Publications

    Machine learning and data mining

  1. B. Lambeau, C. Damas, P. Dupont, State-merging DFA Induction Algorithms with Mandatory Merge Constraints, Lecture Notes in Artificial Intelligence No. 5278, Springer, 9th International Colloquium on Grammatical Inference (ICGI), St Malo, France, September 22-24, pp. 139-153, 2008.

  2. J. Callut, K. Françoisse, M. Saerens and P. Dupont, Semi-supervised Classification from Discriminative Random Walks, Lecture Notes in Artificial Intelligence No. 5211, Springer, European Conference on Machine Learning (ECML PKDD, Part I), Antwerp, Belgium, September 15-19, pp. 162-177, 2008.

  3. J. Louahed, S. Gaulis, T. Helleputte, P. Dupont, O. Gruselle, A. Spatz, W. Kruit, B. Dréno, F. Lehmann, V. Brichard, Clinical response to the MAGE-3 immunotherapeutic in metastatic melanoma patients is associated with a specific gene profile present prior to treatment, European Society for Medical Oncology (ESMO) Congress, Stockholm, Sweden, Annals of Oncology, Vol. 19, pp. viii61-viii62, 2008.

  4. K. Faust, J. Callut, P. Dupont and J. van Helden, Metabolic Pathway Inference using Random Walks and Shortest-Paths Algorithms, Second International Workshop on Machine Learning in Systems Biology (MLSB), Brussels, September 13-14, pp. 27-38, 2008.

  5. J. Callut, K. Françoisse, M. Saerens and P. Dupont, Classification in Graphs using Discriminative Random Walks, 6th International Workshop on Mining and Learning with Graphs (MLG), Helsinki, Finland, July 4-5, 2008.

  6. J. Callut, K. Françoisse, M. Saerens and P. Dupont, Semi-supervised Classification in Graphs using Bounded Random Walks, 17th Annual Machine Learning Conference of Belgium and the Netherlands (Benelearn), Liège, Belgium, May 19-20, pp. 67-68, 2008.

  7. P. Dupont, B. Lambeau, C. Damas and A. van Lamsweerde, The QSM Algorithm and its Application to Software Behavior Model Induction, Applied Artificial Intelligence, Vol. 22, Issue 1, pp. 77-115, January 2008.

  8. K. Faust, P. Dupont, J. Callut and J. Van Helden, Inference of pathways from metabolic networks by subgraph extraction (Lecture), Benelux Bioinformatics Conference (BBC'07), November 12-13, Leuven, Belgium, 2007.

  9. T. Helleputte and P. Dupont, A comparative study of normalization and feature selection techniques for breast cancer prognosis from gene expressions (Poster) , Benelux Bioinformatics Conference (BBC'07), November 12-13, Leuven, Belgium, 2007.

  10. J. Callut and P. Dupont, Learning Partially Observable Markov Models from First Passage Times, Lecture Notes in Artificial Intelligence, No. 4701, Springer, European Conference on Machine Learning (ECML), Warsaw, Poland, pp. 91-103, 2007.

  11. P. Dupont, J. Callut, G. Dooms, J-N. Monette, Y. Deville, Relevant subgraph extraction from random walks in a graph, Research Report UCL/FSA/INGI RR 2006-07, November 2006.

  12. J. Callut and P. Dupont, Sequence Discrimination using Phase-type Distributions, Lecture Notes in Artificial Intelligence, No. 4212, European Conference on Machine Learning (ECML), Berlin, Germany, pp. 78-89, 2006.

  13. P. Dupont, Noisy Sequence Classification with Smoothed Markov Chains, CAp 2006, Conférence d'Apprentissage, Trégastel, France, May 22-24, Presses Universitaires de Grenoble, pp. 187-201, 2006.

  14. C. Damas, B. Lambeau, P. Dupont and A. van Lamsweerde, Generating Annotated Behavior Models from End-User Scenarios, © IEEE, IEEE Transactions on Software Engineering, Special Issue on Interaction and State-based Modeling, Vol. 31, No. 12, pp. 1056-1073, 2005.

  15. J. Callut and P. Dupont, Inducing Hidden Markov Models to Model Long-Term Dependencies, Lecture Notes in Artificial Intelligence, No. 3720, Springer-Verlag, 16th European Conference on Machine Learning (ECML), Porto, Portugal, pp. 513-521, 2005.

