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We initiate a study of the zero-nonzero patterns of n by n alternating sign matrices. We characterize the row (column) sum vectors of these patterns and determine their minimum term rank. In the case of connected alternating sign matrices,…

Combinatorics · Mathematics 2011-04-22 Richard A. Brualdi , Kathleen P. Kiernan , Seth A. Meyer , Michael W. Schroeder

We propose a nonparametric factorization approach for sparsely observed tensors. The sparsity does not mean zero-valued entries are massive or dominated. Rather, it implies the observed entries are very few, and even fewer with the growth…

Machine Learning · Statistics 2021-11-04 Conor Tillinghast , Zheng Wang , Shandian Zhe

We consider the problem of enumerating permutations in the symmetric group on $n$ elements which avoid a given set of consecutive pattern $S$, and in particular computing asymptotics as $n$ tends to infinity. We develop a general method…

Combinatorics · Mathematics 2011-10-13 Richard Ehrenborg , Sergey Kitaev , Peter Perry

Let $v=2ms+t$ be a positive integer, where $t$ divides $2ms$, and let $J$ be the subgroup of order $t$ of the cyclic group $\mathbb{Z}_v$. An integer Heffter array $H_t(m,n;s,k)$ over $\mathbb{Z}_v$ relative to $J$ is an $m\times n$…

Combinatorics · Mathematics 2020-03-20 Fiorenza Morini , Marco Antonio Pellegrini

We derive a sufficient condition for a sparse random matrix with given numbers of non-zero entries in the rows and columns having full row rank. The result covers both matrices over finite fields with independent non-zero entries and…

Combinatorics · Mathematics 2022-02-08 Amin Coja-Oghlan , Pu Gao , Max Hahn-Klimroth , Joon Lee , Noela Müller , Maurice Rolvien

Let $T$ be an $n\times n$ random matrix, such that each diagonal entry $T_{i,i}$ is a continuous random variable, independent from all the other entries of $T$. Then for every $n\times n$ matrix $A$ and every $t\ge0$ $$…

Probability · Mathematics 2013-02-21 Omer Friedland , Ohad Giladi

We give two algorithms for output-sparse matrix multiplication (OSMM), the problem of multiplying two $n \times n$ matrices $A, B$ when their product $AB$ is promised to have at most $O(n^{\delta})$ many non-zero entries for a given value…

Data Structures and Algorithms · Computer Science 2025-08-15 Huck Bennett , Karthik Gajulapalli , Alexander Golovnev , Evelyn Warton

Let $M$ and $M_n,n\ge1$ be nonnegative 2-by-2 matrices such that $\lim_{n\rightarrow\infty}M_n=M.$ It is usually hard to estimate the entries of $M_{k+1}\cdots M_{k+n}$ which are useful in many applications. In this paper, under a mild…

Combinatorics · Mathematics 2022-02-10 Hua-Ming Wang

We introduce a \emph{batch} version of sparse recovery, where the goal is to report a sequence of vectors $A_1',\ldots,A_m' \in \mathbb{R}^n$ that estimate unknown signals $A_1,\ldots,A_m \in \mathbb{R}^n$ using a few linear measurements,…

Data Structures and Algorithms · Computer Science 2018-07-24 Alexandr Andoni , Lior Kamma , Robert Krauthgamer , Eric Price

Let $\{X_i\}$ be a sequence of independent identically distributed random variables with an intermediate regularly varying (IR) right tail $\bar{F}$. Let $(N, C_1, ..., C_N)$ be a nonnegative random vector independent of the $\{X_i\}$ with…

Probability · Mathematics 2012-04-18 Mariana Olvera-Cravioto

We consider the problem of estimating the support of a vector $\beta^* \in \mathbb{R}^{p}$ based on observations contaminated by noise. A significant body of work has studied behavior of $\ell_1$-relaxations when applied to measurement…

Machine Learning · Statistics 2008-05-21 Dapo Omidiran , Martin J. Wainwright

It is known that every complex trace-zero matrix is the sum of four square-zero matrices, but not necessarily of three such matrices. In this note, we prove that for every trace-zero matrix $A$ over an arbitrary field, there is a…

Rings and Algebras · Mathematics 2016-05-18 Clément de Seguins Pazzis

Let $L$ be a lattice of full rank in $n$-dimensional real space. A vector in $L$ is called $i$-sparse if it has no more than $i$ nonzero coordinates. We define the $i$-th successive sparsity level of $L$, $s_i(L)$, to be the minimal $s$ so…

Number Theory · Mathematics 2020-11-30 Lenny Fukshansky , Pavel Guerzhoy , Stefan Kuehnlein

We provide asymptotic formulae for the numbers of bipartite graphs with given degree sequence, and of loopless digraphs with given in- and out-degree sequences, for a wide range of parameters. Our results cover medium range densities and…

Combinatorics · Mathematics 2020-06-30 Anita Liebenau , Nick Wormald

We revisit the probabilistic construction of sparse random matrices where each column has a fixed number of nonzeros whose row indices are drawn uniformly at random. These matrices have a one-to-one correspondence with the adjacency…

Information Theory · Computer Science 2013-07-25 Bubacarr Bah , Jared Tanner

Let R=(r_1, ..., r_m) and C=(c_1, ..., c_n) be positive integer vectors such that r_1 +... + r_m=c_1 +... + c_n. We consider the set Sigma(R, C) of non-negative mxn integer matrices (contingency tables) with row sums R and column sums C as…

Combinatorics · Mathematics 2009-11-25 Alexander Barvinok

Exact evaluation of $<{\rm Tr} S^p>$ is here performed for real symmetric matrices $S$ of arbitrary order $n$, up to some integer $p$, where the matrix entries are independent identically distributed random variables, with an arbitrary…

Statistical Mechanics · Physics 2009-11-10 Giovanni M. Cicuta

We are concerned with the general problem of proving the existence of joint distributions of two discrete random variables $M$ and $N$ subject to infinitely many constraints of the form $\mathbb{P}\left(M=i,N=j\right)=0$. In particular, the…

Probability · Mathematics 2020-03-18 Joseph Squillace

Given a non-negative mxn matrix W=(w_ij) and positive integer vectors R=(r_1, >..., r_m) and C=(c_1, ..., c_n), we consider the total weight T(R, C; W) of mxn non-negative integer matrices (contingency tables) D with the row sums r_i, the…

Combinatorics · Mathematics 2007-05-23 Alexander Barvinok

Sparse support vector machine (SVM) is a popular classification technique that can simultaneously learn a small set of the most interpretable features and identify the support vectors. It has achieved great successes in many real-world…

Machine Learning · Statistics 2019-07-19 Weizhong Zhang , Bin Hong , Wei Liu , Jieping Ye , Deng Cai , Xiaofei He , Jie Wang
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