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Questions tagged [sparse-matrices]

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I am working on a bilinear inverse problem arising in multi-channel signal processing. My problem background is to reconstruct a certain one-dimensional information $\mathbf{w} $ of an object from ...
Mavis's user avatar
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In compressed sensing two terms or perhaps fancy word are frequently encountered. One is the dictionary and the other is atom. The dictionary is the matrix and its columns are called "atoms" ...
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$\newcommand{\lrank}{\operatorname{lrank}}$ $\newcommand{\rank}{\operatorname{rank}}$ Given a matrix $A$, we can define its Hamming weight, $w(A)$, as the number of non-zero elements in it. Now, given ...
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Let $M$ be an $n \times n$ matrix with integer entries. Suppose that $M$ is invertible (over the integers) and that $M$ has at most $An$ nonzero entries, each of which is less than $B$ in absolute ...
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Crossposted at SciComp SE I'm very new to finite difference method and I am just introduced to methods of solving differential equation using finite difference method via sparse matrix method. I find ...
Hari Sam's user avatar
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Suppose $\mathbf{A}_{k\times n}$ ($k<n$) is a matrix whose entries are generated i.i.d. from Gaussian distribution and $\mathbf{s}_{n\times 1}$ is a sparse vector with $m$ sparsity (i.e., $\|\...
Math_Y's user avatar
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What is the most efficient way to solve an equation \begin{align*} (A\,E^{-1}\,C) x = b, \qquad A\in \mathbb{R}^{m\times n}, \, E \in \mathbb{R}^{n\times n}, \, C\in \mathbb{R}^{n\times m} \end{align*}...
Bjornson's user avatar
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Let $s$ and $d$ be non-negative integers with $0\leq s<d$ and let $v,u\in \mathbb{R}^d$ be vectors satisfying the sparsity estimate $$ \max\{\|u\|_0,\|v\|_0\}\leq d-s, $$ where, as usual, for any ...
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Let $S_n(\mathbb{R})$ be the set of symmetric matrices of size $n \times n$. Note $\|\Theta\|_{0}$ the number of nonzero elements of a matrix $\Theta$ and $\|\cdot\|_F$ the Froebenius norm. Consider ...
Titouan Vayer's user avatar
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Let $S_{n}^{++}(\mathbb{R})$ be the set of strictly positive definite (PD) matrices on $\mathbb{R}$. We say that a matrix is $k$ sparse if it has at most $k$ nonzero elements. Can we somehow ...
Titouan Vayer's user avatar
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Let $k<n$ be integers. Let $A\in \mathbb{Z}^{k \times n}$ be a sparse matrix, meaning that the number of nonzero entries in every row and every column is at most $O(1)$. Further, assume that ...
Matt Hastings's user avatar
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In MATLAB, you can get a 2d Laplacian via A = delsq(numgrid('S',N)); yielding a matrix $A$ that is $n \times n$ with $n = O(N^2)$, for a square domain discretized ...
Sébastien Loisel's user avatar
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Let $A$ be a sparse matrix over some field. I would like to know about the existence of LU decompositions so that $L,U$ are both sparse. More precisely, let $A$ be an $N$-by-$N$ matrix. Suppose each ...
Matt Hastings's user avatar
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Note: This should be a geometry problem about packing balls. All the necessary probability pre-requisite is given below. Consider a set of sparse vectors: $T_{n,s}:=\{x\in \mathbb{R}^n:\|x\|_0 \le s, \...
Daniel Li's user avatar
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Assume I have a matrix $A \in GF(2)$, i.e., $A_{i,j} \in \{0, 1\}$ and the sum is modulo 2. Is there any known algorithms/methods to sparsify (reduce the number of non-zero entries) $A$ while keeping ...
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Let $n\leq m$ and $0\leq k\leq (n\times m - \min\{n,m\})$ be in $\mathbb{N}$. Let $\mu$ be a probability measure dominated by the Lebesgue measure on $\mathbb{R}$ and generate a random $n\times m$ ...
AB_IM's user avatar
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Show that if $T$ is a symmetric tridiagonal matrix and an eigenvalue $\lambda$ has multiplicity $k$, then at least $k−1$ subdiagonal elements of $T$ are zero. If we consider a submatrix $B$ that has ...
Prashant Govindarajan's user avatar
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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
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Given a large sparse matrix $M$, how to determine the existence of a good preconditioner? In other words, does there exist a sparse matrix $X$ such that $X M$ is close to the identity with respect to ...
Jianqiang Li's user avatar
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Suppose we are given $n \times n$ rational matrix, $A$ with at most $k$ nonzero elements in each row and each column with $k \ll n$. What is the best algorithm to compute its Jordan decomposition? ...
gondolf's user avatar
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I need to find a way to parametrise a matrix that is both sparse (to some degree) and orthogonal, i.e., I am looking for a parametrisation that describes $A \in \mathbb{R}^{n\times m}$ such that $AA^𝑇...
HesterJ's user avatar
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I am playing with a weird dataset of ternary images (+1,0,-1 values only) which happen to be very sparse (avg. > 90%). I would like to determine the most relevant "islands" (or should I call them ...
charlie_bronx_'s user avatar
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I'm trying to understand the left-looking LU factorization algorithm for sparse matrices, by reading T.A. Davis' book, and have trouble in one step (sorry for the specific question) about returning ...
grok's user avatar
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Given a square matrix A (say with complex entries), which is the sparsest matrix which is similar to A? I guess it has to be its Jordan normal form but I am not sure. Remarks: A matrix is sparser ...
Nacho Garcia Marco's user avatar
1 vote
1 answer
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I have the following optimization problem (like the LASSO problem but with maximization instead of minimization): $\mathbf{maximize}_{\boldsymbol{\alpha}} \|\mathbf{x} -\mathbf{A}\boldsymbol{\alpha}\|...
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Let $\mathbb{F}$ is a field. Consider an $n \times n$ matrix $\bf A$ over $\mathbb{F}$. $\bf A$ is called sparse matrix over $\mathbb{F}$ iff the number of non-zero entities of $\bf A$ be at most ...
user0410's user avatar
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2 answers
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Let $X_n=(X_{ij})_{1 \leq i,j \leq n}$ such that : $$ \begin{cases} &X_{ij} = 0 \quad \text{if}\quad \vert i - j \vert > k\\ & X_{ij} \sim P_X \quad \text{otherwise} \end{cases}$$ And ...
Gericault's user avatar
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I have a large matrix $A \in \mathbb{R}^{n \times m}$ and would like to subtract a sparse matrix $B \in \mathbb{R}^{n \times m}$ with less than $c (n+m)$ non-zero entries, where $c > 0$ is a ...
user3095304's user avatar
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374 views

