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We give a new probabilistic algorithm for interpolating a "sparse" polynomial f given by a straight-line program. Our algorithm constructs an approximation f* of f, such that their difference probably has at most half the number of terms of…

Symbolic Computation · Computer Science 2014-01-24 Andrew Arnold , Mark Giesbrecht , Daniel S. Roche

Consider a sparse multivariate polynomial f with integer coefficients. Assume that f is represented as a "modular black box polynomial", e.g. via an algorithm to evaluate f at arbitrary integer points, modulo arbitrary positive integers.…

Symbolic Computation · Computer Science 2024-01-01 Joris van der Hoeven , Grégoire Lecerf

In this paper, we propose new deterministic and Monte Carlo interpolation algorithms for sparse multivariate polynomials represented by straight-line programs. Let $f$ be an $n$-variate polynomial given by a straight-line program, which has…

Symbolic Computation · Computer Science 2018-07-18 Qiao-Long Huang , Xiao-Shan Gao

In this paper, we propose two new interpolation algorithms for sparse multivariate polynomials represented by a straight-line program(SLP). Both of our algorithms work over any finite fields $F_q$ with large characteristic. The first one is…

Symbolic Computation · Computer Science 2020-02-11 Qiao-Long Huang

Simply put, a sparse polynomial is one whose zero coefficients are not explicitly stored. Such objects are ubiquitous in exact computing, and so naturally we would like to have efficient algorithms to handle them. However, with this compact…

Symbolic Computation · Computer Science 2018-07-24 Daniel S. Roche

We present a new Monte Carlo algorithm for the interpolation of a straight-line program as a sparse polynomial $f$ over an arbitrary finite field of size $q$. We assume a priori bounds $D$ and $T$ are given on the degree and number of terms…

Symbolic Computation · Computer Science 2014-05-05 Andrew Arnold , Mark Giesbrecht , Daniel S. Roche

Consider a sparse polynomial in several variables given explicitly as a sum of non-zero terms with coefficients in an effective field. In this paper, we present several algorithms for factoring such polynomials and related tasks (such as…

Symbolic Computation · Computer Science 2025-02-26 Alexander Demin , Joris van der Hoeven

Given a way to evaluate an unknown polynomial with integer coefficients, we present new algorithms to recover its nonzero coefficients and corresponding exponents. As an application, we adapt this interpolation algorithm to the problem of…

Symbolic Computation · Computer Science 2022-05-19 Pascal Giorgi , Bruno Grenet , Armelle Perret du Cray , Daniel S. Roche

Provided a special function of one variable and some of its derivatives can be accurately computed over a finite range, a method is presented to build a series of polynomial approximations of the function with a defined relative error over…

Computational Physics · Physics 2007-05-23 C. Semay

Sparse interpolation} refers to the exact recovery of a function as a short linear combination of basis functions from a limited number of evaluations. For multivariate functions, the case of the monomial basis is well studied, as is now…

Symbolic Computation · Computer Science 2020-01-27 Evelyne Hubert , Michael F. Singer

We consider the problem of interpolating an unknown multivariate polynomial with coefficients taken from a finite field or as numerical approximations of complex numbers. Building on the recent work of Garg and Schost, we improve on the…

Symbolic Computation · Computer Science 2011-04-05 Mark Giesbrecht , Daniel S. Roche

In this paper, we give new sparse interpolation algorithms for black box univariate and multivariate rational functions h=f/g whose coefficients are integers with an upper bound. The main idea is as follows: choose a proper integer beta and…

Symbolic Computation · Computer Science 2017-06-06 Qiao-Long Huang , Xiao-Shan Gao

We present a probabilistic algorithm to compute the product of two univariate sparse polynomials over a field with a number of bit operations that is quasi-linear in the size of the input and the output. Our algorithm works for any field of…

Symbolic Computation · Computer Science 2020-09-01 Pascal Giorgi , Bruno Grenet , Armelle Perret du Cray

The works presented in this habilitation concern the algorithmics of polynomials. This is a central topic in computer algebra, with numerous applications both within and outside the field - cryptography, error-correcting codes, etc. For…

Symbolic Computation · Computer Science 2026-03-09 Bruno Grenet

In this paper, we give new sparse interpolation algorithms for black box polynomial f whose coefficients are from a finite set. In the univariate case, we recover f from one evaluation of f(a) for a sufficiently large number a. In the…

Symbolic Computation · Computer Science 2017-06-23 Qiao-Long Huang , Xiao-Shan Gao

We consider the problem of interpolating a sparse multivariate polynomial over a finite field, represented with a black box. Building on the algorithm of Ben-Or and Tiwari for interpolating polynomials over rings with characteristic zero,…

Symbolic Computation · Computer Science 2020-02-11 Qiao-Long Huang

We present algorithms performing sparse univariate polynomial interpolation with errors in the evaluations of the polynomial. Based on the initial work by Comer, Kaltofen and Pernet [Proc. ISSAC 2012], we define the sparse polynomial…

Symbolic Computation · Computer Science 2014-06-19 Erich L. Kaltofen , Clément Pernet

We consider space-saving versions of several important operations on univariate polynomials, namely power series inversion and division, division with remainder, multi-point evaluation, and interpolation. Now-classical results show that…

Symbolic Computation · Computer Science 2020-09-01 Pascal Giorgi , Bruno Grenet , Daniel S. Roche

In some fields such as Mathematics Mechanization, automated reasoning and Trustworthy Computing etc., exact results are needed. Symbolic computations are used to obtain the exact results. Symbolic computations are of high complexity. In…

Symbolic Computation · Computer Science 2008-09-10 Yong Feng , Jingzhong Zhang , Xiaolin Qin , Xun Yuan

We propose a fast greedy algorithm to compute sparse representations of signals from continuous dictionaries that are factorizable, i.e., with atoms that can be separated as a product of sub-atoms. Existing algorithms strongly reduce the…

Signal Processing · Electrical Eng. & Systems 2020-12-01 Gilles Monnoyer de Galland , Luc Vandendorpe , Laurent Jacques
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