Statistical modeling of presence-only data has attracted much recent attention in the ecological literature, leading to a proliferation of methods, including the inhomogeneous Poisson process (IPP) model, maximum entropy (Maxent) modeling of species distributions and logistic regression models. Several recent articles have shown the close relationships between these methods. We explain why the ...

Species distribution models have great potential to efficiently guide management for threatened species, especially for those that are rare or cryptic. We used MaxEnt to develop a regional-scale model for the koala Phascolarctos cinereus at a resolution (250 m) that could be used to guide management. To ensure the model was fit for purpose, we placed emphasis on validating the model using indep...

In this paper, we establish an equivalence between two conceptually different methods of signal estimation under modeling uncertainty viz. set–theoretic estimation and maximum entropy (maxent) MAP estimation. The first method assumes constraints on the signal to be estimated, the second assumes constraints on a probability distribution for the signal. We provide broad conditions under which the...

Peru is one of the world’s leading exporters cocoa beans, which directly impacts household economy millions small farmers. Currently, expansion and modernization cocoa-growing area require zoning territory with suitable biophysical infrastructural conditions to facilitate optimizing productivity factors. Therefore, we analyzed land suitability for (Theobroma cacao L.) production on Peruvian mai...

Maximum entropy (MaxEnt) modeling is a popular choice for sequence analysis in applications such as natural language processing, where the sequences are embedded in discrete, tractably-sized spaces. We consider the problem of applying MaxEnt to distributions over paths in continuous spaces of high dimensionality— a problem for which inference is generally intractable. Our main contribution is t...

Sentence boundary detection in speech is important for enriching speech recognition output, making it easier for humans to read and downstream modules to process. In previous work, we have developed hidden Markov model (HMM) and maximum entropy (Maxent) classifiers that integrate textual and prosodic knowledge sources for detecting sentence boundaries. In this paper, we evaluate the use of a co...

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...