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20042020
most citedA Fully Sparse Implementation of a Primal-Dual Interior-Point Potential Reduction Method for Semidefinite Programming

11 citations · 12 across the 7 of their papers we have counts for

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math.NA2020

An adaptive iterative/subdivision hybrid algorithm for curve/curve intersection

Gun Srijuntongsiri

The behavior of the iterative/subdivision hybrid algorithm for curve/curve intersection proposed in [20] depends on the choice of the domain for their convergence test. Using eithe…

math.NA2016

A New Pivot Selection Algorithm for Symmetric Indefinite Factorization Arising in Quadratic Programming with Block Constraint Matrices

Duangpen Jetpipattanapong, Gun Srijuntongsiri

Quadratic programmingis a class of constrained optimization problem with quadratic objective functions and linear constraints. It has applications in many areas and is also used to…

math.NA2016

New Pivot Selection for Sparse Symmetric Indefinite Factorization

Duangpen Jetpipattanapong, Gun Srijuntongsiri

We propose a new pivot selection technique for symmetric indefinite factorization of sparse matrices. Such factorization should maintain both sparsity and numerical stability of th…

math.NA2007★ 1 cited

Properties of polynomial bases used in a line-surface intersection algorithm

Gun Srijuntongsiri, Stephen A. Vavasis

In [5], Srijuntongsiri and Vavasis propose the "Kantorovich-Test Subdivision algorithm", or KTS, which is an algorithm for finding all zeros of a polynomial system in a bounded reg…

math.NA2006

A Condition Number Analysis of a Line-Surface Intersection Algorithm

Gun Srijuntongsiri, Stephen A. Vavasis

We propose an algorithm based on Newton's method and subdivision for finding all zeros of a polynomial system in a bounded region of the plane. This algorithm can be used to find t…

math.NA2004★ 11 cited

A Fully Sparse Implementation of a Primal-Dual Interior-Point Potential Reduction Method for Semidefinite Programming

Gun Srijuntongsiri, Stephen A. Vavasis

In this paper, we show a way to exploit sparsity in the problem data in a primal-dual potential reduction method for solving a class of semidefinite programs. When the problem data…