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11
Global Optimization of Statistical Functions with Simulated Annealing
 Journal of Econometrics
, 1994
"... Many statistical methods rely on numerical optimization to estimate a model’s parameters. Unfortunately, conventional algorithms sometimes fail. Even when they do converge, there is no assurance that they have found the global, rather than a local, optimum. We test a new optimization algorithm, simu ..."
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Cited by 126 (1 self)
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Many statistical methods rely on numerical optimization to estimate a model’s parameters. Unfortunately, conventional algorithms sometimes fail. Even when they do converge, there is no assurance that they have found the global, rather than a local, optimum. We test a new optimization algorithm, simulated annealing, on four econometric problems and compare it to three common conventional algorithms. Not only can simulated annealing find the global optimum, it is also less likely to fail on difficult functions because it is a very robust algorithm. The promise of simulated annealing is demonstrated on the four econometric problems.
CramérRao Bounds for 2D Target Shape Estimation in Nonlinear Inverse Scattering Problems with Application to Passive Radar
 IEEE Trans. on Antennas and Propagat
, 2001
"... We present new methods for computing fundamental performance limits for twodimensional (2D) parametric shape estimation in nonlinear inverse scattering problems with an application to passive radar imaging. We evaluate CramrRao lower bounds (CRB) on shape estimation accuracy using the domain der ..."
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Cited by 7 (3 self)
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We present new methods for computing fundamental performance limits for twodimensional (2D) parametric shape estimation in nonlinear inverse scattering problems with an application to passive radar imaging. We evaluate CramrRao lower bounds (CRB) on shape estimation accuracy using the domain derivative technique from nonlinear inverse scattering theory. The CRB provides an unbeatable performance limit for any unbiased estimator, and under fairly mild regularity conditions is asymptotically achieved by the maximum likelihood estimator (MLE). The resultant CRBs are used to define an asymptotic global confidence region, centered around the true boundary, in which the boundary estimate lies with a prescribed probability. These global confidence regions conveniently display the uncertainty in various geometric parameters such as shape, size, orientation, and position of the estimated target and facilitate geometric inferences. Numerical simulations are performed using the layer approach and the Nystrm method for computation of domain derivatives and using Fourier descriptors for target shape parameterization. This analysis demonstrates the accuracy and generality of the proposed methods. Index TermsCramrRao bounds, Fourier descriptors, global confidence regions, nonlinear inverse scattering, passive radar imaging, shape estimation. I.
Transparent Anonymization: Thwarting Adversaries Who Know the Algorithm
, 2010
"... Numerous generalization techniques have been proposed for privacypreserving data publishing. Most existing techniques, however, implicitly assume that the adversary knows little about the anonymization algorithm adopted by the data publisher. Consequently, they cannot guard against privacy attacks ..."
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Cited by 7 (0 self)
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Numerous generalization techniques have been proposed for privacypreserving data publishing. Most existing techniques, however, implicitly assume that the adversary knows little about the anonymization algorithm adopted by the data publisher. Consequently, they cannot guard against privacy attacks that exploit various characteristics of the anonymization mechanism. This article provides a practical solution to this problem. First, we propose an analytical model for evaluating disclosure risks, when an adversary knows everything in the anonymization process, except the sensitive values. Based on this model, we develop a privacy principle, transparent ldiversity,which ensures privacy protection against such powerful adversaries. We identify three algorithms that achieve transparent ldiversity, and verify their effectiveness and efficiency through extensive experiments with real data.
Input Feature Extraction for Multilayered Perceptrons Using Supervised Principal Component Analysis
"... : A method is proposed for constructing salient features from a set of features that are given as input to a feedforward neural network used for supervised learning. Combinations of the original features are formed that maximize the sensitivity of the network's outputs with respect to variations of ..."
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Cited by 1 (0 self)
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: A method is proposed for constructing salient features from a set of features that are given as input to a feedforward neural network used for supervised learning. Combinations of the original features are formed that maximize the sensitivity of the network's outputs with respect to variations of its inputs. The method exhibits some similarity to Principal Component Analysis, but also takes into account supervised character of the learning task. It is applied to classification problems leading to improved generalization ability originating from the alleviation of the curse of dimensionality problem. This paper has not been submitted elsewhere in identical or similar form, nor will it be during the first three months after its submission to Neural Processing Letters. 1 Input Feature Extraction for Multilayered Perceptrons Using Supervised Principal Component Analysis Key words: feature extraction, feature selection, multilayered perceptron, principal components, saliency Abstra...
Statistical Reconstruction of Qutrits
, 2003
"... The procedure of measurement followed by the reproduction of the quantum state of a threelevel optical system is implemented for a frequency and spatially degenerate twophoton field. The method of statistical estimation of the quantum state from a solution of the likelihood equation and the analys ..."
