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The approximation power of moving leastsquares
 Math. Comp
, 1998
"... Abstract. A general method for nearbest approximations to functionals on Rd, using scattereddata information is discussed. The method is actually the moving leastsquares method, presented by the BackusGilbert approach. It is shown that the method works very well for interpolation, smoothing and ..."
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Cited by 159 (7 self)
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Abstract. A general method for nearbest approximations to functionals on Rd, using scattereddata information is discussed. The method is actually the moving leastsquares method, presented by the BackusGilbert approach. It is shown that the method works very well for interpolation, smoothing
On the Approximation Power of Bivariate Splines
 Advances in Comp. Math. 9
, 1996
"... . We show how to construct stable quasiinterpolation schemes in the bivariate spline spaces S r d (4) with d 3r+2 which achieve optimal approximation order. In addition to treating the usual max norm, we also give results in the Lp norms, and show that the methods also approximate derivatives to ..."
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Cited by 59 (36 self)
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. We show how to construct stable quasiinterpolation schemes in the bivariate spline spaces S r d (4) with d 3r+2 which achieve optimal approximation order. In addition to treating the usual max norm, we also give results in the Lp norms, and show that the methods also approximate derivatives
Approximating Power Indices
"... Many multiagent domains where cooperation among agents is crucial to achieving a common goal can be modeled as coalitional games. However, in many of these domains, agents are unequal in their power to affect the outcome of the game. Prior research on weighted voting games has explored power indices ..."
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Cited by 22 (8 self)
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indices, which reflect how much “real power ” a voter has. Although primarily used for voting games, these indices can be applied to any simple coalitional game. Computing these indices is known to be computationally hard in various domains, so one must sometimes resort to approximate methods
Quasiinterpolants And Approximation Power Of Multivariate Splines
, 1990
"... The determination of the approximation power of spaces of multivariate splines with the aid of quasiinterpolants is reviewed. In the process, a streamlined description of the existing quasiinterpolant theory is given. 1. Approximation power of splines I begin with a brief review of the approximation ..."
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Cited by 57 (6 self)
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The determination of the approximation power of spaces of multivariate splines with the aid of quasiinterpolants is reviewed. In the process, a streamlined description of the existing quasiinterpolant theory is given. 1. Approximation power of splines I begin with a brief review
The Approximation Power of Priority Algorithms
, 2006
"... Greedylike algorithms have been a popular approach in combinatorial optimization, due to their conceptual simplicity and amenability to analysis. Surprisingly, it was only recently that a formal framework for their study emerged. In particular, Borodin, Nielsen and Rackoff introduced the class of p ..."
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of priority algorithms as a model for abstracting the main properties of (deterministic) greedylike algorithms; they also showed limitations on the approximation power of such algorithms for various scheduling problems. In this thesis we extend and modify the priorityalgorithm framework so as to make
Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms
, 1998
"... This article reviews five approximate statistical tests for determining whether one learning algorithm outperforms another on a particular learning task. These tests are compared experimentally to determine their probability of incorrectly detecting a difference when no difference exists (type I err ..."
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Cited by 714 (8 self)
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This article reviews five approximate statistical tests for determining whether one learning algorithm outperforms another on a particular learning task. These tests are compared experimentally to determine their probability of incorrectly detecting a difference when no difference exists (type I
Asymptotic Approximation Power for Neural Networks
"... This paper studies the asymptotic approximation power of radial basis function neural networks in the sup norm. The methods used are constructive and based on discretization of approximate identities. The effect of the kernel on the approximation order is discussed. 1 Introduction The purpose of t ..."
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This paper studies the asymptotic approximation power of radial basis function neural networks in the sup norm. The methods used are constructive and based on discretization of approximate identities. The effect of the kernel on the approximation order is discussed. 1 Introduction The purpose
Volume of Fluid (VOF) Method for the Dynamics of Free Boundaries
, 1981
"... Several methods have been previously used to approximate free boundaries in finite difference numerical simulations. A simple, but powerful, method is described that is based on the concept of a fractional volume of fluid (VOF). This method is shown to be more flexible and efficient than other metho ..."
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Cited by 558 (2 self)
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Several methods have been previously used to approximate free boundaries in finite difference numerical simulations. A simple, but powerful, method is described that is based on the concept of a fractional volume of fluid (VOF). This method is shown to be more flexible and efficient than other
Improving generalization with active learning
 Machine Learning
, 1994
"... Abstract. Active learning differs from "learning from examples " in that the learning algorithm assumes at least some control over what part of the input domain it receives information about. In some situations, active learning is provably more powerful than learning from examples ..."
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Cited by 537 (1 self)
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Abstract. Active learning differs from "learning from examples " in that the learning algorithm assumes at least some control over what part of the input domain it receives information about. In some situations, active learning is provably more powerful than learning from examples
Valuing American options by simulation: A simple leastsquares approach
 Review of Financial Studies
, 2001
"... This article presents a simple yet powerful new approach for approximating the value of America11 options by simulation. The kcy to this approach is the use of least squares to estimate the conditional expected payoff to the optionholder from continuation. This makes this approach readily applicable ..."
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Cited by 504 (9 self)
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This article presents a simple yet powerful new approach for approximating the value of America11 options by simulation. The kcy to this approach is the use of least squares to estimate the conditional expected payoff to the optionholder from continuation. This makes this approach readily
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