We propose a simple abstract formalisation of the act of observation, in which the system and the observer are assumed to be in a pure state and their interaction deterministically changes the states such that the outcome can be read from the state of the observer after the interaction. If the observer consistently realizes the outcome which maximizes the likelihood ratio that the outcome perta...

background breast cancer (bc) is the most common cancer in iranian women. studying the mortality statistics is important to monitor the effects of screening programs or the influence of earlier diagnosis on the burden of this chronic disease. misclassification is still a problem in the iranian death registry data and about 20% of death statistics are recorded in misclassified categories. object...

Classification is a fundamental problem at the intersection of machine learning and statistics. Machine learning methods have enjoyed considerable empirical success. However, they often have an ad hoc quality. It is desirable to have hard theoretical results which might highlight specific quantitative advantages of these methods. The statistical methods often tackle the classification problem t...

This paper introduces two novel approaches for extracting compact grammars for hierarchical phrase-based translation. The first is a combinatorial optimization approach and the second is a Bayesian model over Hiero grammars using Variational Bayes for inference. In contrast to the conventional Hiero (Chiang, 2007) rule extraction algorithm , our methods extract compact models reducing model siz...

We consider the general problem of learning multi-category classification from labeled examples. We present experimental results for a nearest neighbor algorithm which actively selects samples from different pattern classes according to a querying rule instead of the a priori class probabilities. The amount of improvement of this query-based approach over the passive batch approach depends on t...

Hori (né Uemura) et al. formulated the fuzzy-Bayes decision rule extension of the Wald decision function to fuzzy ORand AND-connectives with multiple subjective distributions. This decision rule maps and transforms a state of nature to fuzzy events. In this context, the map of subjective distributions is called the subjective possibility distribution and the map of utility functions is called t...

In [4] we presented a new approach to data analysis based on flow distribution study in a flow network, called here a flow graph. The introduced flow graph differs from that proposed by Ford and Fulkerson [1], Branches of the flow graph are interpreted as decision rules, whereas the flow graph is supposed to describe a decision algorithm. Hence, we propose to model decision processes as flow gr...

A model of costly medical malpractice claims, based on Bayes Rule, is developed to examine the effects of physicians being liable for actual damage under a negligence rule. This model is consistent with empirical evidence concerning the pattern of claims. It is shown that compensating actual damage does not provide physicians with appropriate incentives to spend the second best optimal amount o...

If the selection of an adequate prior was the major conceptual and modeling challenge of Bayesian analysis, the major implementational challenge is computation. As soon as the model deviates from the conjugate structure, finding the posterior (first the marginal) distribution and the Bayes rule is all but simple. A closed form solution is more an exception than the rule, and even for such close...