Suppose I have a matrix $H^{+} = (H^T H)^{-1} H^T$ where $H$ is a sparse matrix. Consider the case where only the sparsity pattern i.e. the zero elements of $H^{+}$ matrix is known, then would it be ...
Srinath's user avatar
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8 votes
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I am trying to calculate $$Y = A^{\frac 12} X$$ where $A$ is a very large and sparse positive definite matrix, say, $10^4 \times 10^4$. Matrix $X$ is known and, say, $10^4 \times 100$. Is there any ...
messcode's user avatar
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I have two sparse matrices: $A$ of dimension $m \times k$ and $B$ of dimension $k \times n$. Is there a way to know how many non-zero entries there are in $C = A B$ without computing $A B$? I can ...
Morpheus's user avatar
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I am having undirected graphs with adjacency matrices which have a regular Hankel-like form, e.g., $$A=\begin{pmatrix}0 & 0 & 1 & 0 & 0 & 0 & 0 & 1 & (6\times 0 \text{ ...
pisoir's user avatar
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3 votes
1 answer
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Let $A$ be an $n \times n$ sparse matrix generated via the Erdős-Rényi method. Here, "sparse" means that $\|A\|_F = O(n)$. I am interested in the relationship between the expectation $\mathbb E(\rho(A)...
SC_thesard's user avatar
2 votes
1 answer
320 views

I would like to construct a rectangular matrix which doesn't have a decomposition into a product of a sparse and a small matrices. It is easy to see that a random matrix doesn't have such a ...
Alex Golovnev's user avatar
5 votes
1 answer
1k views

