TY - JOUR
T1 - A local decision test for sparse polynomials
AU - Grigorescu, Elena
AU - Jung, Kyomin
AU - Rubinfeld, Ronitt
N1 - Funding Information:
E-mail addresses: [email protected] (E. Grigorescu), [email protected] (K. Jung), [email protected] (R. Rubinfeld). 1 Supported by NSF award CCF-0829672. 2 Supported by the Engineering Research Center of Excellence Program of Korea MEST/National Research Foundation of Korea (NRF) (Grant 2009-0063242). 3 Supported by NSF grants 0732334 and 0728645, Marie Curie Reintegration grant PIRG03-GA-2008-231077, and the Israel Science Foundation grant nos. 1147/09 and 1675/09.
PY - 2010/9/30
Y1 - 2010/9/30
N2 - An ℓ-sparse (multivariate) polynomial is a polynomial containing at most ℓ-monomials in its explicit description. We assume that a polynomial is implicitly represented as a black-box: on an input query from the domain, the black-box replies with the evaluation of the polynomial at that input. We provide an efficient, randomized algorithm, that can decide whether a polynomial f:Fqn→Fq given as a black-box is ℓ-sparse or not, provided that q is large compared to the polynomial's total degree. The algorithm makes only O(ℓ) queries, which is independent of the domain size. The running time of our algorithm (in the bit-complexity model) is poly(n,logd,ℓ), where d is an upper bound on the degree of each variable. Existing interpolation algorithms for polynomials in the same model run in time poly(n,d,ℓ). We provide a similar test for polynomials with integer coefficients.
AB - An ℓ-sparse (multivariate) polynomial is a polynomial containing at most ℓ-monomials in its explicit description. We assume that a polynomial is implicitly represented as a black-box: on an input query from the domain, the black-box replies with the evaluation of the polynomial at that input. We provide an efficient, randomized algorithm, that can decide whether a polynomial f:Fqn→Fq given as a black-box is ℓ-sparse or not, provided that q is large compared to the polynomial's total degree. The algorithm makes only O(ℓ) queries, which is independent of the domain size. The running time of our algorithm (in the bit-complexity model) is poly(n,logd,ℓ), where d is an upper bound on the degree of each variable. Existing interpolation algorithms for polynomials in the same model run in time poly(n,d,ℓ). We provide a similar test for polynomials with integer coefficients.
KW - Multivariate polynomials
KW - Randomized algorithms
KW - Sparsity tests
UR - http://www.scopus.com/inward/record.url?scp=77954973414&partnerID=8YFLogxK
U2 - 10.1016/j.ipl.2010.07.012
DO - 10.1016/j.ipl.2010.07.012
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AN - SCOPUS:77954973414
SN - 0020-0190
VL - 110
SP - 898
EP - 901
JO - Information Processing Letters
JF - Information Processing Letters
IS - 20
ER -