SST/EPL Ecole polytechnique de Louvain (EPL)
SST/ICTM Institute of Information and Communication Technologies, Electronics and Applied Mathematics (ICTEAM)
SST/ICTM/INGI Pôle en ingénierie informatique (INGI)
2025
Papier de conférence
Ronval, B., Dupont, P., & Nijssen, S. (2025). Detection of Large Language Model Contamination with Tabular Data. Advances in Intelligent Data Analysis XXIII 23nd International Symposium on Intelligent Data Analysis, IDA 2025, Konstanz, Germa, 234-245. https://doi.org/10.1007/978-3-031-91398-3_18 (Original work published 2025)
Ronval, B., Dupont, P., & Nijssen, S. (2025). TAGAL: Tabular Data Generation using Agentic LLM Methods. SynDAiTE, ECML PKDD 2025 Workshop. Accepted/in-press. SynDAiTE, ECML PKDD 2025 Workshop, Porto, Portugal. (Original work published 2025)
2024
Article de journal
Gerniers, A., Nijssen, S., & Dupont, P. (2024). scCross: efficient search for rare subpopulations across multiple single-cell samples. Bioinformatics, 40(6), btae371. https://doi.org/10.1093/bioinformatics/btae371 (Original work published 2024)
2022
Papier de conférence
Gerniers, A., & Dupont, P. (2022). MicroCellClust 2: a hybrid approach for multivariate rare cell mining in large-scale single-cell data. 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), p. 148-153. https://doi.org/10.1109/bibm55620.2022.9995176
2021
Article de journal
Hamer, V., & Dupont, P. (2021). An Importance Weighted Feature Selection Stability Measure. Journal of Machine Learning Research, 22(116), 1-57. (Original work published 2021)
Gerniers, A., Bricard, O., & Dupont, P. (2021). MicroCellClust: mining rare and highly specific subpopulations from single-cell expression data. Bioinformatics, 37(19), 3220-3227. https://doi.org/10.1093/bioinformatics/btab239 (Original work published 2021)
Papier de conférence
Hamer, V., & Dupont, P. (2021). Robust Selection Stability Estimation in Correlated Spaces. Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 1(1), 446-461. (Original work published 2021)
2020
Papier de conférence
Hamer, V., & Dupont, P. (2020). Joint optimization of predictive performance and selection stability. ESANN 2020 - Proceedings, 1(1), 381-386. (Original work published 2020)
2019
Papier de conférence
Hamer, V., & Dupont, P. (2019). Explicit Control of Feature Relevance and Selection Stability Through Pareto Optimality. C E U R Workshop Proceedings, 2444(1), 64-79. (Original work published 2019)
Branders, V., Derval, G., Schaus, P., & Dupont, P. (2019). Mining a Maximum Weighted Set of Disjoint Submatrices. Discovery Science : Lecture Notes in Computer Science, p. 18-28. https://doi.org/10.1007/978-3-030-33778-0_2
Article de journal
Branders, V., Schaus, P., & Dupont, P. (2019). Identifying gene-specific subgroups: an alternative to biclustering. BMC Bioinformatics, 20(625), 13. https://doi.org/10.1186/s12859-019-3289-0 (Original work published 2019)
Chapitre de livre
Derval, G., Branders, V., Dupont, P., & Schaus, P. (2019). The Maximum Weighted Submatrix Coverage Problem: A CP Approach. In Louis-Martin Rousseau, Kostas Stergiou (ed.), Integration of Constraint Programming, Artificial Intelligence, and Operations Research : Lecture Notes in Computer Science (16th International Conference, CPAIOR 2019, Thessaloniki, Greece, June 4–7, 2019, Proceedings, p. p. 258-274). Springer, Cham. https://doi.org/10.1007/978-3-030-19212-9_17
2018
Papier de conférence
Hamer, V., & Dupont, P. (2018). Learning Computationally Efficient Metrics for Large Scale Person Identification. Proceedings of the Annual Machine Learning Conference of Belgium and the Netherlands 2018. Published. BENELEARN2018, Jheronimus Academy of Data Science. (Original work published 2018)
Chapitre de livre
Branders, V., Schaus, P., & Dupont, P. (2018). Combinatorial Optimization Algorithms to Mine a Sub-Matrix of Maximal Sum. In Annalisa Appice, Corrado Loglisci, Giuseppe Manco, Elio Masciari, Zbigniew W. Ras (ed.), New Frontiers in Mining Complex Patterns (6th International Workshop, NFMCP 2017, Held in Conjunction with ECML-PKDD 2017, Macedonia, Sept. 18-22, Revised Selected Papers, p. p. 65-79). https://doi.org/10.1007/978-3-319-78680-3_5
2017
Papier de conférence
Branders, V., Schaus, P., & Dupont, P. (2017). Mining a sub-matrix of maximal sum. Proceedings of the 6th International Workshop on New Frontiers in Mining Complex Patterns in conjunction with ECML-PKDD 2017. Published. 6th International Workshop on New Frontiers in Mining Complex Patterns in conjunction with ECML-PKDD 2017, Skopje (MK). (Original work published 2017)
2015
Article de journal
De Visscher, R., Delouille, V., Dupont, P., & Deledalle, C.-A. (2015). Supervised classification of solar features using prior information. Journal of Space Weather and Space Climate, 5(A34), 1-12. https://doi.org/10.1051/swsc/2015033 (Original work published 2015)
Paul, J., D’Ambrosio, R., & Dupont, P. (2015). Kernel methods for heterogeneous feature selection. Neurocomputing, 169, 187-195. https://doi.org/10.1016/j.neucom.2014.12.098 (Original work published 2015)
Paul, J., & Dupont, P. (2015). Inferring statistically significant features from random forests. Neurocomputing, 150(part B), 471-480. https://doi.org/10.1016/j.neucom.2014.07.067 (Original work published 2015)
Lombard, C., André, F., Paul, J., Wanty, C., Vosters, O., Bernard, P., Pilette, C., Dupont, P., Sokal, E., & Smets, F. (2015). Clinical Parameters vs Cytokine Profiles as Predictive Markers of IgE-Mediated Allergy in Young Children. PLoS One, 10(7), e0132753 [1-12]. https://doi.org/10.1371/journal.pone.0132753 (Original work published 2015)
Branders, S., & Dupont, P. (2015). A balanced hazard ratio for risk group evaluation from survival data. Statistics in Medicine, 34(17), 2528-2543. https://doi.org/10.1002/sim.6505 (Original work published 2015)
Lauwerys, B., Hernández-Lobato, D., Gramme, P., Ducreux, J., Dessy, A., Ambroise, J., Bearzatto, B., