Some di cult conceptual problems that have plagued Statistical Mechanics from the start, are explained by reference to a very simple experiment, which also explains why the MAXENT formalism gives reliable predictions. Then some of the inner workings of MAXENT are revealed by a general perturbation theorem, showing how a prediction is modi ed by adding a new constraint. It is illustrated by the ...

In the context of contemporary monophonic music, expression can be seen as the difference between a musical performance and its symbolic representation, i.e. a musical score. In this paper, we show how Maximum Entropy (MaxEnt) models can be used to generate musical expression in order to mimic a human performance. As a training corpus, we had a professional pianist play about 150 melodies of ja...

An increasing number of authors agree in that the maximum entropy principle (MaxEnt) is essential for the understanding of macroecological patterns. However, there are subtle but crucial differences among the approaches by several of these authors. This poses a major obstacle for anyone interested in applying the methodology of MaxEnt in this context. In a recent publication, Frank (2011) gives...

DSLRAE is a hierarchical classifier for similar written languages and varieties based on maximum-entropy (maxent) classifiers. In the first level, the text is classified into a language group using a simple token-based maxent classifier. At the second level, a group-specific maxent classifier is applied to classify the text as one of the languages or varieties within the previously identified g...

The following picture shows the test omission rate and predicted area as a function of the cumulative threshold, averaged over the replicate runs. The omission rate should be close to the predicted omission, because of the definition of the cumulative threshold. The next picture is the receiver operating characteristic (ROC) curve for the same data, again averaged over the replicate runs. Note ...

In this paper we pose the question: After gathering N data points, at what value of the control parameter should the next measurement be done? We propose an on-line algorithm which samples optimally by maximizing the gain in information on the parameters to be measured. We show analytically that the information gain is maximum for those potential measurements whose outcome is most unpredictable...

Wildfire ignition distributionmodels are powerful tools for predicting the probability of ignitions across broad areas, and identifying their drivers. Several approaches have been used for ignition-distribution modelling, yet the performance of different model types has not been compared. This is unfortunate, given that conceptually similar speciesdistributionmodels exhibit pronounced differenc...

Ecological niche modeling (ENM) algorithms, Maximum Entropy Species Distribution Modeling (Maxent) and Genetic Algorithm for Rule-set Prediction (GARP), were used to develop models in Iowa for three species of mosquito - two significant, extant West Nile virus (WNV) vectors (Culex pipiens L and Culex tarsalis Coquillett (Diptera: Culicidae)), and the nuisance mosquito, Aedes vexans Meigen (Dipt...

Maximum Entropy (MaxEnt) model has been proven to be a very effective approach in the topic classification task, where a specific topic from a pre-defined topic set will be assigned to each sentence. Although it is originally developed based on the motivation of maximizing the conditional probability entropy under certain constraints, MaxEnt model is indeed an exponential distribution model tha...