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6,347
Convergence Properties of the NelderMead Simplex Method in Low Dimensions
 SIAM Journal of Optimization
, 1998
"... Abstract. The Nelder–Mead simplex algorithm, first published in 1965, is an enormously popular direct search method for multidimensional unconstrained minimization. Despite its widespread use, essentially no theoretical results have been proved explicitly for the Nelder–Mead algorithm. This paper pr ..."
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Cited by 598 (3 self)
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methods, Nelder–Mead simplex methods, nonderivative optimization AMS subject classifications. 49D30, 65K05
Stochastic Perturbation Theory
, 1988
"... . In this paper classical matrix perturbation theory is approached from a probabilistic point of view. The perturbed quantity is approximated by a firstorder perturbation expansion, in which the perturbation is assumed to be random. This permits the computation of statistics estimating the variatio ..."
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Cited by 907 (36 self)
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and the eigenvalue problem. Key words. perturbation theory, random matrix, linear system, least squares, eigenvalue, eigenvector, invariant subspace, singular value AMS(MOS) subject classifications. 15A06, 15A12, 15A18, 15A52, 15A60 1. Introduction. Let A be a matrix and let F be a matrix valued function of A
(kurganov@math.tulane.edu). A WELLBALANCED RECONSTRUCTION FOR WETTING/DRYING FRONTS
"... Hyperbolic systems of conservation and balance laws, Saint–Venant system of shallow water equations, finite volume methods, well–balanced schemes. AMS subject classifications: ..."
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Hyperbolic systems of conservation and balance laws, Saint–Venant system of shallow water equations, finite volume methods, well–balanced schemes. AMS subject classifications:
Universal OneWay Hash Functions and their Cryptographic Applications
, 1989
"... We define a Universal OneWay Hash Function family, a new primitive which enables the compression of elements in the function domain. The main property of this primitive is that given an element x in the domain, it is computationally hard to find a different domain element which collides with x. We ..."
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Cited by 351 (15 self)
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schemes were based on the stronger mathematical assumption that trapdoor oneway functions exist. Key words. cryptography, randomized algorithms AMS subject classifications. 68M10, 68Q20, 68Q22, 68R05, 68R10 Part of this work was done while the authors were at the IBM Almaden Research Center. The first
On the Advantage of Well–Balanced Schemes for Moving–Water Equilibria of the Shallow Water Equations
"... Shallow water equation, still water, moving water equilibrium, high order accuracy, well balanced scheme. AMS subject classifications: 65M08, 35L45, 35L65, 76B15 ..."
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Cited by 6 (0 self)
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Shallow water equation, still water, moving water equilibrium, high order accuracy, well balanced scheme. AMS subject classifications: 65M08, 35L45, 35L65, 76B15
On Positive Harris Recurrence of Multiclass Queueing Networks: A Unified Approach Via Fluid Limit Models
 Annals of Applied Probability
, 1995
"... It is now known that the usual traffic condition (the nominal load being less than one at each station) is not sufficient for stability for a multiclass open queueing network. Although there has been some progress in establishing the stability conditions for a multiclass network, there is no unified ..."
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Cited by 357 (27 self)
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, multiclass feedforward networks and firstbufferfirstserved preemptive resume discipline in a reentrant line are positive Harris recurrent under the usual traffic condition. AMS 1991 subject classification: Primary 60K25, 90B22; Secondary 60K20, 90B35. Key words and phrases: multiclass queueing networks
Quantum Circuit Complexity
, 1993
"... We study a complexity model of quantum circuits analogous to the standard (acyclic) Boolean circuit model. It is shown that any function computable in polynomial time by a quantum Turing machine has a polynomialsize quantum circuit. This result also enables us to construct a universal quantum compu ..."
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Cited by 320 (1 self)
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that the majority function does not have a linearsize quantum formula. Keywords. Boolean circuit complexity, communication complexity, quantum communication complexity, quantum computation AMS subject classifications. 68Q05, 68Q15 1 This research was supported in part by the National Science Foundation under
ImplicitExplicit RungeKutta schemes and applications to hyperbolic systems with relaxation
 Journal of Scientific Computing
, 2000
"... We consider implicitexplicit (IMEX) Runge Kutta methods for hyperbolic systems of conservation laws with stiff relaxation terms. The explicit part is treated by a strongstabilitypreserving (SSP) scheme, and the implicit part is treated by an Lstable diagonally implicit Runge Kutta (DIRK). The sch ..."
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Cited by 83 (14 self)
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applications will be presented. Keywords: RungeKutta methods, hyperbolic systems with relaxation, stiff systems, high order shock capturing schemes. AMS Subject Classification: 65C20, 82D25 1
Weighted ENO Schemes for HamiltonJacobi Equations
 SIAM J. Sci. Comput
, 1997
"... In this paper, we present a weighted ENO (essentially nonoscillatory) scheme to approximate the viscosity solution of the HamiltonJacobi equation: OE t +H(x 1 ; \Delta \Delta \Delta ; x d ; t; OE; OE x1 ; \Delta \Delta \Delta ; OE xd ) = 0: This weighted ENO scheme is constructed upon and has the ..."
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Cited by 229 (0 self)
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words. ENO, weighted ENO, HamiltonJacobi equation, shape from shading, level set. AMS(MOS) subject classification. 35L99, 65M06. 1 Introduction The HamiltonJacobi equation: OE t +H(x; t; OE; DOE) = 0; OE(x; 0) = OE 0 (x) (1.1) 1 Research supported by ONR N0001492J1890. Email: gsj
Gabor Feature Based Classification Using the Enhanced Fisher Linear Discriminant Model for Face Recognition
 IEEE Trans. Image Processing
, 2002
"... This paper introduces a novel GaborFisher Classifier (GFC) for face recognition. The GFC method, which is robust to changes in illumination and facial expression, applies the Enhanced Fisher linear discriminant Model (EFM) to an augmented Gabor feature vector derived from the Gabor wavelet represen ..."
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Cited by 286 (10 self)
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for multiclass problems; and (iii) extensive performance evaluation studies. In particular, we performed comparative studies of different similarity measures applied to various classifiers. We also performed comparative experimental studies of various face recognition schemes, including our novel GFC
Results 1  10
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