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We consider the problem of finding a sparse multiple of a polynomial. Given f in F[x] of degree d over a field F, and a desired sparsity t, our goal is to determine if there exists a multiple h in F[x] of f such that h has at most t…

Symbolic Computation · Computer Science 2011-01-04 Mark Giesbrecht , Daniel S. Roche , Hrushikesh Tilak

Suppose we are given a matrix that is formed by adding an unknown sparse matrix to an unknown low-rank matrix. Our goal is to decompose the given matrix into its sparse and low-rank components. Such a problem arises in a number of…

Optimization and Control · Mathematics 2011-08-09 Venkat Chandrasekaran , Sujay Sanghavi , Pablo A. Parrilo , Alan S. Willsky

We study resonances of nonlinear systems of differential equations, including but not limited to the equations of motion of a particle moving in a potential. We use the calculus of variations to determine the minimal additive forcing…

Chaotic Dynamics · Physics 2009-08-27 Vadas Gintautas , Alfred W. Hubler

In our recent work \cite{StojnicCSetam09,StojnicUpper10} we considered solving under-determined systems of linear equations with sparse solutions. In a large dimensional and statistical context we proved results related to performance of a…

Information Theory · Computer Science 2013-04-02 Mihailo Stojnic

In this paper, we describe a new algorithm that approximates the extreme eigenvalue/eigenvector pairs of a symmetric matrix. The proposed algorithm can be viewed as an extension of the Jacobi eigenvalue method for symmetric matrices…

Numerical Analysis · Mathematics 2025-09-16 Cristian Rusu

Sparsity plays a central role in recent developments in signal processing, linear algebra, statistics, optimization, and other fields. In these developments, sparsity is promoted through the addition of an $L^1$ norm (or related quantity)…

Analysis of PDEs · Mathematics 2014-08-04 Russel E. Caflisch , Stanley J. Osher , Hayden Schaeffer , Giang Tran

A formulation is given for the spectral transformation of the generalized eigenvalue problem through the decomposition of the second-order differential operators. This allows us to construct some Laurent biorthogonal polynomial systems with…

Classical Analysis and ODEs · Mathematics 2022-12-26 Yu Luo , Satoshi Tsujimoto

Sparse tensors are prevalent in many data-intensive applications, yet existing differentiable programming frameworks are tailored towards dense tensors. This presents a significant challenge for efficiently computing gradients through…

Programming Languages · Computer Science 2023-03-14 Amir Shaikhha , Mathieu Huot , Shideh Hashemian

The aim of this article is to investigate the issues of multiplicative inverses and composition in the set of formal Laurent series. We show the lack of general uniqueness of inverses of formal Laurent series; necessary and sufficient…

Commutative Algebra · Mathematics 2025-08-26 Dawid Bugajewski

In this work we introduce the concept of $s$-sparse observability for large systems of ordinary differential equations. Let $\dot x=f(t,x)$ be such a system. At time $T>0$, suppose we make a set of observations $b=Ax(T)$ of the solution of…

Optimization and Control · Mathematics 2010-04-22 Nicolae Tarfulea

This work develops a framework to discover relations between the components of the solution to a given initial-value problem for a first-order system of ordinary differential equations. This is done by using sparse identification techniques…

Optimization and Control · Mathematics 2025-07-22 Nicolae Tarfulea

We give a simple algebraic derivation of a useful determinantal identity for multilevel systems such as random matrix chains and finite determinantal point processes, with applications to the calculation of point correlators, gap…

Mathematical Physics · Physics 2014-10-07 J. Harnad , A. Yu. Orlov

We consider the high-dimensional discriminant analysis problem. For this problem, different methods have been proposed and justified by establishing exact convergence rates for the classification risk, as well as the l2 convergence results…

Machine Learning · Statistics 2013-06-28 Mladen Kolar , Han Liu

We show how to construct sparse polynomial systems that have non-trivial lower bounds on their numbers of real solutions. These are unmixed systems associated to certain polytopes. For the order polytope of a poset P this lower bound is the…

Algebraic Geometry · Mathematics 2010-03-29 Evgenia Soprunova , Frank Sottile

This paper aims at achieving a simultaneously sparse and low-rank estimator from the semidefinite population covariance matrices. We first benefit from a convex optimization which develops $l_1$-norm penalty to encourage the sparsity and…

Statistics Theory · Mathematics 2014-08-08 Shenglong Zhou , Naihua Xiu , Ziyan Luo , Lingchen Kong

We explore a recently proposed Variational Dropout technique that provided an elegant Bayesian interpretation to Gaussian Dropout. We extend Variational Dropout to the case when dropout rates are unbounded, propose a way to reduce the…

Machine Learning · Statistics 2017-06-14 Dmitry Molchanov , Arsenii Ashukha , Dmitry Vetrov

The implicit compact finite-difference scheme was developed for evolutionary partial differential parabolic and Schr\"odinger-type equations and systems with a weak nonlinearity. To make a temporal step of the compact implicit scheme we…

Mathematical Physics · Physics 2018-12-31 Vladimir Gordin , Evgenii Tsymbalov

This paper analyzes the eigenvalue distribution of neutral differential systems and the corresponding difference systems, and establishes the relationship between the eigenvalue distribution and delay-independent stability of neutral…

Dynamical Systems · Mathematics 2007-05-23 Ping Wei , Qiang Guan , Wensheng Yu , Long Wang

A formula expressing the fermionic determinant (a large order polynomial) as an infinite product of smaller determinants is derived and discussed. These smaller determinants are of a fixed size, independent of the size of the lattice and…

High Energy Physics - Lattice · Physics 2016-11-03 Ion-Olimpiu Stamatescu , Erhard Seiler

This paper is concerned with the problem of approximating the determinant of A for a large sparse symmetric positive definite matrix A. It is shown that an efficient solution of this problem is obtained by using a sparse approximate inverse…

High Energy Physics - Lattice · Physics 2007-05-23 Arnold Reusken
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