Results 11 to 20 of about 116,336 (250)
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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Interior point methods in the year 2025
EURO Journal on Computational OptimizationInterior point methods (IPMs) have hugely influenced the field of optimization. Their fast development has been triggered by the seminal paper of Narendra Karmarkar published in 1984 which delivered a polynomial algorithm for linear programming and ...
Jacek Gondzio
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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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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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An Interior-Point Method for Semidefinite Programming [PDF]
SIAM Journal on Optimization, 1996 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Christoph Helmberg +3 more
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The Symbolic Interior Point Method
Proceedings of the AAAI Conference on Artificial Intelligence, 2017 Numerical optimization is arguably the most prominent computational framework in machine learning and AI. It can be seen as an assembly language for hard combinatorial problems ranging from classification and regression in learning, to computing optimal policies and equilibria in decision theory, to entropy minimization in information ...
Mladenov, Martin +2 more
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A new search direction for full-Newton step infeasible interior-point method in linear optimization
Croatian Operational Research Review, 2023 In this work, we investigate a full Newton step infeasible interior-point method for linear optimization based on a new search direction which is obtained from an algebraic equivalent transformation of the central path system.
Behrouz Kheirfam
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Radio frequency interference suppression filters design for HF radar based on SOCP
The Journal of Engineering, 2019 High-frequency radar is easily affected by radio frequency interference (RFI) since it shares the band with many radio services. To mitigate the RFIs, this study designs receiver for radar's fast-time processing.
Zhaoyi Wang +4 more
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A Full-NT Step Infeasible Interior-Point Algorithm for Mixed Symmetric Cone LCPs [PDF]
Sahand Communications in Mathematical Analysis, 2019 An infeasible interior-point algorithm for mixed symmetric cone linear complementarity problems is proposed. Using the machinery of Euclidean Jordan algebras and Nesterov-Todd search direction, the convergence analysis of the algorithm is shown and ...
Ali Nakhaei Amroudi +2 more
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Optimal Correction of Infeasible Systems in the Second Order Conic Linear Setting [PDF]
Computer Science Journal of Moldova, 2011 In this paper we consider correcting infeasibility in a second order conic linear inequality by minimal changes in the problem data. Under certain conditions, it is proved that the minimal correction can be done by solving a lower dimensional convex ...
Maziar Salahi
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