We investigate properties of Bayesian networks (BNs) in the context of robust state estimation. We focus on problems where state estimation can be viewed as a classification of the possible states, which in turn is based on the fusion of heterogeneous and noisy information. We introduce a coarse perspective of the inference processes and show that classification with BNs can be very robust, eve...

Hyperspectral images can be represented either as a set of images or as a set of spectra. Spectral classification and segmentation and data reduction are the main problems in hyperspectral image analysis. In this paper we propose a Bayesian estimation approach with an appropriate hiearchical model with hidden markovian variables which gives the possibility to jointly do data reduction, spectral...

ayesian estimation is a framework for the formulation of statistical inference problems. In the prediction or estimation of a random process from a related observation signal, the Bayesian philosophy is based on combining the evidence contained in the signal with prior knowledge of the probability distribution of the process. Bayesian methodology includes the classical estimators such as maximu...

The Bayesian framework is a well-studied and successful framework for inductive reasoning, which includes hypothesis testing and confirmation, parameter estimation, sequence prediction, classification, and regression. But standard statistical guidelines for choosing the model class and prior are not always available or can fail, in particular in complex situations. Solomonoff completed the Baye...

Continuous time Bayesian network classifiers are designed for analyzing multivariate streaming data when time duration of events matters. New continuous time Bayesian network classifiers are introduced while their conditional log-likelihood scoring function is developed. A learning algorithm, combining conditional log-likelihood with Bayesian parameter estimation is developed. Classification ac...

          The aim of this paper is to simulate the effects of some macroeconomic policy tools on production and inflation of Iran by the current worldwide financial and real crisis. The theoretical framework of the analysis is based on the so-called ‘IMF/World Bank Integrated Model’ which is the synthesis (a merger) of the basic monetary approach of the Balance of Payments used at t...

Abstract. In the current conditions investment is an important basis for development of many levels economic system and can be considered as a driver country`s development. They are necessary to increase production rate, modernize complex, diversify economy. Assessment attractiveness means optimal achievement goals, which ensures performance function management mechanism. The individual country...

â â â  â â â â â  the aim of this paper is to simulate the effects of some macroeconomic policy tools on production and inflation of iran by the current worldwide financial and real crisis. the theoretical framework of the analysis is based on the so-called ‘imf/world bank integrated model’ which is the synthesis (a merger) of the basic monetary approach of the balance of payments used at t...

We applied PAC-Bayesian framework to derive generalization bounds for co-clustering. The analysis yielded regularization terms that were absent in the preceding formulations of this task. The bounds suggested that co-clustering should optimize a trade-off between its empirical performance and the mutual information that the cluster variables preserve on row and column indices. Proper regulariza...

abstract t he relationship between public sector deficits and inflation is one of the important and controversial issues in the academic literature as well as in economic policy field. on the other hand, a major objective of macroeconomic policies is to foster economic growth and to keep inflation on a low level. so keeping the price stability plays an important role in determining the growth r...