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Related papers: A note on the rank of a sparse random matrix

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Exact matrix completion and low rank matrix estimation problems has been studied in different underlying conditions. In this work we study exact low-rank completion under non-degenerate noise model. Non-degenerate random noise model has…

Machine Learning · Computer Science 2022-04-06 Jafar Jafarov

A fooling-set matrix has nonzero diagonal, but at least one in every pair of diagonally opposite entries is 0. Dietzfelbinger et al. '96 proved that the rank of such a matrix is at least $\sqrt n$. It is known that the bound is tight (up to…

Discrete Mathematics · Computer Science 2016-12-06 Mozhgan Pourmoradnasseri , Dirk Oliver Theis

Define the weight of a matrix to be the number of non-zero entries. One would like to count $m$ by $n$ matrices over a finite field by their weight and rank. This is equivalent to determining the probability distribution of the weight while…

Rings and Algebras · Mathematics 2007-06-12 Theresa Migler , Kent E. Morrison , Mitchell Ogle

We study the problem of low-rank matrix completion for symmetric matrices. The minimum rank of a completion of a generic partially specified symmetric matrix depends only on the location of the specified entries, and not their values, if…

Combinatorics · Mathematics 2020-10-16 Daniel Irving Bernstein , Grigoriy Blekherman , Kisun Lee

Given matrices $X,Y \in R^{n \times K}$ and $S \in R^{K \times K}$ with positive elements, this paper proposes an algorithm fastRG to sample a sparse matrix $A$ with low rank expectation $E(A) = XSY^T$ and independent Poisson elements. This…

Computation · Statistics 2017-03-10 Karl Rohe , Jun Tao , Xintian Han , Norbert Binkiewicz

In this paper, we consider matrix completion from non-uniformly sampled entries including fully observed and partially observed columns. Specifically, we assume that a small number of columns are randomly selected and fully observed, and…

Machine Learning · Computer Science 2018-06-28 Yuanyu Wan , Jinfeng Yi , Lijun Zhang

Random linear systems over the Galois Field modulo 2 have an interest in connection with problems ranging from computational optimization to complex networks. They are often approached using random matrices with Poisson-distributed or…

Disordered Systems and Neural Networks · Physics 2010-11-09 Salvatore Mandrà , Marco Cosentino Lagomarsino , Bruno Bassetti

Let $\mathbb{F}_q$ be the finite field of order $q$, and $\mathcal{A}$ a non-empty proper subset of $\mathbb{F}_q$. Let $\mathbf{M}$ be a random $m \times n$ matrix of rank $r$ over $\mathbb{F}_q$ taken with uniform distribution. It was…

Number Theory · Mathematics 2024-09-17 Chin Hei Chan , Maosheng Xiong

An $n\times n$ matrix $M$ is called a \textit{fooling-set matrix of size $n$} if its diagonal entries are nonzero and $M_{k,\ell} M_{\ell,k} = 0$ for every $k\ne \ell$. Dietzfelbinger, Hromkovi{\v{c}}, and Schnitger (1996) showed that $n…

Combinatorics · Mathematics 2014-01-17 Mirjam Friesen , Aya Hamed , Troy Lee , Dirk Oliver Theis

As a typical dimensionality reduction technique, random projection can be simply implemented with linear projection, while maintaining the pairwise distances of high-dimensional data with high probability. Considering this technique is…

Machine Learning · Computer Science 2014-10-14 Weizhi Lu , Weiyu Li , Kidiyo Kpalma , Joseph Ronsin

For an $n \times n$ matrix $M$ with entries in $\mathbb{Z}_2$ denote by $R(M)$ the minimal rank of all the matrices obtained by changing some numbers on the main diagonal of $M$. We prove that for each non-negative integer $k$ there is a…

Combinatorics · Mathematics 2021-04-22 Eugene Kogan

Let M be a random (alpha n) x n matrix of rank r<<n, and assume that a uniformly random subset E of its entries is observed. We describe an efficient algorithm that reconstructs M from |E| = O(rn) observed entries with relative root mean…

Machine Learning · Computer Science 2009-09-17 Raghunandan H. Keshavan , Andrea Montanari , Sewoong Oh

We consider uniformly random strictly upper-triangular matrices in $\operatorname{Mat}_n(\mathbb{F}_q)$. For such a matrix $A_n$, we show that $n-\operatorname{rank}(A_n) \approx \log_q n$ as $n \to \infty$, and find that the fluctuations…

Probability · Mathematics 2026-01-14 Roger Van Peski

Recently, fundamental conditions on the sampling patterns have been obtained for finite completability of low-rank matrices or tensors given the corresponding ranks. In this paper, we consider the scenario where the rank is not given and we…

Machine Learning · Computer Science 2017-11-03 Morteza Ashraphijuo , Xiaodong Wang , Vaneet Aggarwal

Let $ A_n $ be an $n \times n$ random matrix with i.i.d Bernoulli($p$) entries. For a fixed positive integer $\beta$, suppose $p$ satisfies $$ \frac{ \log(n) }{ n } \le p \le c_\beta $$ where $c_\beta \in ( 0, 1/2 )$ is a…

Probability · Mathematics 2025-05-20 Han Huang

We present an example of a subfield $\mathcal{F}\subset\mathbb{R}$ and a matrix $A$ whose conventional and nonnegative ranks equal five, but the nonnegative rank with respect to $\mathcal{F}$ equals six. In other words, $A$ can be…

Combinatorics · Mathematics 2019-07-25 Yaroslav Shitov

Every m by n matrix A with rank r has exactly r independent rows and r independent columns. The fact has become the most fundamental theorem in linear algebra such that we may favor it in an unconscious way. The sole aim of this paper is to…

History and Overview · Mathematics 2022-07-29 Jun Lu

Consider a random $n\times m$ matrix $A$ over the finite field of order $q$ where every column has precisely $k$ nonzero elements, and let $M[A]$ be the matroid represented by $A$. In the case that q=2, Cooper, Frieze and Pegden (RS\&A…

Combinatorics · Mathematics 2024-01-22 Pu Gao , Peter Nelson

Let $W_{k,n}^{i}(m)$ denote a matrix with rows and columns indexed by the $k$-subsets and $n$-subsets, respectively, of an $m$-element set. The row $S$, column $T$ entry of $W_{k,n}^{i}(m)$ is $1$ if $|S \cap T| = i$, and is $0$ otherwise.…

Combinatorics · Mathematics 2023-05-09 Joshua E. Ducey , Colby J. Sherwood

Given a matrix A \in R^{m x n}, we present a randomized algorithm that sparsifies A by retaining some of its elements by sampling them according to a distribution that depends on both the square and the absolute value of the entries. We…

Information Theory · Computer Science 2014-04-02 Abhisek Kundu , Petros Drineas