  16. J. Callut and P. Dupont, Learning Hidden Markov Models to Fit Long-Term Dependencies, UCL-INGI Research Report RR 2005-09, July 2005.

  17. J. Callut and P. Dupont, Fβ support vector machines, IJCNN05, International Joint Conference on Neural Networks, Montréal, Canada, pp. 1443-1448, 2005.

  18. S. Vast, P. Dupont and Y. Deville, Automatic extraction of relevant nodes in biochemical networks, Atelier Apprentissage et Bioinformatique, CAp 2005, Conférence d'Apprentissage, Nice, pp. 21-31, 2005.

  19. P. Dupont, F. Denis and Y. Esposito, Links between Probabilistic Automata and Hidden Markov Models: probability distributions, learning models and induction algorithms, Pattern Recognition: Special Issue on Grammatical Inference Techniques & Applications, Vol. 38, No. 9, pp. 1349-1371, 2005.

  20. J. Callut and P. Dupont, Séparateurs à vaste marge optimisant la fonction Fβ, CAp 2005, Conférence d'Apprentissage, Nice, Presses Universitaires de Grenoble, pp. 79-91, 2005.

  21. J. Callut and P. Dupont, A Markovian Approach to the Induction of Regular String Distributions, Lecture Notes in Artificial Intelligence, No. 3264, Springer-Verlag, Grammatical Inference: Algorithms and Applications, pp. 77--90, October, 2004.

  22. M. Saerens, F. Fouss, L. Yen and P. Dupont, The Principal Components Analysis of a Graph, and its Relationship to Spectral Clustering, Lecture Notes in Artificial Intelligence, No. 3201, Springer-Verlag, 15th European Conference on Machine Learning (ECML), Pisa, Italy, pp. 371-383, 2004.

  23. C. Kermorvant, C. de la Higuera and P.Dupont, Learning typed automata from automatically labeled data, Journal Électronique d'Intelligence Artificielle, Vol. 6-45, 2004.

  24. C. Kermorvant, C. de la Higuera and P. Dupont, Improving probabilistic automata learning with Additional Knowledge, Lecture Notes in Computer Science, No. 3138, Springer-Verlag, Joint IAPR International Workshops on Syntactical and Structural Pattern Recognition (SSPR 2004) and Statistical Pattern Recognition (SPR 2004), Lisbon, Portugal, pp. 260-268, 2004.

  25. C. Kermorvant, C. de la Higuera and P. Dupont, Construction de Modèles de Langages par Inférence d'Automates Typés à partir de Données Etiquetées Automatiquement, Conférence d'Apprentissage, Laval, France, Presses Universitaires de Grenoble, pp. 77--90, 2003.

  26. P. Dupont, F. Denis and Y. Esposito, Links between Probabilistic Automata and Hidden Markov Models: probability distributions, learning models and induction algorithms, UCL-INGI, Research Report 2003-02, January 2003.

  27. C. Kermorvant and P. Dupont, Stochastic grammatical inference with multinomial tests, Lecture Notes in Artificial Intelligence, No. 2484, Springer-Verlag, Grammatical Inference: Algorithms and Applications, pp. 149--160, 2002.

  28. Y. Esposito, A. Lemay, F. Denis and P.Dupont, Learning Probabilistic Residual Finite Automata, Lecture Notes in Artificial Intelligence, No. 2484, Springer-Verlag, Grammatical Inference: Algorithms and Applications, pp. 77--91, 2002.

  29. C. Kermorvant and P. Dupont, Improved smoothing for Probabilistic Suffix Trees seen as variable order Markov chains, Proceedings of the 13th European Conference on Machine Learning, Helsinki, Finland, pp. 185--194, 2002.

  30. C. Kermorvant and P. Dupont, Mélanges de Chaînes de Markov lissées pour la détection de domaines dans les protéines, Journées ouvertes biologie informatique mathématique, Saint-Malo, France, 2002.

  31. C. Kermorvant and P. Dupont, Inférence d'automates et correction d'erreurs pour la classification des protéines, Conférence d'Apprentissage, pp. 269--278, Grenoble, France, 2001.

  32. F. Thollard, P. Dupont and C. de la Higuera, Probabilistic DFA Inference using Kullback-Leibler Divergence and Minimality, Proceedings of the Seventeenth International Conference on Machine Learning, Morgan Kauffman, pp. 975 -- 982, Stanford University, USA, 2000.

