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We present an evolutionary algorithm that evolves a population of local approximators in order to fit an unknown function. The evolutionary algorithm performs a simultaneous learning of simple local approximators togethe...

Approximation algorithms for a class of planar graph problems, including planar independent set, planar vertex cover and planar dominating set, were intensively studied. The current upper bound on the running time of the...

This clearly written , mathematically rigorous text includes a novel algorithmic exposition of the simplex method and also discusses the Soviet ellipsoid algorithm for linear programming; efficient algorithms for network...

Models for the processes by which ideas and influence propagate through a social network have been studied in a number of domains, including the diffusion of medical and technological innovations, the sudden and widespre...

Protein Folding is an important open problem in the eld of Computational Biology Due to its com binatorial nature exact polynomial algorithms to solve it could not exist and so approximation algorithms and heurist...

Many tasks in computer vision involve assigning a label (such as disparity) to every pixel. A common constraint is that the labels should vary smoothly almost everywhere while preserving sharp discontinuities that may ex...

Hybrid dynamic spatial approximation trees are recently proposed data structures for searching in metric spaces, based on combining the concepts of spatial approximation and pivot based algorithms. These data structures ...

Independent component analysis (ICA) is a statistical method for transforming an observed multidimensional random vector into components that are statistically as independent from each other as possible. In this paper, w...

Function estimation/approximation is viewed from the perspective of numerical optimization in function space, rather than parameter space. A connection is made between stagewise additive expansions and steepest-descent m...

Boundary extraction is an important procedure associated with recognition and interpretation tasks in digital image processing and computer vision. Most of the segmentation techniques are based on the detection of the lo...

Conventional operating systems, like Silicon Graphics' IRIX and IBM's AIX, adopt a single Memory Management algorithm. The choice of this algorithm is usually based on its good performance in relation to the set of progr...

Web Engines are a useful tool for searching information in the Web. But a great part of this information is non-textual and for that case a metric space is used. A metric space is a set where a notion of distance (call...

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...

In visualization applications, the data has been increasing its size at very big rates. Processing of the whole data in main memory becomes impossible due to size limitations. A way of dealing with this constraint is to ...

Fuzzy rule-based systems have proved to be a convenient tool for modeling complex systems. This is due to their capacity to capture their typical imprecision, which makes classical methods inefficient. At present, Fuzzy...

The main objective of this work is to establish a basis for comparing BDI agents with the optimality of decision theory models such as POMDPs. It is argued that a direct comparison is not possible due to the intractabili...

Boosting is one of the most important recent developments in classification methodology. Boosting works by sequentially applying a classification algorithm to reweighted versions of the training data and then taking a we...

Abstract In a 1935 paper and in his book Theory of Probability, Jeffreys developed a methodology for quantifying the evidence in favor of a scientific theory. The centerpiece was a number, now called the Bayes factor, wh...

The purpose of model selection algorithms such as All Subsets, Forward Selection and Backward Elimination is to choose a linear model on the basis of the same set of data to which the model will be applied. Typically we ...

From the Publisher: This is the revised and greatly expanded Second Edition of the hugely popular Numerical Recipes: The Art of Scientific Computing. The product of a unique collaboration among four leading scientists in...

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...

This paper proposes two parallel variants of an Estimation of Distribution Algorithm (EDA) that represents the probability distribution by means of a single connected graphical model based on a polytree structure. The ma...

In this article we consider the problem of computing approximations to the second derivatives of functions of n variables using finite differences. We show how to derive different formulas and how to comput the errors of...

In order to be able to perform multimedia searches (like sounds, videos, images, etc.) we have to use data strucures like the Spatial Approximation Tree (SAT). This structure is a nice example of a tree structure in whic...