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214 results — page 4 of 11

This work reviews blackbox optimization applications over the last twenty years, addressed using direct search optimization methods. Emphasis is placed on...

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The design of key nonlinear systems often requires the use of expensive blackbox simulations presenting inherent discontinuities whose positions in the varia...

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We consider the iterative solution of regularized saddle-point systems. When the leading block is symmetric and positive semi-definite on an appropriate sub...

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We provide eigenvalues bounds for a new formulation of the step equations in interior methods for convex quadratic optimization. The matrix of our formulati...

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In derivative-free and blackbox optimization, the objective function is often evaluated through the execution of a computer program seen as a blackbox. It ...

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A highly influential ingredient of many techniques designed to exploit sparsity in numerical optimization is the so-called chordal extension of a graph repre...

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We introduce an iterative method named BiLQ for solving general square linear systems \(Ax=b\) based on the Lanczos biorthogonalization process defined by ...

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In this paper, we compare the BFGS and the conjugate gradient (CG) methods for solving unconstrained problems with a trust-region algorithm. The main result ...

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Statistical image reconstruction in X-Ray computed tomography yields large-scale regularized linear least-squares problems with nonnegativity bounds, where t...

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Reducing the number of features used in data classification can remove noisy or redundant features, reduce the cost of data collection, and improve the accur...

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We build upon Estrin et al. (2019) to develop a general constrained nonlinear optimization algorithm based on a smooth penalty function proposed by Fletch...

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The minimum residual method (MINRES) of Paige and Saunders (1975), which is often the method of choice for symmetric linear systems, is a generalization of t...

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We propose an iterative method named USYMLQR for the solution of symmetric saddle-point systems that exploits the orthogonal tridiagonalization method of Sa...

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We propose a regularization method for nonlinear least-squares problems with equality constraints. Our approach is modeled after those of Arreckx and Orban ...

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The present work is in a context of derivative-free optimization involving direct search algorithms guided by surrogate models of the original problem. The...

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In the interest of full disclosure, the reader is advised that I am biased positively towards the book considered here as I have collaborated with its first ...

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We develop a general equality-constrained nonlinear optimization algorithm based on a smooth penalty function proposed by Fletcher (1970). Although it was ...

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Algorithms for finding sparse solutions of underdetermined systems of linear equations have been the subject of intense interest in recent years, sparked b...

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We describe LNLQ for solving the least-norm problem \(\min\ \|x\|\) subject to \(Ax=b\). Craig's method is known to be equivalent to applying the conjug...

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