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
core
Improved Full-Newton-Step Infeasible Interior-Point Method for Linear Complementarity Problems
Croatian Operational Research Review, 2016 We present an Infeasible Interior-Point Method for monotone Linear Complementarity Problem (LCP) which is an improved version of the algorithm given in [13]. In the earlier version, each iteration consisted of one feasibility step and few centering steps.
Lesaja, Goran, Ozen, Mustafa
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A preconditioned inexact infeasible quantum interior point method for linear optimization
Computational Optimization and ApplicationsAbstract Quantum Interior Point Methods (QIPMs) have been attracting significant interests recently due to their potential of solving optimization problems substantially faster than state-of-the-art conventional algorithms. In general, QIPMs use Quantum Linear System Algorithms (QLSAs) to substitute classical linear system solvers ...
Zeguan Wu, Xiu Yang, Tamás Terlaky
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An inexact infeasible arc-search interior-point method for linear optimization
28 pages, 3 ...
Iida, Einosuke, Yamashita, Makoto
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An infeasible Predictor-Corrector Interior Point Method Applied to Image Denoising
, 1997 Image recovery problems can be solved using optimization techniques. In this case, they often lead to the resolution of either a large scale quadratic program, or, equivalently, to a nondifferentiable minimization problem. Interior point methods are widely known for their efficiency in linear programming. Lately, they have been extended with success to
Pola, Cecilia, Sagastizábal, Claudia
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An infeasible-interior-point method for the \(P_\ast(k)\) -matrix LCP
Journal of Numerical Analysis and Approximation Theory, 1998 Not available.
Jun Ji, Florian A. Potra
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Integration of AR and deep learning-based image classification using CNN for construction project monitoring. [PDF]
Sci RepFan SL +6 more
europepmc +1 more source
Cycle-configuration descriptors: a novel graph-theoretic approach to enhancing molecular inference. [PDF]
J CheminformSong B +5 more
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