  33. P. Dupont and J.-C. Amengual, Smoothing probabilistic automata: an error-correcting approach, Lecture Notes in Artificial Intelligence, No. 1891, Springer-Verlag, Grammatical Inference: Algorithms and Applications, pp. 51-64, 2000.

  34. F. Thollard and P. Dupont, Inférence Grammaticale Probabiliste utilisant la divergence de Kullback-Leibler et un principe de minimalité, Conférence d'Apprentissage, Saint-Etienne, France, Hermes Science, pp. 259 -- 275, 2000.

  35. F. Thollard and P. Dupont, Entropie relative et algorithmes d'inférence grammaticale probabiliste, Conférence d'Apprentissage, AFIA, pp. 115 -- 121, Palaiseau, France, 1999.

  36. L. Miclet, J. Chodorowski and P. Dupont, Apprentissage et évaluation de modèles de langage par des techniques de correction d'erreurs, Conférence d'Apprentissage, AFIA, pp. 253 -- 262, Palaiseau, France, 1999.

  37. P. Dupont and L. Chase, Using symbol clustering to improve probabilistic automaton inference, Lecture Notes in Artificial Intelligence, No. 1433, Springer-Verlag, Grammatical Inference, pp. 232 -- 243, 1998.

  38. P. Dupont and L. Miclet, Inférence grammaticale régulière : fondements théoriques et principaux algorithmes, Technical Report RR-3449, INRIA, 1998.

  39. P. Dupont, Polynomial Regular Inference, Technical Report EURISE 9705, 1997.

  40. P. Dupont, Incremental Regular Inference, Lecture Notes in Artificial Intelligence, No. 1147, Springer-Verlag, Grammatical Inference : learning syntax from sentences, pp. 222 -- 237, 1996.

  41. P. Dupont, Learning and Use of Language Models for Continuous Speech Recognition (written in French), ENST (Paris), February 1996, 247 pages.

  42. L. Miclet, P. Dupont and S. Vial, Inférence Grammaticale Régulière : méthodes semi-itératives et mesure de performance, Journées Francophones sur l'Apprentissage, pp. 103--106, Grenoble, 1995.

  43. P. Dupont, L. Miclet and E. Vidal, What is the search space of Regular Inference? , Lecture Notes in Artificial Intelligence, No. 862, Springer-Verlag, Grammatical Inference and Applications, pp. 25--37, 1994.

  44. P. Dupont, Regular Grammatical Inference from Positive and Negatives Samples by Genetic Search : the GIG method, Lecture Notes in Artificial Intelligence, No. 862, Springer-Verlag, Grammatical Inference and Applications, pp. 236--245, 1994.

  45. P. Dupont and F. Pinson, Inférence Grammaticale Régulière par Optimisation Génétique à partir d'échantillons positifs et négatifs : la méthode GIG, Journées Francophones sur l'Apprentissage, pp. G1--G13, 1994.

    Speech and language processing

  46. M.-C. de Marneffe, C. Archambeau, P. Dupont and M. Verleysen, Local Vector-based Models for Sense Discrimination, Sixth International Workshop on Computational Semantics, Tilburg, The Netherlands, January 12-14, pp. 163-174, 2005.

  47. M.-C. de Marneffe and P. Dupont, Comparative study of statistical word sense discrimination, Proc. of 7th International Conference on Statistical Analysis of Textual Data, Louvain-La-Neuve, Belgium, pp. 270--281, 2004.

  48. J. González, A. Juan, P. Dupont, E. Vidal and F. Casacuberta, A Bernoulli mixture model for word categorisation, Proceedings of Simposium Nacional de Reconocimiento de Formas y Análisis de Imágenes, Vol. 1, pp. 165-170, Benicàssim, Spain, 2001.

  49. L.J. Boë, F. Bimbot, J.-F. Bonastre and P. Dupont, Des évaluations des systèmes de vérification du locuteur à la mise en cause des expertises vocales en identification juridique, Langues, Vol.2, No.4, pp 270--288, 1999.

  50. P. Dupont and R. Rosenfeld, Lattice based language models, Technical Report, Carnegie Mellon University, CMU-CS-97-173, 1997.

  51. P. Dupont, Interpolated Word and Class Bigram Models for Spanish Conversational Speech Recognition, IEEE on Automatic Speech Recognition Workshop, pp. 121--122. -- Snowbird (USA), 1995.

