316 citations · 903 across the 32 of their papers we have counts for
7 papers · 1 filter
Positive Semi-Definiteness of Generalized Anti-Circulant Tensors
Guoyin Li, Liqun Qi, Qun Wang
Anti-circulant tensors have applications in exponential data fitting. They are special Hankel tensors. In this paper, we extend the definition of anti-circulant tensors to generali…
SOS-Hankel Tensors: Theory and Application
Guoyin Li, Liqun Qi, Yi Xu
Hankel tensors arise from signal processing and some other applications. SOS (sum-of-squares) tensors are positive semi-definite symmetric tensors, but not vice versa. The problem…
New Classes of Positive Semi-Definite Hankel Tensors
Qun Wang, Guoyin Li, Liqun Qi +1
A Hankel tensor is called a strong Hankel tensor if the Hankel matrix generated by its generating vector is positive semi-definite. It is known that an even order strong Hankel ten…
Douglas-Rachford splitting for nonconvex optimization with application to nonconvex feasibility problems
Guoyin Li, Ting Kei Pong
We adapt the Douglas-Rachford (DR) splitting method to solve nonconvex feasibility problems by studying this method for a class of nonconvex optimization problem. While the converg…
A Tensor Analogy of Yuan's Theorem of the Alternative and Polynomial Optimization with Sign structure
Shenglong Hu, Guoyin Li, Liqun Qi
Yuan's theorem of the alternative is an important theoretical tool in optimization, which provides a checkable certificate for the infeasibility of a strict inequality system invol…
Global convergence of splitting methods for nonconvex composite optimization
Guoyin Li, Ting Kei Pong
We consider the problem of minimizing the sum of a smooth function with a bounded Hessian, and a nonsmooth function. We assume that the latter function is a composition of a pr…
Robust Solutions to Multi-Objective Linear Programs with Uncertain Data
M. A. Goberna, V. Jeyakumar, G. Li +1
In this paper we examine multi-objective linear programming problems in the face of data uncertainty both in the objective function and the constraints. First, we derive a formula…