Zhengfeng Yang

Works (4)

Updated: July 5th, 2023 15:54

2018 article

Sparse Polynomial Interpolation With Arbitrary Orthogonal Polynomial Bases

ISSAC'18: PROCEEDINGS OF THE 2018 ACM INTERNATIONAL SYMPOSIUM ON SYMBOLIC AND ALGEBRAIC COMPUTATION, pp. 223–230.

By: E. Imamoglu  n, E. Kaltofen n & Z. Yang*

TL;DR: These algorithms deterministically recover the sparse representation in the First, Second, Third and Fourth Kind Chebyshev representation from exactly t + B evaluations, and generalize to bases whose ChebysHEv recurrences have parametric scalars. (via Semantic Scholar)
Source: Web Of Science
Added: February 25, 2019

2008 journal article

Approximate factorization of multivariate polynomials using singular value decomposition

JOURNAL OF SYMBOLIC COMPUTATION, 43(5), 359–376.

By: E. Kaltofen n, J. May*, Z. Yang* & L. Zhi *

author keywords: multivariate polynomial factorization; approximate factorization; singular value decomposition; numerical algebra; Gauss-Newton optimization
TL;DR: These algorithms are based on a generalization of the differential forms introduced by W. Ruppert and S. Gao to many variables, and use singular value decomposition or structured total least squares approximation and Gauss-Newton optimization to numerically compute the approximate multivariate factors. (via Semantic Scholar)
Source: Web Of Science
Added: August 6, 2018

2007 conference paper

On exact and approximate interpolation of sparse rational functions

ISSAC 2007: International Symposium for Symbolic and Algebraic Computation: Proceedings.

By: E. Kaltofen n & Z. Yang n

TL;DR: Five new algorithms for sparse rational function interpolation algorithm in the hybrid symbolic-numeric setting when the black box for the function returns real and complex values with noise are presented and analyzed. (via Semantic Scholar)
Source: NC State University Libraries
Added: August 6, 2018

2007 conference paper

On probabilistic analysis of randomization in hybrid symbolic-numeric algorithms

International Workshop on Symbolic-Numeric Computation: Proceedings. New York: ACM Press.

By: E. Kaltofen, Z. Yang & L. Zhi

Source: NC State University Libraries
Added: August 6, 2018

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