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Searching for Asymptotic Error Repair

by M. Vilares, V. M. Darriba, M. A. Alonso , 2003
"... We work in the domain of a regional least-cost strategy with dynamic validation in order to avoid cascaded errors [3], extending the theoretical model to illustrate its asymptotic equivalence with global repair algorithms. This is an objective criterion to measure the quality of an error repair ..."
Abstract - Cited by 1 (1 self) - Add to MetaCart
We work in the domain of a regional least-cost strategy with dynamic validation in order to avoid cascaded errors [3], extending the theoretical model to illustrate its asymptotic equivalence with global repair algorithms. This is an objective criterion to measure the quality of an error repair

Searching for Asymptotic Error Repair

by Vilares Darriba And, M. Vilares, V. M. Darriba, M. A. Alonso , 2002
"... We work in the domain of a regional least-cost strategy with dynamic validation in order to avoid cascaded errors [3], extending the theoretical model to illustrate its asymptotic equivalence with global repair algorithms. This is an objective criterion to measure the quality of an error repair ..."
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We work in the domain of a regional least-cost strategy with dynamic validation in order to avoid cascaded errors [3], extending the theoretical model to illustrate its asymptotic equivalence with global repair algorithms. This is an objective criterion to measure the quality of an error repair

Searching for asymptotic error repair?

by Manuel Vilares Ferro, See Profile, Victor Manuel, Darriba Bilbao, Miguel Ángel, Alonso Pardo, M. Vilares, V. M. Darriba, M. A. Alonso
"... All in-text references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately. ..."
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All in-text references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately.

Asymptotic error distributions for the Euler method for stochastic differential equations

by Jean Jacod, Philip Protter - THE ANNALS OF PROBABILITY , 1998
"... We are interested in the rate of convergence of the Euler scheme approximation of the solution to a stochastic differential equation driven by a general (possibly discontinuous) semimartingale, and by the asymptotic behavior of the associated normalized error. It is well known that for Itô’s equatio ..."
Abstract - Cited by 176 (13 self) - Add to MetaCart
We are interested in the rate of convergence of the Euler scheme approximation of the solution to a stochastic differential equation driven by a general (possibly discontinuous) semimartingale, and by the asymptotic behavior of the associated normalized error. It is well known that for Itô’s

Asymptotic error rates in quantum hypothesis testing

by K. M. R. Audenaert, M. Nussbaum, A. Szkoła, F. Verstraete - COMMUN. MATH. PHYS , 2008
"... We consider the problem of discriminating between two different states of a finite quantum system in the setting of large numbers of copies, and find a closed form expression for the asymptotic exponential rate at which the specified error probability tends to zero. This leads to the identification ..."
Abstract - Cited by 31 (7 self) - Add to MetaCart
We consider the problem of discriminating between two different states of a finite quantum system in the setting of large numbers of copies, and find a closed form expression for the asymptotic exponential rate at which the specified error probability tends to zero. This leads to the identification

On Discriminative vs. Generative classifiers: A comparison of logistic regression and naive Bayes

by Andrew Y. Ng, Michael I. Jordan , 2001
"... We compare discriminative and generative learning as typified by logistic regression and naive Bayes. We show, contrary to a widely held belief that discriminative classifiers are almost always to be preferred, that there can often be two distinct regimes of performance as the training set size is i ..."
Abstract - Cited by 520 (8 self) - Add to MetaCart
is increased, one in which each algorithm does better. This stems from the observation -- which is borne out in repeated experiments -- that while discriminative learning has lower asymptotic error, a generative classifier may also approach its (higher) asymptotic error much faster.

Asymptotic Error Analysis of the Adaptive Verlet Method

by Stéphane Cirilli, Ernst Hairer, Benedict Leimkuhler - BIT , 1998
"... The Adaptive Verlet method [7] and variants [1] are time-reversible schemes for treating Hamiltonian systems subject to a Sundman time transformation. These methods have been observed in computer experiments to exhibit superior numerical stability when implemented in a counterintuitive "recipro ..."
Abstract - Cited by 7 (5 self) - Add to MetaCart
;reciprocal" formulation. Here we give a theoretical explanation of this behavior by examining the leading terms of the modified equation (backward error analysis) and those of the asymptotic error expansion. With this insight we are able to improve the algorithm by simply correcting the starting stepsize. keywords

Quadrature Formulae And Asymptotic Error Expansions For Wavelet Approximations Of Smooth Functions

by Wim Sweldens, Robert Piessens - SIAM J. Numer. Anal , 1994
"... . This paper deals with typical problems that arise when using wavelets in numerical analysis applications. The first part involves the construction of quadrature formulae for the calculation of inner products of smooth functions and scaling functions. Several types of quadratures are discussed and ..."
Abstract - Cited by 51 (6 self) - Add to MetaCart
and compared for different classes of wavelets. Since their construction using monomials is ill-conditioned, also a modified, well-conditioned construction using Chebyshev polynomials is presented. The second part of the paper deals with pointwise asymptotic error expansions of wavelet approximations of smooth

On the sharpness of an asymptotic error estimate for Conjugate Gradients

by B. Beckermann, A. B. J. Kuijlaars - BIT , 2000
"... Recently, the authors obtained an upper bound on the error for the conjugate gradient method, which is valid in an asymptotic setting as the size of the linear systems tends to infinity. The estimate depends on the asymptotic distribution of eigenvalues, and the ratio between the size and the number ..."
Abstract - Cited by 6 (4 self) - Add to MetaCart
Recently, the authors obtained an upper bound on the error for the conjugate gradient method, which is valid in an asymptotic setting as the size of the linear systems tends to infinity. The estimate depends on the asymptotic distribution of eigenvalues, and the ratio between the size

Non-asymptotic Error Bounds for Sequential MCMC

by Nikolaus Schweizer - Methods in Multimodal Settings., in preparation
"... ar ..."
Abstract - Cited by 6 (0 self) - Add to MetaCart
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Results 1 - 10 of 5,925