Results 51 to 60 of about 1,105 (105)
On global optimization with indefinite quadratics
EURO Journal on Computational Optimization, 2017 We present an algorithmic framework for global optimization problems in which the non-convexity is manifested as an indefinite-quadratic as part of the objective function.
Marcia Fampa, Jon Lee, Wendel Melo
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Convergence of the Lasserre Hierarchy of SDP Relaxations for Convex Polynomial Programs without Compactness [PDF]
, 2013 The Lasserre hierarchy of semidefinite programming (SDP) relaxations is an effective scheme for finding computationally feasible SDP approximations of polynomial optimization over compact semi-algebraic sets.
Jeyakumar, V., Li, G., Pham, T. S.
core
A Support Based Algorithm for Optimization with Eigenvalue Constraints [PDF]
, 2013 Optimization of convex functions subject to eigenvalue constraints is intriguing because of peculiar analytical properties of eigenvalues, and is of practical interest because of wide range of applications in fields such as structural design and control ...
Mengi, Emre
core
Performance Bounds For Co-/Sparse Box Constrained Signal Recovery
Analele Stiintifice ale Universitatii Ovidius Constanta: Seria Matematica, 2019 The recovery of structured signals from a few linear measurements is a central point in both compressed sensing (CS) and discrete tomography. In CS the signal structure is described by means of a low complexity model e.g. co-/sparsity.
Kuske Jan, Petra Stefania
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Geometric approaches to matrix normalization and graph balancing
Forum of Mathematics, SigmaNormal matrices, or matrices which commute with their adjoints, are of fundamental importance in pure and applied mathematics. In this paper, we study a natural functional on the space of square complex matrices whose global minimizers are normal ...
Tom Needham, Clayton Shonkwiler
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Tikhonov regularization of a second order dynamical system with Hessian driven damping. [PDF]
Math Program, 2021 Boţ RI, Csetnek ER, László SC.
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Journal of Inequalities and Applications, 2011 In this paper, an efficient modified nonlinear conjugate gradient method for solving unconstrained optimization problems is proposed. An attractive property of the modified method is that the generated direction in each step is always descending without ...
Liu Jinkui, Wang Shaoheng
doaj
Consensus-based optimisation with truncated noise
European Journal of Applied MathematicsConsensus-based optimisation (CBO) is a versatile multi-particle metaheuristic optimisation method suitable for performing non-convex and non-smooth global optimisations in high dimensions.
Massimo Fornasier +3 more
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A second-order dynamical approach with variable damping to nonconvex smooth minimization. [PDF]
Appl Anal, 2020 Boţ RI, Csetnek ER, László SC.
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ORTHOGONAL TRACE-SUM MAXIMIZATION: APPLICATIONS, LOCAL ALGORITHMS, AND GLOBAL OPTIMALITY. [PDF]
SIAM J Matrix Anal Appl, 2021 Won JH, Zhou H, Lange K.
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