This work presents a comprehensive second-order predictive modeling (PM) methodology designated by the acronym 2nd-BERRU-PMD. The attribute “2nd” indicates that this incorporates uncertainties (means and covariances) sensitivities of computed model responses to parameters. BERRU stands for “Best- Estimate Results with Reduced Uncertainties” last letter (“D”) in “deterministic,” referring determ...

This work presents a comprehensive second-order predictive modeling (PM) methodology based on the maximum entropy (MaxEnt) principle for obtaining best-estimate mean values and correlations model responses parameters. is designated by acronym 2nd-BERRU-PMP, where attribute “2nd” indicates that this incorporates second- order uncertainties (means covariances) second (and higher) sensitivities of...

This paper develops Bayesian inference in reliability of a class of scale mixtures of log-normal failure time (SMLNFT) models with stochastic (or uncertain) constraint in their reliability measures. The class is comprehensive and includes existing failure time (FT) models (such as log-normal, log-Cauchy, and log-logistic FT models) as well as new models that are robust in terms of heavy-tailed ...

Bee keeping is indispensable to global food production. It is an alternate income source, especially in rural underdeveloped African settlements, and an important forest conservation incentive. However, dwindling honeybee colonies around the world are attributed to pests and diseases whose spatial distribution and influences are not well established. In this study, we used remotely sensed data ...

This paper presents an approach for generating free paraphrases of compounds (task 4 at SemEval 2013) by decomposing the training data into a collection of templates and fillers and recombining/scoring these based on a generative language model and discriminative MaxEnt reranking. The system described in this paper achieved the highest score (with a very small margin) in the (default) isomorphi...

MaxEnt grammar is a probabilistic version of Harmonic Grammar in which the harmony scores candidates are mapped onto probabilities. It has become tool choice for analyzing phonological phenomena involving variation or gradient acceptability, but there competing proposal making probabilistic, Noisy Grammar, derived by adding random ‘noise’ to constraint weights. In this paper these frameworks, a...

Discovering and summarizing opinions from online reviews is an important and challenging task. A commonly-adopted framework generates structured review summaries with aspects and opinions. Recently topic models have been used to identify meaningful review aspects, but existing topic models do not identify aspect-specific opinion words. In this paper, we propose a MaxEnt-LDA hybrid model to join...

The Maximum Entropy maxent principle has been successfully applied in classi cation and tagging tasks Compared with other statistical learning method it allows convenient integration of di erent knowledge sources However it is restricted by the size of the training corpus in that not all knowledge can be incorporated For instance events observed with low counts can be either a particular patter...