Prototype-based Classifier for Automatic Diagnosis of Depressive Mood
International audience
International audience
In this paper, we study a nonconvex continuous relaxation of MAP inference in discrete Markov random fields (MRFs). We show that for arbitrary MRFs, this relaxation is tight, and a discrete stationary point of it can be easily reached by a simple block coordinate descent algorithm. In addition, we study the resolution of this relaxation using popul...
International audience
International audience
Published in PloS one
Rumour is an old social phenomenon used in politics and other public spaces. It has been studied for only hundred years by sociologists and psychologists by qualitative means. Social media platforms open new opportunities to improve quantitative analyses. We scanned all scientific literature to find relevant features. We made a quantitative screeni...
Published in IEEE/ACM transactions on computational biology and bioinformatics
Due to the rapid progress of biological networks for modeling biological systems, a lot of biomolecular networks have been producing more and more protein-protein interaction (PPI) data. Analyzing protein-protein interaction networks aims to find regions of topological and functional (dis)similarities between molecular networks of different species...
This paper empirically investigate the design of a fault detection mechanism based on Long Short Term Memory (LSTM) neural network. Given an equation based model that approximate the behavior of aircraft ailerons, the fault detector aims at predicting the state of aircraft: the normal state for which no failure are observed, or four different failu...
Ce mémoire d'habilitation présente une synthèse de mes réalisations académiques depuis la thèse de doctorat jusqu'à ma récente arrivée à l'IMT Atlantique de Brest. Après une année de post-doctorat en 2011 à l'Université de Technologie du Queensland (QUT, Australie), j'ai effectué la majorité de mes recherches entre 2011 et 2016 au laboratoire d'Ing...
A wide literature exists on constraint programming model linearization, based on integer domain decomposition. This paper considers the systematic study of classical global constraints, but in the context of mathematical variables. We consider constraints originally stated using integer domain variables, for which we investigate new definitions and...
Providing efficient black-box search procedures is one of the major concerns for constraint-programming solvers. Most of the contributions in that area follow the fail-first principle, which is very useful to close the search tree or to solve SAT/UNSAT problems. However, for real-life applications with an optimization criterion, proving optimality ...