes
1 answer
401 views

Best orthogonal approximation of rank 1 matrix

Let $X=\lambda_0u_0v_0^T\in\mathbb{R}^{n\times n}$ be a rank 1 matrix where $\lambda_0\in\mathbb{R}$, $u_0,v_0$ are of unit Euclidean norm. What is the solution of the following problem? $$\hat{X}=\...
neverevernever's user avatar
5 votes
3 answers
693 views

Norm of triangular truncation operator on rank deficient matrices

Let $T_{n\times n}$ be a triangular truncation matrix, i.e. $$T_{i,j}=\begin{cases}1 & i\ge j\\ 0 & i<j \end{cases}$$ It is known that for arbitrary $A_{n\times n}$ $$\|T\circ A\|\le\frac{\...
sb945's user avatar
  • 153
5 votes
1 answer
260 views

Numerical minimization spectral norm under diagonal similarity

This question is a follow up. Let $A$ be a real square matrix of size $n \times n$. How to determine the minimum spectral norm under diagonal similarity, i.e., $$ s(A) = \inf_{D} \lVert D^{-1} A D\...
Jiro's user avatar
  • 909
5 votes
1 answer
251 views

Smooth, non-analytic functions of non-normal matrices

My apologies if this isn't a well-enough-posed question, I think I'm partly unsure of what exact question to even ask. There are many different ways in which we can take a function of a matrix. We ...
Yonah Borns-Weil's user avatar
5 votes
0 answers
392 views

Preconditioner for finding the smallest eigenpairs of a large, but structured, matrix

I'm trying to find the eigenvector corresponding to the second smallest eigenvalue of a large $(4,000,000 \times 4,000,000)$ matrix $L$. $L$ is a graph Laplacian, with the following structure: $L = D -...
Jeff's user avatar
  • 500
5 votes
0 answers
112 views

Inverses of the sums of all possible subsets of a set of symmetric and positive definite matrices

I have a set of $c$ matrices $A_1 ... A_c$ which are all symmetric and positive definite. I would like to calculate the inverses of all the possible sums, i.e. $(A_1+A_2)^{-1},(A_1+A_3)^{-1},(A_2+A_3)...
Tzonathan's user avatar
4 votes
3 answers
3k views

Is this inequality involving the Frobenius norm right?

Let $A$ be a generic (or varying) square, real $ n \times n$ matrix. Let $G$ be a fixed $n \times k$ matrix, $k < n.$ Denote by $||.||_F$ the Frobenius norm. Is it true that $||AG||_F \geq c(G) ||...
Learning math's user avatar
4 votes
2 answers
948 views

Numerically solving for pseudo inverse of non-squared Vandermonde matrix

I have a linear system to solve, set up as: $\bf{Ax}=\bf{b}$ with a non-squared matrix A, $ \bf{A}= \begin{bmatrix} 1 & A_{1} & A_{1}^2 & \cdots & A_{1}^n \\ 1 & A_{2} & A_{...
nimamura's user avatar
4 votes
1 answer
292 views

Is there a fast algorithm to test positivity of all principal minors of non-symmetric matrix?

I have a matrix $A \in \mathbb{R}^{n \times n}$ with positive eigenvalues. In the symmetric case, Sylvester's criterion implies that all the principal minors are positive. In the non-symmetric case, ...
Gabriel Mitchell's user avatar
4 votes
1 answer
749 views

submatrix of a given size with maximum frobenius norm

Let $I\subset \{1,2,\ldots,n\}$, and let $|I|$ denote its cardinality. Now given a Hermitian matrix $\mathbf{A}\in\mathbf{C}^{n\times n}$. I am interested in finding the subset $I$ that maximizes the ...
mohi's user avatar
  • 859
4 votes
0 answers
149 views

Zero diagonal nonsymmetric block checkerboard matrix: orbits and numerical ranges

Let $A \in \mathbb{R}^{m \times m}$ be a nonsymmetric zero diagonal matrix with a zero/non-zero pattern which is symmetric and persymmetric (i.e. symmetric in the northeast-to-southwest diagonal). If ...
Astor's user avatar
  • 323
4 votes
0 answers
2k views

What is the time complexity of the largest singular value and its vectors?

