An Inexact Feasible Quantum Interior Point Method for Linearly Constrained Quadratic Optimization [PDF]
Entropy, 2023 Quantum linear system algorithms (QLSAs) have the potential to speed up algorithms that rely on solving linear systems. Interior point methods (IPMs) yield a fundamental family of polynomial-time algorithms for solving optimization problems. IPMs solve a
Zeguan Wu +4 more
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On the relationship of interior-point methods
International Journal of Mathematics and Mathematical Sciences, 1993 In this paper, we show that the moving directions of the primal-affine scaling method (with logarithmic barrier function), the dual-affine scaling method (with logarithmic barrier function), and the primal-dual interior point method are merely the Newton
Ruey-Lin Sheu, Shu-Cherng Fang
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Adapting the interior point method for the solution of linear programs on high performance computers [PDF]
, 1991 In this paper we describe a unified algorithmic framework for the interior point method (IPM) of solving Linear Programs (LPs) which allows us to adapt it over a range of high performance computer architectures. We set out the reasons as to why IPM makes
Levkovitz, R +5 more
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Experimental investigations in combining primal dual interior point method and simplex based LP solvers [PDF]
, 1993 The use of a primal dual interior point method (PD) based optimizer as a robust linear programming (LP) solver is now well established. Instead of replacing the sparse simplex algorithm (SSX), the PD is increasingly seen as complementing it. The progress
Levkovitz, R +5 more
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Robust Interior Point Method for Quantum Key Distribution Rate Computation [PDF]
Quantum, 2022 Security proof methods for quantum key distribution, QKD, that are based on the numerical key rate calculation problem, are powerful in principle. However, the practicality of the methods are limited by computational resources and the efficiency and ...
Hao Hu +4 more
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Sparse Approximations with Interior Point Methods [PDF]
SIAM Review, 2022 Large-scale optimization problems that seek sparse solutions have become ubiquitous. They are routinely solved with various specialized first-order methods. Although such methods are often fast, they usually struggle with not-so-well conditioned problems.
Valentina De Simone +4 more
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Adapting the interior point method for the solution of LPs on serial, coarse grain parallel and massively parallel computers [PDF]
, 1990 In this paper we describe a unified scheme for implementing an interior point algorithm (IPM) over a range of computer architectures. In the inner iteration of the IPM a search direction is computed using Newton's method.
Levkovitz, R +3 more
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Efficient method to compute search directions of infeasible primal-dual path-following interior-point method for large scale block diagonal quadratic programming [PDF]
Songklanakarin Journal of Science and Technology (SJST), 2021 Quadratic programming is an important optimization problem that has applications in many areas such as finance, control, and management. Quadratic programs arisen in practice are often large but sparse, and they usually cannot be solved efficiently ...
Duangpen Jetpipattanapong +1 more
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Structure-Exploiting Interior Point Methods [PDF]
, 2020 Interior point methods are among the most popular techniques for large scale nonlinear optimization, owing to their intrinsic ability of scaling to arbitrary large problem sizes. Their efficiency has attracted in recent years a lot of attention due to increasing demand for large scale optimization in industry and engineering.
Jurai Kardos +2 more
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Ergodic Capacity Analysis of Downlink Communication Systems under Covariance Shaping Equalizers
Mathematics, 2022 Advances in higher-end spectrum utilization has enabled user equipment to dock multiple antenna elements, and hence make use of selectivity via equalization in new generation of mobile networks.
Ubaid M. Al-Saggaf +2 more
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