A three-term Polak-Ribière-Polyak derivative-free method and its application to image restoration
In this paper, a derivative-free method for solving convex constrained nonlinear equations involving a monotone operator with a Lipschitz condition imposed on the underlying operator is introduced and studied.
Abdulkarim Hassan Ibrahim +3 more
doaj +1 more source
On representations of the feasible set in convex optimization [PDF]
We consider the convex optimization problem $\min \{f(x) : g_j(x)\leq 0, j=1,...,m\}$ where $f$ is convex, the feasible set K is convex and Slater's condition holds, but the functions $g_j$ are not necessarily convex.
A. Ben-Tal +8 more
core +5 more sources
An elementary approach to polynomial optimization on polynomial meshes [PDF]
A polynomial mesh on a multivariate compact set or manifold is a sequence of finite norming sets for polynomials whose norming constant is independent of degree.
Vianello, Marco
core +3 more sources
Halpern-type proximal point algorithm in complete CAT(0) metric spaces
First, Halpern-type proximal point algorithm is introduced in complete CAT(0) metric spaces. Then, Browder convergence theorem is considered for this algorithm and also we prove that Halpern-type proximal point algorithm converges strongly to a zero of ...
Heydari Mohammad Taghi, Ranjbar Sajad
doaj +1 more source
Implementation of LDG method for 3D unstructured meshes
This paper describes an implementation of the Local Discontinuous Galerkin method (LDG) applied to elliptic problems in 3D. The implementation of the major operators is discussed.
Filander A. Sequeira Chavarría +1 more
doaj +1 more source
Iterative algorithms with seminorm‐induced oblique projections
A definition of oblique projections onto closed convex sets that use seminorms induced by diagonal matrices which may have zeros on the diagonal is introduced. Existence and uniqueness of such projections are secured via directional affinity of the sets with respect to the diagonal matrices involved. A block‐iterative algorithmic scheme for solving the
Yair Censor, Tommy Elfving
wiley +1 more source
Adaptive First-Order Methods for General Sparse Inverse Covariance Selection [PDF]
In this paper, we consider estimating sparse inverse covariance of a Gaussian graphical model whose conditional independence is assumed to be partially known.
Lu, Zhaosong
core +3 more sources
Convergence of a short‐step primal‐dual algorithm based on the Gauss‐Newton direction
We prove the theoretical convergence of a short‐step, approximate path‐following, interior‐point primal‐dual algorithm for semidefinite programs based on the Gauss‐Newton direction obtained from minimizing the norm of the perturbed optimality conditions. This is the first proof of convergence for the Gauss‐Newton direction in this context.
Serge Kruk, Henry Wolkowicz
wiley +1 more source
An entropic regularization method for solving systems of fuzzy linear inequalities
Solving systems of fuzzy linear inequalities could lead to the solutions of fuzzy linear programs. It is shown that a system of fuzzy linear inequalities can be converted to a regular min‐max problem. An entropic regularization method is introduced for solving such a problem. Some computational results are included.
F. B. Liu
wiley +1 more source
MINIMUM COST NETWORK FLOWS: PROBLEMS, ALGORITHMS, AND SOFTWARE
: We present a wide range of problems concerning minimum cost network flows, and give an overview of the classic linear single-commodity Minimum Cost Network Flow Problem (MCNFP) and some other closely related problems, either tractable or intractable ...
Angelo Sifaleras
semanticscholar +1 more source

