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- Thomas Abeel, Thibault Helleputte, Yves Van de Peer, Pierre Dupont, Yvan Saeys
- Bioinformatics
- 2010

MOTIVATION
Biomarker discovery is an important topic in biomedical applications of computational biology, including applications such as gene and SNP selection from high-dimensional data. Surprisingly, the stability with respect to sampling variation or robustness of such selection processes has received attention only recently. However, robustness of… (More)

- Marco Saerens, François Fouss, Luh Yen, Pierre Dupont
- ECML
- 2004

This work presents a novel procedure for computing (1) distances between nodes of a weighted, undirected, graph, called the Euclidean Commute Time Distance (ECTD), and (2) a subspace projection of the nodes of the graph that preserves as much variance as possible, in terms of the ECTD – a principal components analysis of the graph. It is based on a… (More)

- Pierre Dupont
- ICGI
- 1996

In this paper, we extend the characterization of the search space of regular inference DMV94] to sequential presentations of learning data. We propose the RPNI2 algorithm, an incremental extension of the RPNI algorithm. We study the convergence and complexities of both algorithms from a theoretical and practical point of view. These results are assessed on… (More)

- Pierre Dupont, François Denis, Yann Esposito
- Pattern Recognition
- 2005

This article presents an overview of Probabilistic Automata (PA) and discrete Hidden Markov Models (HMMs), and aims at clarifying the links between them. The first part of this work concentrates on probability distributions generated by these models. Necessary and sufficient conditions for an automaton to define a probabilistic language are detailed. It is… (More)

- Franck Thollard, Pierre Dupont, Colin de la Higuera
- ICML
- 2000

- Pierre Dupont, Bernard Lambeau, Christophe Damas, Axel van Lamsweerde
- Applied Artificial Intelligence
- 2008

& This article presents a novel application of grammatical inference techniques to the synthesis of behavior models of software systems. This synthesis is used for the elicitation of software requirements. This problem is formulated as a deterministic finite-state automaton induction problem from positive and negative scenarios provided by an end user of… (More)

- Grégoire Dooms, Yves Deville, Pierre Dupont
- CP
- 2005

In an increasing number of domains such as bioinformatics, combinatorial graph problems arise. We propose a novel way to solve these problems, mainly those that can be translated to constrained subgraph finding. Our approach extends constraint programming by introducing CP(Graph), a new computation domain focused on graphs including a new type of variable:… (More)

- Christophe Damas, Bernard Lambeau, Pierre Dupont, Axel van Lamsweerde
- IEEE Transactions on Software Engineering
- 2005

Requirements-related scenarios capture typical examples of system behaviors through sequences of desired interactions between the software-to-be and its environment. Their concrete, narrative style of expression makes them very effective for eliciting software requirements and for validating behavior models. However, scenarios raise coverage problems as… (More)

- Pierre Dupont
- ICGI
- 1994

We recall brieey in this paper the formal theory of regular grammatical inference from positive and negative samples of the language to be learned. We state this problem as a search toward an optimal element in a boolean lattice built from the positive information. We explain how a genetic search technique may be applied to this problem and we introduce a… (More)

- Karoline Faust, Pierre Dupont, Jérôme Callut, Jacques van Helden
- Bioinformatics
- 2010

MOTIVATION
Subgraph extraction is a powerful technique to predict pathways from biological networks and a set of query items (e.g. genes, proteins, compounds, etc.). It can be applied to a variety of different data types, such as gene expression, protein levels, operons or phylogenetic profiles. In this article, we investigate different approaches to… (More)