Abstract
A new algorithm is introduced which computes the multivariate leading coefficients of polynomial factors from their univariate images. This algorithm is incorporated into a sparse Hensel lifting scheme and only requires the factorization of a single univariate image. The algorithm also provides the content of the input polynomial in the main variable as a by-product. We show how we can take advantage of this property when computing the GCD of multivariate polynomials by sparse Hensel lifting.
Cite
CITATION STYLE
Kaltofen, E. (1985). Sparse hensel lifting. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 204 LNCS, pp. 4–17). Springer Verlag. https://doi.org/10.1007/3-540-15984-3_230
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