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Related papers: Interpolation of Shifted-Lacunary Polynomials

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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

We consider quantum interpolation of polynomials. We imagine a quantum computer with black-box access to input/output pairs (x_i, f(x_i)), where f is a degree-d polynomial, and we wish to compute f(0). We give asymptotically tight quantum…

Quantum Physics · Physics 2010-03-19 Daniel M. Kane , Samuel A. Kutin

An input- and output-sensitive GCD algorithm for multi-variate polynomials over finite fields is proposed by combining the modular method with the Ben-Or/Tiwari sparse interpolation. The bit complexity of the algorithm is given and is…

Symbolic Computation · Computer Science 2022-07-29 Qiao-Long Huang , Xiao-Shan Gao

We present sparse interpolation algorithms for recovering a polynomial with $\le B$ terms from $N$ evaluations at distinct values for the variable when $\le E$ of the evaluations can be erroneous. Our algorithms perform exact arithmetic in…

Symbolic Computation · Computer Science 2020-11-05 Erich L. Kaltofen , Zhi-Hong Yang

A polynomial matrix inequality is a formula asserting that a polynomial matrix is positive semidefinite. Polynomial matrix optimization concerns minimizing the smallest eigenvalue of a symmetric polynomial matrix subject to a tuple of…

Optimization and Control · Mathematics 2025-06-06 Jared Miller , Jie Wang , Feng Guo

We propose an efficient algorithm to compute the real roots of a sparse polynomial $f\in\mathbb{R}[x]$ having $k$ non-zero real-valued coefficients. It is assumed that arbitrarily good approximations of the non-zero coefficients are given…

Symbolic Computation · Computer Science 2017-04-25 Gorav Jindal , Michael Sagraloff

Based on the computation of a superset of the implicit support, implicitization of a parametrically given hyper-surface is reduced to computing the nullspace of a numeric matrix. Our approach exploits the sparseness of the given parametric…

Algebraic Geometry · Mathematics 2014-11-12 Ioannis Emiris , Tatjana Kalinka , Christos Konaxis

Efficient handling of sparse data is a key challenge in Computer Science. Binary convolutions, such as polynomial multiplication or the Walsh Transform are a useful tool in many applications and are efficiently solved. In the last decade,…

Data Structures and Algorithms · Computer Science 2014-10-22 Amihood Amir , Oren Kapah , Ely Porat , Amir Rothschild

We consider solutions to the equation f = h^r for polynomials f and h and integer r > 1. Given a polynomial f in the lacunary (also called sparse or super-sparse) representation, we first show how to determine if f can be written as h^r…

Symbolic Computation · Computer Science 2015-03-13 Mark Giesbrecht , Daniel S. Roche

In this paper we study sums of powers of affine functions in (mostly) one variable. Although quite simple, this model is a generalization of two well-studied models: Waring decomposition and sparsest shift. For these three models there are…

Computational Complexity · Computer Science 2017-10-25 Ignacio Garcia-Marco , Pascal Koiran , Timothée Pecatte

We present an algorithm to reduce the computational effort for the multiplication of a given matrix with an unknown column vector. The algorithm decomposes the given matrix into a product of matrices whose entries are either zero or integer…

Information Theory · Computer Science 2020-02-28 Ralf R. Müller , Bernhard Gäde , Ali Bereyhi

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

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 give the first algorithm that is both query-efficient and time-efficient for testing whether an unknown function $f: \{0,1\}^n \to \{0,1\}$ is an $s$-sparse GF(2) polynomial versus $\eps$-far from every such polynomial. Our algorithm…

Computational Complexity · Computer Science 2008-05-14 Ilias Diakonikolas , Homin K. Lee , Kevin Matulef , Rocco A. Servedio , Andrew Wan

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

The Qth-power algorithm produces a useful canonical P-module presentation for the integral closures of certain integral extensions of $P:=\mathbf{F}[x_n,...,x_1]$, a polyonomial ring over the finite field $\mathbf{F}:=\mathbf{Z}_q$ of $q$…

Commutative Algebra · Mathematics 2013-01-28 Douglas A. Leonard

We present a new rational approximation algorithm based on the empirical interpolation method for interpolating a family of parametrized functions to rational polynomials with invariant poles, leading to efficient numerical algorithms for…

Numerical Analysis · Mathematics 2025-01-23 Aidi Li , Yuwen Li

Motivated by a recently introduced HIMMO key distribution scheme, we consider a modification of the noisy polynomial interpolation problem of recovering an unknown polynomial $f(X) \in Z[X]$ from approximate values of the residues of $f(t)$…

Number Theory · Mathematics 2014-01-08 Oscar Garcia-Morchon , Ronald Rietman , Igor E. Shparlinski , Ludo Tolhuizen

One of the biggest open problems in computational algebra is the design of efficient algorithms for Gr{\"o}bner basis computations that take into account the sparsity of the input polynomials. We can perform such computations in the case of…

Symbolic Computation · Computer Science 2018-06-22 Matías Bender , Jean-Charles Faugère , Elias Tsigaridas

We present two new algorithms for the computation of the q-integer linear decomposition of a multivariate polynomial. Such a decomposition is essential for the treatment of q-hypergeometric symbolic summation via creative telescoping and…

Symbolic Computation · Computer Science 2021-02-15 Mark Giesbrecht , Hui Huang , George Labahn , Eugene Zima