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Abstract We generalize the method proposed by Gelman and Rubin (1992a) for monitoring the convergence of iterative simulations by comparing between and within variances of multiple chains, in order to obtain a family of ...

Materie / parole chiave: Differential evolution; Cuckoo search; Particle swarm optimization; Mathematical optimization; Evolutionary algorithm; Computer science; Algorithm; Mathematics

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1. The general discrete inverse problem 2. Monte Carol methods 3. The least-squares criterion 4. Least-absolute values criterion and minimax criterion 5. Functional inverse problems 6. Appendices 7. Problems References I...

In this article, we present a new LINear Constraint Solver (LINCS) for molecular simulations with bond constraints. The algorithm is inherently stable, as the constraints themselves are reset instead of derivatives of th...

A basic text in linear programming, the solution of systems of linear equalities. The subjects covered include the concepts, origins and formulations of linear programs, and the simplex method of solution as applied to t...

Summary We propose the elastic net, a new regularization and variable selection method. Real world data and a simulation study show that the elastic net often outperforms the lasso, while enjoying a similar sparsity of r...

Materie / parole chiave: Gradient boosting; Parameterized complexity; Mathematics; Robustness (evolution); Boosting (machine learning); Regression; Mathematical optimization; Algorithm; Data point; Computer science; Statistics; Artificial intell...

Abstract Assuming that numerical scores are available for the performance of each of n persons on each of n jobs, the “assignment problem” is the quest for an assignment of persons to jobs so that the sum of the n sc...

The k-means method is a widely used clustering technique that seeks to minimize the average squared distance between points in the same cluster. Although it offers no accuracy guarantees, its simplicity and speed are ver...

From the Publisher: This book brings together - in an informal and tutorial fashion - the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic al...

Materie / parole chiave: Interior point method; Algorithm; Line search; Karush–Kuhn–Tucker conditions; Nonlinear programming; Heuristics; Filter (signal processing); Mathematical optimization; Mathematics; Nonlinear system; Convergence (econ...

A new algorithm is presented for obtaining points on a steepest descent path from the transition state of the reactants and products. In mass-weighted coordinates, this path corresponds to the intrinsic reaction coordina...

Many problems of recent interest in statistics and machine learning can be posed in the framework of convex optimization. Due to the explosion in size and complexity of modern datasets, it is increasingly important to be...

FOUNDATIONS. The Scope of Integer and Combinatorial Optimization. Linear Programming. Graphs and Networks. Polyhedral Theory. Computational Complexity. Polynomial-Time Algorithms for Linear Programming. Integer Lattices....

Previous article Next article An Algorithm for Least-Squares Estimation of Nonlinear ParametersDonald W. MarquardtDonald W. Marquardthttps://doi.org/10.1137/0111030PDFPDF PLUSBibTexSections ToolsAdd to favoritesExport Ci...

Preface 1. Introduction. Problems to be considered Characteristics of 'real-world' problems Finite-precision arithmetic and measurement of error Exercises 2. Nonlinear Problems in One Variable. What is not possible Newto...

Recently, a number of researchers have investigated a class of graph partitioning algorithms that reduce the size of the graph by collapsing vertices and edges, partition the smaller graph, and then uncoarsen it to const...

Designing complex, dynamic yet multi-functional materials and devices is challenging because the design spaces for these materials have numerous interdependent and often conflicting constraints. Taking inspiration from a...

From the Publisher: The past decade has seen considerable theoretical and applied research on Markov decision processes, as well as the growing use of these models in ecology, economics, communications engineering, and o...

A nonlinear (nonconvex) programming model provides a new definition of efficiency for use in evaluating activities of not-for-profit entities participating in public programs. A scalar measure of the efficiency of each p...

The lasso is a popular technique for simultaneous estimation and variable selection. Lasso variable selection has been shown to be consistent under certain conditions. In this work we derive a necessary condition for the...

The particle swarm is an algorithm for finding optimal regions of complex search spaces through the interaction of individuals in a population of particles. This paper analyzes a particle's trajectory as it moves in disc...

Introduction and Preliminaries. Problems, Algorithms, and Complexity. LINEAR ALGEBRA. Linear Algebra and Complexity. LATTICES AND LINEAR DIOPHANTINE EQUATIONS. Theory of Lattices and Linear Diophantine Equations. Algorit...