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The procedure of measurement followed by the reproduction of the quantum state of a threelevel optical system is implemented for a frequency and spatially degenerate twophoton field. The method of statistical estimation of the quantum state from a solution of the likelihood equation and the analysis of the statistical properties of the obtained estimates is developed. Using the root approach of estimating quantum states, the initial twophoton (qutrit) wave function is reproduced from the measured fourthorder field moments. The developed approach applied to quantum states reconstruction is based on considering amplitudes of mutually complementing processes. Classical approach to statistical estimation that is based on Fisher information matrix is generalized for the case of quantum systems obeying the Bohr’s complementary principle. The condition for a statistical completeness of a set of measurements is derived and a method of statistical fluctuations estimation is developed. Quasi Bayesian approach to density matrix reconstruction of mixed states is considered. The developed tools are applied to the analysis of real and numerical experiments with biphoton field. It has been experimentally proven that qutrit quantum states can be reconstructed with the fidelity of 0.9950.9998. A comparison of the reconstruction results with the fundamental statistical level of accuracy can serve as a basis for some problems such as the setup adjustment, operation stability control, revelation of foreign interference in the quantum system, etc.
RESEARCH Model Parameters and Outbreak Control for SARS
"... with movement of SARS patients between hospitals contributing to the disease's initial spread (5). In Taiwan, 94% of SARS cases occurred through transmission in hospital wards (6), and similar effects occurred in Hong Kong and Singapore (7). Although the SARS epidemic was eventually controlled, the ..."
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with movement of SARS patients between hospitals contributing to the disease's initial spread (5). In Taiwan, 94% of SARS cases occurred through transmission in hospital wards (6), and similar effects occurred in Hong Kong and Singapore (7). Although the SARS epidemic was eventually controlled, the measures used to achieve that control varied greatly in scope from one place to another. Control of an outbreak relies partly on identifying what disease parameters are likely to lead to a reduction in the reproduction number R 0 . Here we calculate the dependence of R 0 on model parameters. Methods Two models of the SARS epidemic that incorporate the effects of quarantine and early detection of new cases but assume perfect isolation were recently introduced (8,9). A slightly different model was used to quantify the role that fast diagnosis and efficient isolation of patients played in Toronto's outbreak (10). This model predicted control in Toronto and showed that lack of immediate actio
MeanGini Analysis of Stochastic Externalities: The Case of Groundwater Contamination a
"... Abstract. The meanGini approach is used to analyze stochastic externalities generated by agricultural production. The model addresses the problem of groundwater pollution caused by excessive fertilizer application. Inherent in the meanGini approach to expected utility maximization is a twofold va ..."
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Abstract. The meanGini approach is used to analyze stochastic externalities generated by agricultural production. The model addresses the problem of groundwater pollution caused by excessive fertilizer application. Inherent in the meanGini approach to expected utility maximization is a twofold value: the simplicity of the twoparameter meanvariance model and satisfaction of necessary and sufficient conditions for stochastic dominance. Price and quantity policy recommendations to control externalities are formulated based upon the relative assessment of uncertainty by the regulatory authority and the farmers. Using the Gini as a measure of risk allows for the quantification of control policy measures under differentiated risk aversion and multiple sources of pollution. The model shows that when producers underestimate uncertainty, quota policies restricting fertilizer are more efficient than tax policies in reducing groundwater contamination. Key words. Stochastic externalities, water pollution policies, stochastic dominance. 1.
© PHOTO F/X2 HIGH QUALITY ENDTOEND LINK PERFORMANCE Adaptive Distributed MIMO Multihop Networks with Optimized Resource Allocation
"... Recently, there has been an increasing interest in applying traditional pointtopoint multipleinput multipleoutput (MIMO) techniques to multihop wireless relaying networks to support higher endtoend (e2e) data rates and to provide a better user experience [1]–[5]. By the concept of virtual anten ..."
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Recently, there has been an increasing interest in applying traditional pointtopoint multipleinput multipleoutput (MIMO) techniques to multihop wireless relaying networks to support higher endtoend (e2e) data rates and to provide a better user experience [1]–[5]. By the concept of virtual antenna array (VAA), spatially separated relaying nodes can utilize the capacity improvements offered by MIMO transmission techniques. Digital Object Identifier 10.1109/MVT.2009.933472 For example, the application of distributed spacetime codes was proven in [5] to significantly improve the data rate in multihop networks. Figure 1 depicts a distributed MIMO multihop network, where one source communicates with one destination via a number of relaying VAAs in multiple hops. Spatially adjacent nodes in a VAA receive data from the previous VAA and relay the message to the consecutive VAA until the destination is reached. The general concept of distributed MIMO multihop communication systems has been analyzed in [4] and [5],
INVESTIGATION OF THE POTENTIAL EFFECTS OF UNDERWATER NOISE FROM PETROLEUM INDUSTRY ACTIVITIES ON FEEDING HUMPBACK WHALE BEHAVIOR
, 1985
"... Attn: Mr. Stephen D. TreacyThe opinions, findings, conclusions, or recommendations expressed in this report are those of the authors and do not necessarily reflect the views of the U.S. Department of the Interior, nor does mention of trade names or commercial products constitute endorsement or recom ..."
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Attn: Mr. Stephen D. TreacyThe opinions, findings, conclusions, or recommendations expressed in this report are those of the authors and do not necessarily reflect the views of the U.S. Department of the Interior, nor does mention of trade names or commercial products constitute endorsement or recommendation