Full zero-error SVD on an $m \times n$ matrix $A$ would cost $O(\min(m^2n,mn^2))$. What is the time complexity if we need only the largest singular value and its corresponding vectors? I think it is $...
B. Arsic's user avatar
  • 123
4 votes
0 answers
578 views

Determining whether a Schur complement is invertible

Consider the symmetric matrix $$M = \begin{bmatrix} A & B \\ B^T & -C \end{bmatrix}$$ where $A \in \cal{R}^{n \times n}$ and $C \in \cal{R}^{m\times m}$ are symmetric, ...
berkin's user avatar
  • 41
3 votes
2 answers
2k views

Matrix equation with Hadamard product and its own inverse involved

I know there is an almost exactly same question here but I have further specifications. So my problem is as follows: $$ \Omega^{-1}=\dfrac{1}{n}\left(\Omega\odot \mathbf{W}+\mathbf{X}'\mathbf{X}+\...
Daeyoung's user avatar
  • 133
3 votes
2 answers
245 views

A problem about determinant and matrix

Suppose $a_{0},a_{1},a_{2}\in\mathbb{Q}$, such that the following determinant is zero, i.e. $ \left |\begin{array}{cccc}\\ a_{0} &a_{1} & a_{2} \\ \\ a_{2} &a_{0}+a_{1} & a_{1}+a_{...
HilbertHunnterrrD's user avatar
3 votes
1 answer
143 views

A problem about matrix inverse and regularization methods

I'm researching the problem of solving the equation $A\mathbf{x}=\mathbf{b}$ with ill-conditioned matrices. We know that if we solve it directly, like $\mathbf{x}=\mathrm{inv}(A)\ast\mathbf{b}$, then ...
bing's user avatar
  • 33
3 votes
2 answers
2k views

Iterative methods for linear system with non-diagonally dominant matrix

I have a linear system \begin{align*} \left[\begin{array}{cccc} 1 & 2 & 1 & -1 \\ 3 & 2 & 4 & 4 \\ 4 & 4 & 3 & 4 \\ 2 & 0 &...
mohd's user avatar
  • 65
3 votes
0 answers
147 views

Convolution integral and its matrix representation

My background is chemistry and I was exploring some one dimensional deconvolution problems i.e., resolution of two or more overlapping peaks. A lot of excellent work was done in the 1970-80s. However, ...
ACR's user avatar
  • 879
3 votes
0 answers
243 views

An inequality concerning the solution of a Lyapunov equation

Let $A$ be an Hurwitz stable matrix (i.e. the real part of the eigenvalues of $A$ lie in the left-half plane) and $Q$ be a positive semidefinite matrix ($Q\ge 0$, for short). Let $P>0$ be the ...
Ludwig's user avatar
  • 2,712
3 votes
0 answers
220 views

Could SVD be used to optimize the partial inner-products?

Suppose a set $N$ of $n$ distinct points in $m-$dimensional space is given in $X\in\mathbb{R}^{n\times m}$. Also, suppose a subset $L\subset N$, $|L|=l<m<n$, with $m-$dimensional coordinates in ...
usero's user avatar
  • 131
2 votes
2 answers
606 views

Solving a matrix equation $X=c \cdot AXA' +I$ with a diagonal corrections

I am now struggling to solve the matrix $X \in R^{n \times n}$ in the following equation: $X=c \cdot AXA' - diag(c \cdot AXA')+ I$, where (1) $A \in R^{n \times n}$ is a given matrix whose element ...
John Smith's user avatar
2 votes
1 answer
1k views

Updating $LU$ decomposition after adding a sparse matrix

How many elements of $LU$ decomposition of a symmetric matrix change after adding a sparse symmetric matrix? Is it more efficient to recompute $LU$ decomposition after adding a sparse matrix comparing ...
Michael's user avatar
  • 2,205
2 votes
1 answer
164 views

The "best way" to order unknowns in linear systems

Start with a linear system of the form \begin{equation*} Ax + Bt + C = 0, \end{equation*} where $x = (x_1, \dots, x_n) \in \mathbb R^n$ is the vector of unknowns, $t \in \mathbb R^m$ is a vector of ...
avril_14th's user avatar
2 votes
0 answers
52 views

Large-scale projected minimum-eigenvalue computations

I am interested in efficient numerical procedures for solving large-scale instances of the following projected minimum-eigenvalue problem: $$\mu := \min_{v \in \mbox{ker}(A)} \frac{v^T H v}{\lVert v \...
David Rosen's user avatar
2 votes
0 answers
1k views

Condition number of the product of two matrices

Consider two matrices $A$ and $B$ that are non-square in general and may not be full rank. Assuming their shapes are such that the product $A\cdot B$ is well-defined, what is the relationship between ...
glwhart's user avatar
  • 171
2 votes
0 answers
131 views

SVD when only off-diagonal terms are known

I have a real matrix $A \in \mathbb{R}^{n\times n}$ such that: $A$ is symmetric All the off-diagonal terms are known and positive Has rank $k<n$ Unfortunately I don't know the values of the ...
Ulderique Demoitre's user avatar
1 vote
1 answer
326 views

For the purposes of solving linear equations, is there a fast decomposition that works for all Hermitian matrices?

Let $A$ be an arbitrary Hermitian matrix. Is there a way of efficiently factorizing $A$ for the purposes of solving $Ax = b$ for arbitrary $b$? There are two decompositions I'm aware of that nearly ...
wlad's user avatar
  • 4,943