We show that, to generate the statistical operator appropriate for a given system, and as an alternative to Jaynes’ MaxEnt approach, that refers to the entropy S, one can use instead the increments δS in S. To such an effect, one uses the macroscopic thermodynamic relation that links δS to changes in i) the internal energy E and ii) the remaining M relevant extensive quantities Ai, i = 1, . . ....

This study addresses the problem of automatically detecting decisions in conversational speech. We formulate the problem as classifying decision-making units at two levels of granularity: dialogue acts and topic segments. We conduct an empirical analysis to determine the characteristic features of decision-making dialogue acts, and train MaxEnt models using these features for the classification...

We represent knowledge by using probability distributions of mixed continuous and discrete variables. In the case of complete knowledge of the joint distribution of all items, one can compute arbitrary conditional distributions, which may be used for prediction. However, in many cases only some marginal distributions, inverse probabilities, or moments are known. Under these conditions, a princi...

of the PhD thesis

In this work, we make an exhaustive study of the properties of the Green’s function related to the periodic boundary value problem Lax ≡ x′′ + a(t) x = 0, x(0) = x(T ), x′(0) = x′(T ), with a sign-changing potential a(t). Moreover, we obtain new explicit criteria that ensures that the maximum or anti-maximum principle holds for this equation. The given criteria complement previous results in th...

For each transition probability, MEMM uses maximum entropy model. Maximum entropy model is used to model the data distribution, which gives us as much information as possible. Without any constraints, the uniform distribution gives us maximum entropy. However, we have training data which gives some facts about the true distribution. What maximum entropy model does is to maximize the entropy of ...

Based on the Markov model and the basic theory of information entropy, this paper puts forward a new method for optimizing the location of observation points in order to obtain more information from limited geological investigation. According to the existing data from observation points data, classification of tunnel geological lithology was performed, and various lithology distribution were de...

One of the key problems in non-parametric data analysis is to create a good model of a generating probability distribution, assuming we are given as data a finite sample from that distribution. Obviously this problem is ill-posed for continuous distributions: with finite data, there is no way to distinguish between (or exclude) distributions that are not restricted to be smooth. The question th...

Text mining is variance of a field called data mining. To make unstructured data workable by the computer Text mining is used which is also referred as “Text Analytics”. Text categorization, also called as topic spotting is the task of automatically classifies a set of documents into groups from a predefined set. Text classification is an essential application and research topic because of incr...

with μ = b, one notices that the coupling for μ > 0 is noncooperative such that indeed, see [14], the standard maximum principle cannot be used. Nevertheless, by the results in [14] one is able to estimate the value bc(Ω) from below by using the so called 3G-Theorem from [3] which can be rephrased as a positivity preserving property for the auxiliary system:    −∆u = f − λ v in Ω, −∆v = f in...