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We study the Matrix Multiplication Verification Problem (MMV) where the goal is, given three $n \times n$ matrices $A$, $B$, and $C$ as input, to decide whether $AB = C$. A classic randomized algorithm by Freivalds (MFCS, 1979) solves MMV…

Data Structures and Algorithms · Computer Science 2024-07-23 Huck Bennett , Karthik Gajulapalli , Alexander Golovnev , Evelyn Warton

Nonnegative matrix factorization (NMF) is a powerful tool for data mining. However, the emergence of `big data' has severely challenged our ability to compute this fundamental decomposition using deterministic algorithms. This paper…

Machine Learning · Statistics 2018-05-02 N. Benjamin Erichson , Ariana Mendible , Sophie Wihlborn , J. Nathan Kutz

Let $N(L)$ be the number of eigenvalues, in an interval of length $L$, of a matrix chosen at random from the Gaussian Orthogonal, Unitary or Symplectic ensembles of ${\cal N}$ by ${\cal N}$ matrices, in the limit ${\cal…

chao-dyn · Physics 2009-10-22 Ovidiu Costin , Joel L. Lebowitz

A random matrix is likely to be well conditioned, and motivated by this well known property we employ random matrix multipliers to advance some fundamental matrix computations. This includes numerical stabilization of Gaussian elimination…

Numerical Analysis · Mathematics 2012-12-27 Victor Y. Pan , Guoliang Qian

Min-plus product of two $n\times n$ matrices is a fundamental problem in algorithm research. It is known to be equivalent to APSP, and in general it has no truly subcubic algorithms. In this paper, we focus on the min-plus product on a…

Data Structures and Algorithms · Computer Science 2022-02-03 Shucheng Chi , Ran Duan , Tianle Xie

Learning a Gaussian mixture model (GMM) is a fundamental problem in machine learning, learning theory, and statistics. One notion of learning a GMM is proper learning: here, the goal is to find a mixture of $k$ Gaussians $\mathcal{M}$ that…

Data Structures and Algorithms · Computer Science 2015-06-04 Jerry Li , Ludwig Schmidt

Given a multiset $S$ of $n$ positive integers and a target integer $t$, the Subset Sum problem asks to determine whether there exists a subset of $S$ that sums up to $t$. The current best deterministic algorithm, by Koiliaris and Xu…

Data Structures and Algorithms · Computer Science 2020-01-03 Ce Jin , Hongxun Wu

For various $2\leq n,m \leq 6$, we propose some new algorithms for multiplying an $n\times m$ matrix with an $m \times 6$ matrix over a possibly noncommutative coefficient ring.

Symbolic Computation · Computer Science 2023-06-02 Manuel Kauers , Jakob Moosbauer

We construct a continuous-time non-commutative random walk on $U(\mathfrak{gl}_N)$ with dilation maps $U(\mathfrak{gl}_N)\rightarrow L^2(U(N))^{\otimes\infty}$. This is an analog of a continuous-time non-commutative random walk on the group…

Representation Theory · Mathematics 2016-12-20 Jeffrey Kuan

This paper deals with circulant matrices. It is shown that a circulant matrix can be multiplied by a vector in time O(n log(n)) in a ring with roots of unity without making use of an FFT algorithm. With our algorithm we achieve a speedup of…

Data Structures and Algorithms · Computer Science 2021-03-05 Andreas Rosowski

For vertices $u$ and $v$ of an $n$-vertex graph $G$, a $uv$-trail of $G$ is an induced $uv$-path of $G$ that is not a shortest $uv$-path of $G$. Berger, Seymour, and Spirkl [Discrete Mathematics 2021] gave the previously only known…

Data Structures and Algorithms · Computer Science 2024-10-02 Yung-Chung Chiu , Hsueh-I Lu

Given a graph $G$ with $n$ nodes and two nodes $u,v\in G$, the {\em CoSimRank} value $s(u,v)$ quantifies the similarity between $u$ and $v$ based on graph topology. Compared to SimRank, CoSimRank is shown to be more accurate and effective…

Social and Information Networks · Computer Science 2024-02-21 Renchi Yang , Xiaokui Xiao

We provide an algorithm for properly learning mixtures of two single-dimensional Gaussians without any separability assumptions. Given $\tilde{O}(1/\varepsilon^2)$ samples from an unknown mixture, our algorithm outputs a mixture that is…

Data Structures and Algorithms · Computer Science 2014-05-20 Constantinos Daskalakis , Gautam Kamath

We show that $n$-bit integers can be factorized by independently running a quantum circuit with $\tilde{O}(n^{3/2})$ gates for $\sqrt{n}+4$ times, and then using polynomial-time classical post-processing. The correctness of the algorithm…

Quantum Physics · Physics 2024-01-09 Oded Regev

Let $X$ be a symmetric, isotropic random vector in $\mathbb{R}^m$ and let $X_1...,X_n$ be independent copies of $X$. We show that under mild assumptions on $\|X\|_2$ (a suitable thin-shell bound) and on the tail-decay of the marginals…

Functional Analysis · Mathematics 2022-07-13 Daniel Bartl , Shahar Mendelson

Let {\alpha} be the maximal value such that the product of an n x n^{\alpha} matrix by an n^{\alpha} x n matrix can be computed with n^{2+o(1)} arithmetic operations. In this paper we show that \alpha>0.30298, which improves the previous…

Data Structures and Algorithms · Computer Science 2021-10-05 François Le Gall

Motivated by a sampling problem basic to computational statistical inference, we develop a nearly optimal algorithm for a fundamental problem in spectral graph theory and numerical analysis. Given an $n\times n$ SDDM matrix ${\bf…

Data Structures and Algorithms · Computer Science 2014-10-21 Dehua Cheng , Yu Cheng , Yan Liu , Richard Peng , Shang-Hua Teng

We present a randomized algorithm, which, given positive integers n and t and a real number 0< epsilon <1, computes the number Sigma(n, t) of n x n non-negative integer matrices (magic squares) with the row and column sums equal to t within…

Combinatorics · Mathematics 2007-05-23 Alexander Barvinok , Alex Samorodnitsky , Alexander Yong

The exact nonnegative matrix factorization (exact NMF) problem is the following: given an $m$-by-$n$ nonnegative matrix $X$ and a factorization rank $r$, find, if possible, an $m$-by-$r$ nonnegative matrix $W$ and an $r$-by-$n$ nonnegative…

Optimization and Control · Mathematics 2016-10-07 Arnaud Vandaele , Nicolas Gillis , François Glineur , Daniel Tuyttens

In this paper we provide an $\tilde{O}(nd+d^{3})$ time randomized algorithm for solving linear programs with $d$ variables and $n$ constraints with high probability. To obtain this result we provide a robust, primal-dual…

Data Structures and Algorithms · Computer Science 2021-08-24 Jan van den Brand , Yin Tat Lee , Aaron Sidford , Zhao Song