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On some interrelations of generalized $q$-entropies and a generalized Fisher information, including a Cramér-Rao inequality
Cramér-Rao inequality generalizedq-entropy generalized Gaussians de Bruijn identity
2013/6/17
In this communication, we describe some interrelations between generalized $q$-entropies and a generalized version of Fisher information. In information theory, the de Bruijn identity links the Fisher...
Some results on a $χ$-divergence, an~extended~Fisher information and~generalized~Cramer-Rao inequalities
Some results $χ$-divergence an~extended~Fisher information generalized~Cramer-Rao inequalities
2013/6/17
We propose a modified $\chi^{\beta}$-divergence, give some of its properties, and show that this leads to the definition of a generalized Fisher information. We give generalized Cram\'er-Rao inequalit...
Meta Path-Based Collective Classification in Heterogeneous Information Networks
Heterogeneous information networks Meta path Collective classi
2013/6/17
Collective classification has been intensively studied due to its impact in many important applications, such as web mining, bioinformatics and citation analysis. Collective classification approaches ...
A General Family of Estimators for Estimating Population Mean in Systematic Sampling Using Auxiliary Information in the Presence of Missing Observations
Family of estimators Auxiliary information Mean square error Non-response Systematic sampling
2013/6/14
This paper proposes a general family of estimators for estimating the population mean in systematic sampling in the presence of non-response adapting the family of estimators proposed by Khoshnevisan ...
Relative Performance of Expected and Observed Fisher Information in Covariance Estimation for Maximum Likelihood Estimates
Relative Performance Expected and Observed Fisher Information Covariance Estimation Maximum Likelihood Estimates
2013/6/13
Maximum likelihood estimation is a popular method in statistical inference. As a way of assessing the accuracy of the maximum likelihood estimate (MLE), the calculation of the covariance matrix of the...
Efficiently Using Second Order Information in Large l1 Regularization Problems
Efficiently Using Second Order Information Large l1 Regularization Problems
2013/4/28
We propose a novel general algorithm LHAC that efficiently uses second-order information to train a class of large-scale l1-regularized problems. Our method executes cheap iterations while achieving f...
On confidence intervals in regression that utilize uncertain prior information about a vector parameter
Frequentist confidence interval Prior information Linear regression
2013/4/28
Consider a linear regression model with n-dimensional response vector, p-dimensional regression parameter beta and independent normally distributed errors. Suppose that the parameter of interest is th...
Monte Carlo Algorithms for the Partition Function and Information Rates of Two-Dimensional Channels
Two-dimensional channels constrained channels partition function Gibbs sampling importance sampling factor graphs sum-product message passing capacity information rate
2011/6/21
The paper proposes Monte Carlo algorithms for
the computation of the information rate of two-dimensional
source / channel models. The focus of the paper is on binary-input
channels with constraints...
How to use our talents based on Information Theory - or spending time wisely
talents based Information Theory time wisely
2010/10/19
We discuss the allocation of finite resources in the presence of a logarithmic diminishing return law, in analogy to some results from Information Theory. To exemplify the problem we assume that the ...