Results 211 to 220 of about 4,708 (226)
Some of the next articles are maybe not open access.
Pattern Recognition, 2021
Abstract Similar to binary and multi-class classifiers, one-class classifiers have to face the difficulty of ’curse of dimensionality’ when they are applied to deal with high-dimensional samples. As an efficient dimensionality reduction method, sparse coding tries to learn a set of over-complete bases to represent the given samples.
Hong-Jie Xing
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Abstract Similar to binary and multi-class classifiers, one-class classifiers have to face the difficulty of ’curse of dimensionality’ when they are applied to deal with high-dimensional samples. As an efficient dimensionality reduction method, sparse coding tries to learn a set of over-complete bases to represent the given samples.
Hong-Jie Xing
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Exact Penalty Function and Asymptotic Strong Nonlinear Duality in Integer Programming
In this paper, a logarithmic-exponential penalty function with two parameters for integer programming is discussed. We obtain the exact penalty properties and then establish the asymptotic strong nonlinear duality in the corresponding logarithmic ...
L S Zhang
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Logarithmic-exponential penalty formulation for integer programming
The purpose of this note is to present a smooth penalty formulation for integer programming. By adopting the proposed logarithmic-exponential penalty function, we are able to transform an inequality constrained integer programming problem into an ...
Li, D., Sun, X.L.
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A New Exact Penalty Function Approach to Semi-infinite Programming Problem
In this paper, we propose a new exact penalty function method for solving a class of semi-infinite programming problems (SIPs). We introduce a logarithmic form function of the constraint violation, where the constraint violation is a measure of the ...
Changjun Yu +2 more
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A penalty method for nonparametric estimation of the logarithmic derivative of a density function
Annals of the Institute of Statistical Mathematics, 1985This paper deals with the estimation of the function \(\psi_ 0=-f'\!_ 0/f_ 0\) from independent random variables \(X_ 1,...,X_ n\) with common unknown density \(f_ 0\) and cumulative distribution function \(F_ 0\). From the remark that, under mild conditions, \(\psi_ 0\) is the unique minimizer of \(\int [\psi^ 2-2\psi ']dF_ 0\) the author proposes as ...
openaire +2 more sources
Using logarithmic penalties in the shooting algorithm for optimal control problems
Optimal Control Applications and Methods, 2003J F Bonnans
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On Logarithmic Penalty in Adaptive Pointwise Estimation and Blockwise Wavelet Shrinkage
Journal of Computational and Graphical Statistics, 2005Sam Efromovich
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