Maximum block improvement and polynomial optimization
In this paper we propose an efficient method for solving the spherically constrained
homogeneous polynomial optimization problem. The new approach has the following three …
homogeneous polynomial optimization problem. The new approach has the following three …
Compressed quadratization of higher order binary optimization problems
Recent hardware advances in quantum and quantum-inspired annealers promise
substantial speedup for solving NP-hard combinatorial optimization problems compared to …
substantial speedup for solving NP-hard combinatorial optimization problems compared to …
Convexification of power flow equations in the presence of noisy measurements
This paper is concerned with the power system state estimation (PSSE) problem that aims to
find the unknown operating point of a power network based on a given set of measurements …
find the unknown operating point of a power network based on a given set of measurements …
Discrete polynomial optimization with coherent networks of condensates and complex coupling switching
N Stroev, NG Berloff - Physical review letters, 2021 - APS
Gain-dissipative platforms consisting of lasers, optical parametric oscillators and
nonequilibrium condensates operating at the condensation or coherence threshold have …
nonequilibrium condensates operating at the condensation or coherence threshold have …
Best Rank-One Approximation of Fourth-Order Partially Symmetric Tensors by Neural Network.
X Wang, M Che, Y Wei - Numerical Mathematics: Theory …, 2018 - search.ebscohost.com
Our purpose is to compute the multi-partially symmetric rank-one approximations of higher-
order multi-partially symmetric tensors. A special case is the partially symmetric rank-one …
order multi-partially symmetric tensors. A special case is the partially symmetric rank-one …
Probability bounds for polynomial functions in random variables
Random sampling is a simple but powerful method in statistics and in the design of
randomized algorithms. In a typical application, random sampling can be applied to estimate …
randomized algorithms. In a typical application, random sampling can be applied to estimate …
On the consistent path problem
The application of decision diagrams in combinatorial optimization has proliferated in the
last decade. In recent years, authors have begun to investigate how to use not one, but a set …
last decade. In recent years, authors have begun to investigate how to use not one, but a set …
On the tensor spectral p-norm and its dual norm via partitions
B Chen, Z Li - Computational Optimization and Applications, 2020 - Springer
This paper presents a generalization of the spectral norm and the nuclear norm of a tensor
via arbitrary tensor partitions, a much richer concept than block tensors. We show that the …
via arbitrary tensor partitions, a much richer concept than block tensors. We show that the …
Characterizing real-valued multivariate complex polynomials and their symmetric tensor representations
In this paper we study multivariate polynomial functions in complex variables and their
corresponding symmetric tensor representations. The focus is to find conditions under which …
corresponding symmetric tensor representations. The focus is to find conditions under which …
Exact semidefinite programming relaxations with truncated moment matrix for binary polynomial optimization problems
For binary polynomial optimization problems (POPs) of degree d with n variables, we prove
that the ⌈(n+d-1)/2⌉ th semidefinite programming (SDP) relaxation in Lasserre's hierarchy …
that the ⌈(n+d-1)/2⌉ th semidefinite programming (SDP) relaxation in Lasserre's hierarchy …