  52. D. Sadek, P. Bretier, V. Cadoret, A. Cozannet, P. Dupont, A. Ferrieux and F. Panaget, A Cooperative Spoken Dialogue System Based on a Rational Agent Model: A First Implementation on the AGS Application, ESCA Tutorial and Research Workshop on Spoken Dialogue Systems, Visgo, Denmark, 1995.

  53. P. Dupont, Dynamic Use of Syntactical Knowledge in Continuous Speech Recognition, Proc. European Conference on Speech Communication and Technology, pp. 1959--1962. -- Berlin, 1993.

  54. P. Dupont, Efficient Integration of Context-Free Based Language Models in Continuous Speech Recognition, New Advances and Trends in Speech Recognition and Coding, NATO ASI, pp. 179--182. -- Granada, Spain, 1993.

  55. P. Dupont and Y. Kamp, Guiding Speech Recognition by a Language Model, From Natural Language Processing to Logic for Expert Systems, A Logic Based Approach to Artificial Intelligence, A. Thayse (editor), chap. 1, pp. 1--48. -- Chichester, Wiley, 1991.

  56. P. Dupont and A.Thayse, Montague's Semantics and Boolean Semantics for Natural Language Representation, Philips Journal of Research, Vol.45, No.1, pp. 41--66, 1990.

  57. P. Dupont and Y. Kamp, Reconnaissance de la parole pilotée par un modèle linguistique, Approche logique de l'intelligence artificielle, 3. Du traitement de la langue à la logique des systèmes experts, A. Thayse (éditeur), chap. 1, pp. 1--61. -- Paris, Bordas, Dunod Informatique, 1990.

    Constraint programming

  58. Y. Deville, P. Dupont, G. Dooms, J.-N.Monette, P. Schaus, S. Wodak and S. Zampelli. BioEdge: a tool box for advanced analyses of biochemical networks (Poster) , Benelux Bioinformatics Conference (BBC'07), November 12-13, Leuven, Belgium, 2007.

  59. P. Schaus, Y. Deville and P. Dupont, Bound-Consistent Deviation Constraint, Lecture Notes in Computer Science, No. 4741, Springer, 13th International Conference on Principles and Practice of Constraint Programming (CP 2007), Providence, RI, USA, September 23-27, pp. 620-634, 2007.

  60. S. Zampelli, Y. Deville, C. Solnon, S. Sorlin and P. Dupont, Filtering for Subgraph Isomorphism, Lecture Notes in Computer Science, No. 4741, Springer, 13th International Conference on Principles and Practice of Constraint Programming (CP 2007), Providence, RI, USA, September 23-27, pp. 728-742, 2007.

  61. J.-N. Monette, P. Schaus, S. Zampelli, Y. Deville and P. Dupont, A CP Approach to the Balanced Academic Curriculum Problem, 7th International Workshop on Symmetry and Constraint Satisfaction Problems (SymCon'07), Providence, RI, USA, September 23, pp. 56-63, 2007.

  62. S. Zampelli, Y. Deville, C. Solnon, S. Sorlin and P. Dupont, Filtrage pour l'isomorphisme de sous-graphe, Journées Francophones de Programmation par Contraintes (JFPC'07), Rocquencourt, France, June 4-6, pp. 285-296, 2007.

  63. P. Schaus, Y. Deville and P. Dupont, La Contrainte Déviation, Journées Francophones de Programmation par Contraintes (JFPC'07), Rocquencourt, France, June 4-6, pp. 173-182, 2007.

  64. J.-N. Monette, Y. Deville, and P. Dupont, Un propagateur basé sur les positions pour le problème d'Open-Shop, in Journées Francophones de Programmation par Contraintes (JFPC'07), Rocquencourt, France, pp. 255-264, June 4-6, 2007.

  65. P. Schaus, Y. Deville, P. Dupont and J.-C. Régin, The Deviation Constraint, Lecture Notes in Computer Science, No. 4510, pp. 260-274, Springer, 4th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, Brussels, Belgium, May 23-26, 2007.

  66. J.-N. Monette, Y. Deville, and P. Dupont, A Position-Based Propagator for the Open-Shop Problem, Lecture Notes in Computer Science, No. 4510, pp. 186-199, Springer, 4th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, Brussels, Belgium, May 23-26, 2007.