In a large (possibly above $5000\times 5000$) matrix, the problem of finding all the eigenvalues and eigenvectors can be solved using iterative methods (Arnoldi, Lanczos etc.). However, there seems to ...
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6 votes
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344 views

Consider the block matrix given by $$\textbf{D} = \left[ \begin{array}{ccc} \left[ \begin{array}{ccc} D & \ldots & D\\ \vdots & \ddots & \vdots\\ D &...
Integral's user avatar
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Let $A\in\left\{ 0,1\right\} ^{M\times N}$, where each row of $A$ has at most $d$ components equal to $1$, and $d\leq M\ll N\ll Md$. Question: $\forall n\leq N$, what is $m\left(n\right)$, the ...
Daniel Soudry's user avatar
3 votes
2 answers
886 views

Given a dense matrix $A \in \mathbb{R}^{n \times m}$, with $n < m$, I am interested in finding a good approximation by choosing $s$ rows and zeroing the rest. This leads me to the following ...
Paul Irofti's user avatar
2 votes
2 answers
388 views

I have a huge sparse linear system $Ax = b$ where I know that an eigenvalue/eigenvector pair is $1$ and a vector of all $1$'s. Can this knowledge help me in solving the linear system at all? It seems ...
kip622's user avatar
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4 votes
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Let $\boldsymbol{R}$ be the correlation matrix of $X_i,i=1,\dots,p$ with a large $p\gg q=\text{rank}(\boldsymbol{R})$. Is that reasonable to assume that $\boldsymbol{R}$ is both (approximately) sparse ...
John's user avatar
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2 answers
3k views

How to study the decomposition of a square matrix into a product of sparse matrices? There are no restrictions on the number of matrices in the product, but the fewer the better.
unknown's user avatar
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0 answers
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I want to find a $k$ by $r$ biclique hidden in an $M$ by $N$ random bipartite graph where edges are present with probability $p \in [0,1]$. I am specifically interested in $p \ll 1$, and large values ...
HoseinMohimani's user avatar
13 votes
2 answers
5k views

Given an $m$ by $n$ matrix $A$ I'm familiar with the standard method to compute a basis for the null space of $A$ by computing a QR factorization of $A^T$. If $A$ is large and sparse, we can use ...
Alec Jacobson's user avatar
1 vote
0 answers
176 views

I would like to know if there are any special analytic expressions or fast numerical methods to get the spectrum for the transition matrix corresponding to a Markovian binary process (Bernoulli ...
Memming's user avatar
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8 votes
1 answer
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How can I efficiently compute $\mathrm{trace}(A(B^{-1}))$ where $A$ and $B$ are both sparse symmetric PSD $n \times n$ matrices, both with $O(n)$ non-zero entries? If it helps, the pattern of non-...
Jeff's user avatar
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7 votes
1 answer
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I am interested in finding the gap between the two least eigenvalues of $A(t)$, a Hermitian $N\times N$ sparse ‎matrix whose diagonal elements are $a_it+b_i\,(1\leq i\leq N)$, and all off-diagonal non-...
Toughee's user avatar
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3 votes
1 answer
301 views

I'm investigating 3D image deblurring and one of the approaches I'm interested in is applying spatial regularisation. To do this I have generated a matrix $A$ which encodes the 6-connectivity of each ...
user69820's user avatar
1 vote
1 answer
326 views

We have an asymptotic analysis problem for the eigenvalue performance of the following random matrix: $H=\{h_{ij}\}_{N_r\times N_t}$, where each entry $h_{ij}$ is with a probability $p$ to obey the ...
Wenlong Cai's user avatar
6 votes
1 answer
293 views

Given a sparse graph, how can one go about proving that it is Hamiltonian? (Assuming it actually is, of course). There are three main classes of criteria for Hamiltonicity that I am aware of: Dirac-...
Felix Goldberg's user avatar
1 vote
1 answer
702 views

There is a matrix A where each entry is either 0 or 1. Each column has exactly a 1's and each row has at most b 1's. What's the upper bound of abs(|A|)? The condition is stronger than the Hadamard's ...
MMM's user avatar
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