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...

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...

A single-step, self-contained method for determining the crystallite-size distribution and shape from experimental x-ray line profile data is presented. It is shown that the crystallite-size distribution can be determined without invoking a functional form for the size distribution, determining instead the size distribution with the least assumptions by applying the Bayesian/MaxEnt method. The ...

Chomsky and Halle (1968) propose an Evaluation Procedure that prefers featurally simple rules and grammars, and Bach and Harms (1972) propose that this bias for structural simplicity can explain instances of historical change in terms of rule simplication in learning. In this talk, I discuss an alternative model of structural bias (Pater and Moreton 2012) cast in a Maximum Entropy framework (Go...

Understanding the dynamics of neural networks is a major challenge in experimental neuroscience. For that purpose, a modelling of the recorded activity that reproduces the main statistics of the data is required. In a first part, we present a review on recent results dealing with spike train statistics analysis using maximum entropy models (MaxEnt). Most of these studies have been focusing on m...

To describe uncertainty of experts’ statements E1, ..., En that form a knowledge base, it is natural to use (subjective) probabilities pi. Correspondingly, it is natural to use probabilities to describe uncertainty of the system’s answer to a given query Q. Since it is impossible to inquire about the expert’s probabilities for all possible (≥ 2) propositional combinations of Ei, a knowledge bas...

In this paper, we present a reordering model based on Maximum Entropy. This model is extended from a hierarchical reordering model with PBSMT (Galley and Manning, 2008), which integrates syntactic information directly in decoder as features of MaxEnt model. The advantages of this model are (1) maintaining the strength of phrase based approach with a hierarchical reordering model, (2) many kinds...

This paper presents a model for disfluency detection in spontaneous speech transcripts called LSTM Noisy Channel Model. The model uses a Noisy Channel Model (NCM) to generate n-best candidate disfluency analyses and a Long Short-Term Memory (LSTM) language model to score the underlying fluent sentences of each analysis. The LSTM language model scores, along with other features, are used in a Ma...

Contextualización: El cambio climático y las actividades antrópicas sobre los recursos naturales se constituyen como principales causantes de la pérdida biodiversidad redistribución especies. Vacío conocimiento: Sin embargo, efectos a nivel comunidades ecosistemas, así impactos en cultivos agrícolas escala regional, son poco estudiados. Los modelos distribución especies han convertido, por lo t...