  67. P. Schaus, Y. Deville, P. Dupont and J.-C. Régin, Simplification and extension of the SPREAD Constraint, Trends in Constraint Programming, F. Benhamou, N. Jussien and B. O'Sullivan (Eds), pp. 95-99, ISTE Hermes, 2007.

  68. S. Zampelli, Y. Deville and P. Dupont, Symmetry Breaking in Subgraph Pattern Matching, Trends in Constraint Programming, F. Benhamou, N. Jussien and B. O'Sullivan (Eds), Chapter 10, pp. 203-218, ISTE Hermes, 2007.

  69. P. Schaus, Y. Deville, P. Dupont, J.-C. Régin, Simplification and extension of the SPREAD Constraint, Third International Workshop on Constraint Propagation And Implementation (CPAI'06), Nantes, France, pp. 77-91, September 25, 2006.

  70. S. Zampelli, Y. Deville, P. Dupont, Symmetry Breaking in Subgraph Pattern Matching, Sixth International Workshop on Symmetry in Constraint Satisfaction Problems (SymCon'06), Nantes, France, pp. 31-38, September 25, 2006.

  71. S. Zampelli, Y. Deville, P. Dupont, Elimination des symétries pour l'appariement de graphes, JFPC'06, Deuxièmes Journées Francophones de Programmation par Contraintes, Nîmes, France, June 7-9, pp. 357-367, 2006.

  72. Y. Deville, G. Dooms, S. Zampelli and P. Dupont, CP(Graph+Map) for Approximate Graph Matching, 1st International Workshop on Constraint Programming Beyond Finite Integer Domains, Sitges (Barcelona), Spain, October 1, pp. 31-47, 2005.

  73. G. Dooms, Y. Deville, P. Dupont, Constrained metabolic network analysis: discovering pathways using CP(Graph), Workshop on Constraint Based Methods for Bioinformatics, Sitges (Barcelona), Spain, October 5, pp. 29-35, 2005.

  74. S. Zampelli, Y. Deville and P. Dupont, Declarative Approximate Graph Matching Using a Constraint Approach, Second International Workshop on Constraint Propagation and Implementation, Sitges (Barcelona), Spain, October 1, Vol. 1, pp. 109-124, 2005.

  75. S. Zampelli, Y. Deville and P. Dupont, Approximate Constrained Subgraph Matching, Lecture Notes in Computer Science, No. 3709, Springer-Verlag, 11th International Conference on Principles and Practice of Constraint Programming, Sitges, Barcelona, Spain, pp. 832-836, 2005.

  76. G. Dooms, Y. Deville and P. Dupont, CP(Graph): Introducing a Graph Computation Domain in Constraint Programming, Lecture Notes in Computer Science, No. 3709, Springer-Verlag, 11th International Conference on Principles and Practice of Constraint Programming, Sitges, Barcelona, Spain, pp. 211-225, 2005.

  77. G. Dooms, Y. Deville and P. Dupont, A Mozart implementation of CP(BioNet), Lecture Notes in Artficial Intelligence, No. 3389, Springer-Verlag, 2nd International Mozart/Oz Conference, pp. 237-250, 2005.

  78. G. Dooms, Y. Deville and P. Dupont, Recherche de chemins contraints dans les réseaux biochimiques, Treizièmes Journées Francophones de Programmation en Logique et de Programmation par Contraintes (JFPLC), Angers, France, pp. 109-128, June 2004.

  79. G. Dooms, Y. Deville and P. Dupont, Constrained Path Finding in Biochemical Networks: a Constraint Programming Approach, 5th Open Days in Biology, Computer Science and Mathematics (JOBIM), Montreal, Canada, JO-40, 2004.

  80. S. Zampelli, Y. Deville and P. Dupont, Finding Patterns in Biochemical Networks, 5th Open Days in Biology, Computer Science and Mathematics (JOBIM), Montreal, Canada, JO-85, 2004.

    Miscellaneous

  81. E. Bourgeois, P. Dupont, M. Frenay, B. Galand, A. Laloux, E. Milgrom, B. Raucent, C. Trullemans, C. Vander Borght, V. Wertz, P. Wouters, L'approche par Problèmes et par Projets dans l'Enseignement Supérieur. Impact, Enjeux et Défis, Benoît Galand et Mariane Frenay (dir.), Presses Universitaires de Louvain, 2005.

Autonomous Citation Index (ACI) from Research Index (CiteSeer)

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Pierre Dupont
Last modified: Mon Sep 29 11:17:55 CEST 2008