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Related papers: A sparse overview on sparse resultants

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Sparse (or toric) elimination exploits the structure of polynomials by measuring their complexity in terms of Newton polytopes instead of total degree. The sparse, or Newton, resultant generalizes the classical homogeneous resultant and its…

Symbolic Computation · Computer Science 2012-01-30 Ioannis Z. Emiris

It has by now become a standard approach to use the theory of sparse (or toric) elimination, based on the Newton polytope of a polynomial, in order to reveal and exploit the structure of algebraic systems. This talk surveys compact…

Computational Complexity · Computer Science 2017-10-16 Ioannis Emiris

We present a product formula for the initial parts of the sparse resultant associated to an arbitrary family of supports, generalising a previous result by Sturmfels. This allows to compute the homogeneities and degrees of the sparse…

Commutative Algebra · Mathematics 2021-09-22 Carlos D'Andrea , Gabriela Jeronimo , Martin Sombra

We refine and extend a result by Tuitman on the supports of a Bezout identity satisfied by a finite sequence of sparse Laurent polynomials without common zeroes in the toric variety associated to their supports. When the number of these…

Algebraic Geometry · Mathematics 2025-06-03 Carlos D'Andrea , Gabriela Jeronimo

The Canny-Emiris formula gives the sparse resultant as the ratio of the determinant of a Sylvester-type matrix over a minor of it, both obtained via a mixed subdivision algorithm. The same authors gave an explicit class of mixed…

Combinatorics · Mathematics 2024-01-09 Carles Checa , Ioannis Z. Emiris

We present formulas for computing the resultant of sparse polynomials as a quotient of two determinants, the denominator being a minor of the numerator. These formulas extend the original formulation given by Macaulay for homogeneous…

Algebraic Geometry · Mathematics 2007-05-23 Carlos D'Andrea

We present a Poisson formula for sparse resultants and a formula for the product of the roots of a family of Laurent polynomials, which are valid for arbitrary families of supports. To obtain these formulae, we show that the sparse…

Algebraic Geometry · Mathematics 2015-06-12 Carlos D'Andrea , Martin Sombra

The sparse difference resultant introduced in \citep{gao-2015} is a basic concept in difference elimination theory. In this paper, we show that the sparse difference resultant of a generic Laurent transformally essential system can be…

Symbolic Computation · Computer Science 2021-04-21 Chun-Ming Yuan , Zhi-Yong Zhang

In this paper, we first introduce the concept of Laurent differentially essential systems and give a criterion for Laurent differentially essential systems in terms of their supports. Then the sparse differential resultant for a Laurent…

Symbolic Computation · Computer Science 2012-06-19 Wei Li , Chun-Ming Yuan , Xiao-Shan Gao

Effective computation of resultants is a central problem in elimination theory and polynomial system solving. Commonly, we compute the resultant as a quotient of determinants of matrices and we say that there exists a determinantal formula…

Commutative Algebra · Mathematics 2021-05-28 Matías R. Bender , Jean-Charles Faugère , Angelos Mantzaflaris , Elias Tsigaridas

We give a new theoretical tool to solve sparse systems with finitely many solutions. It is based on toric varieties and basic linear algebra; eigenvalues, eigenvectors and coefficient matrices. We adapt Eigenvalue theorem and Eigenvector…

Algebraic Geometry · Mathematics 2015-08-07 César Massri

We investigate algebraic and arithmetic properties of a class of sequences of sparse polynomials that have binomial coefficients both as exponents and as coefficients. In addition to divisibility and irreducibility results we also consider…

Number Theory · Mathematics 2021-09-27 Karl Dilcher , Maciej Ulas

We establish how the coefficients of a sparse polynomial system influence the sum (or the trace) of its zeros. As an application, we develop numerical tests for verifying whether a set of solutions to a sparse system is complete. These…

Algebraic Geometry · Mathematics 2022-01-14 Taylor Brysiewicz , Michael Burr

Many computer vision applications require robust and efficient estimation of camera geometry from a minimal number of input data measurements, i.e., solving minimal problems in a RANSAC framework. Minimal problems are usually formulated as…

Computer Vision and Pattern Recognition · Computer Science 2023-09-04 Snehal Bhayani , Janne Heikkilä , Zuzana Kukelova

Let $\cP$ be a system of $n$ linear nonhomogeneous ordinary differential polynomials in a set $U$ of $n-1$ differential indeterminates. Differential resultant formulas are presented to eliminate the differential indeterminates in $U$ from…

Classical Analysis and ODEs · Mathematics 2013-06-04 Sonia L. Rueda

Toric (or sparse) elimination theory is a framework developped during the last decades to exploit monomial structures in systems of Laurent polynomials. Roughly speaking, this amounts to computing in a \emph{semigroup algebra}, \emph{i.e.}…

Symbolic Computation · Computer Science 2014-06-26 Jean-Charles Faugere , Pierre-Jean Spaenlehauer , Jules Svartz

We propose a new lifting and recombination scheme for rational bivariate polynomial factorization that takes advantage of the Newton polytope geometry. We obtain a deterministic algorithm that can be seen as a sparse version of an algorithm…

Algebraic Geometry · Mathematics 2009-12-07 Martin Weimann

We give the first exact determinantal formula for the resultant of an unmixed sparse system of four Laurent polynomials in three variables with arbitrary support. This follows earlier work by the author on exact formulas for bivariate…

Algebraic Geometry · Mathematics 2009-09-29 Amit Khetan

In this paper, the concept of sparse difference resultant for a Laurent transformally essential system of difference polynomials is introduced and a simple criterion for the existence of sparse difference resultant is given. The concept of…

Symbolic Computation · Computer Science 2013-09-25 Wei Li , Chun-Ming Yuan , Xiao-Shan Gao

We propose a new approach for metric learning by framing it as learning a sparse combination of locally discriminative metrics that are inexpensive to generate from the training data. This flexible framework allows us to naturally derive…

Machine Learning · Computer Science 2019-01-25 Yuan Shi , Aurélien Bellet , Fei Sha
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