Primal and dual active-set methods for convex quadratic programming
, 2015 Computational methods are proposed for solving a convex quadratic program (QP). Active-set methods are defined for a particular primal and dual formulation of a QP with general equality constraints and simple lower bounds on the variables.
Forsgren, Anders +2 more
core +1 more source
All Real Eigenvalues of Symmetric Tensors
, 2014 This paper studies how to compute all real eigenvalues of a symmetric tensor. As is well known, the largest or smallest eigenvalue can be found by solving a polynomial optimization problem, while the other middle eigenvalues can not.
Cui, Chun-Feng +2 more
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An infeasible full NT-step interior point method for circular optimization
Numerical Algebra, Control & Optimization, 2017 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kheirfam, Behrouz, Wang, Guoqiang
openaire +3 more sources
OSQP: An Operator Splitting Solver for Quadratic Programs
, 2018 We present a general-purpose solver for convex quadratic programs based on the alternating direction method of multipliers, employing a novel operator splitting technique that requires the solution of a quasi-definite linear system with the same ...
Banjac, Goran +4 more
core +1 more source
Spatial Period-Doubling Agglomeration of a Core-Periphery Model with a System of Cities [PDF]
, 2009 The orientation and progress of spatial agglomeration for Krugman's core--periphery model are investigated in this paper. Possible agglomeration patterns for a system of cities spread uniformly on a circle are set forth theoretically.
Akamatsu, Takashi +2 more
core
Getting Feasible Variable Estimates From Infeasible Ones: MRF Local Polytope Study [PDF]
, 2012 This paper proposes a method for construction of approximate feasible primal solutions from dual ones for large-scale optimization problems possessing certain separability properties.
Savchynskyy, Bogdan, Schmidt, Stefan
core
A Full Nesterov-Todd Step Infeasible Interior-point Method for Symmetric Optimization in the Wider Neighborhood of the Central Path. [PDF]
Stat Optim Inf Comput, 2021 Lesaja G, Wang GQ, Oganian A.
europepmc +1 more source
A distributed primal-dual interior-point method for loosely coupled problems using ADMM [PDF]
, 2015 In this paper we propose an efficient distributed algorithm for solving loosely coupled convex optimization problems. The algorithm is based on a primal-dual interior-point method in which we use the alternating direction method of multipliers (ADMM) to ...
Annergren, Mariette +3 more
core
A bounded degree SOS hierarchy for polynomial optimization
, 2015 We consider a new hierarchy of semidefinite relaxations for the general polynomial optimization problem $(P):\:f^{\ast}=\min \{\,f(x):x\in K\,\}$ on a compact basic semi-algebraic set $K\subset\R^n$.
A Sos +10 more
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Worst-Case Linear Discriminant Analysis as Scalable Semidefinite Feasibility Problems
, 2014 In this paper, we propose an efficient semidefinite programming (SDP) approach to worst-case linear discriminant analysis (WLDA). Compared with the traditional LDA, WLDA considers the dimensionality reduction problem from the worst-case viewpoint, which ...
Hengel, Anton van den +3 more
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