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Error estimation and error bounds for neural networks

Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems, 2002
A method is proposed to estimate the standard error of predicted values in multilayer perceptron (MLP). It is based on likelihood theory. It holds for all feedforward networks, irrespective of the topology or the specific task at hand. In addition, the bounds on a neural network with perturbed weights and inputs is analytically derived.
Hualou Liang, Guiliang Dai
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Estimation of the GSSM calibration error

Applied Optics, 2016
The calibration of the tertiary mirror of the Thirty Meter Telescope, also known as the giant science steering mirror (GSSM), is a step of great significance during its testing process. Systematic, drift, and random errors constitute the major limitations to the accuracy of the calibration measurements.
Linchu, Han   +3 more
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Generalization error of ensemble estimators

Proceedings of International Conference on Neural Networks (ICNN'96), 2002
It has been empirically shown that a better estimate with less generalization error can be obtained by averaging outputs of multiple estimators. This paper presents an analytical result for the generalization error of ensemble estimators. First, we derive a general expression of the ensemble generalization error by using factors of interest (bias ...
Naonori Ueda, Ryohei Nakano
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The Error Estimates

2003
In this chapter we assume the spacetime K is foliated by a double null canonical foliation that satisfies the assumptions $$O \leqslant \epsilon_0 ,\,D \leqslant \epsilon_0 ,$$ (6.0.1) and we make use of the inequality proved in Theorem M7 $$R \leqslant cQ_K^{\frac{1} {2}} .$$ (6.0.2)
Sergiu Klainerman, Francesco Nicolò
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Bounds and error estimates for radiosity

Proceedings of the 21st annual conference on Computer graphics and interactive techniques - SIGGRAPH '94, 1994
We present a method for determining a posteriori bounds and estimates for local and total errors in radiosity solutions. The ability to obtain bounds and estimates for the total error is crucial fro reliably judging the acceptability of a solution. Realistic estimates of the local error improve the efficiency of adaptive radiosity algorithms, such as ...
Dani Lischinski   +2 more
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Estimation of the Error

1998
In the conceptual idea described in Chapter 6.1, it was assumed that the mean of the sample would deviate from that of the population from which it was collected. This therefore raises the question of how “precisely” does the mean value of the sample reflect that of the population. In other words, how large is the uncertainty of the mean value, or what
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On Weak Residual Error Estimation

SIAM Journal on Scientific Computing, 1996
The author develops a general framework for weak residual error estimators applied to various types of boundary value problems in connection with finite element and finite volume approximations. The paper illustrates basic ideas commonly shared by various applications in error estimation and adaptive computation. Some numerical results are given.
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Local error estimates in quadrature

BIT, 1991
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
ROMANI, FRANCESCO, Favati P, Lotti G.
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Error estimation and control for ODEs

Journal of Scientific Computing, 2005
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Microstructural Decomposition Error Estimates

ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik, 1999
AbstractComputational simulations of interacting microstructure in solid structures, with methods such as the finite element method, require solutions to numerically enormous boundary value problems. The primary objective of this work is to introduce a‐posteriori error bounds for a domain decomposition which can be used to reduce the computational ...
Zohdi, T., Wriggers, P.
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