In many environmental management problems, the construction of occurrence maps of
species of interest is a prerequisite to their effective management. However, the construction …

Motivation This work addresses two common issues in building classification models for
biological or medical studies: learning a sparse model, where only a subset of a large …

Biological networks are a very convenient modeling and visualization tool to discover
knowledge from modern high-throughput genomics and post-genomics data sets. Indeed …

Most clustering and classification methods are based on the assumption that the objects to
be clustered are independent. However, in more and more modern applications, data are …

Among classical methods for module detection, SpaCEM3 provides ad hoc algorithms that
were shown to be particularly well adapted to specific features of biological data: high …

We present recent approaches that extend standard Markov models and increase their
modelling power. These capabilities are illustrated in the cited published works and more …

Este documento presenta una revisión general de las diferentes aproximaciones y métodos
en inferencia estadística, aplicados al problema de entrenamiento o ajuste de parámetros …

Résumé Le logiciel SpaCEM 3 (Spatial Clustering with EM and Markov Models) propose
une variété d'algorithmes pour la classification, supervisée ou non supervisée, de données …

본 논문에서는 색조영상의 R-, G-, B-성분에서 랜덤결측된 화소값들의 대체를 위한
프리퀀티스틱 (frequentictic) 기법을 제공한다. 이 기법은 관측영상을 가우시안 마코프 랜덤필드 …

The SpaCEM3 software makes the most of variational estimates in Markov Random Field
(MRF) models to cluster (i) high-dimensional (ii) dependent and (iii) incomplete data. This …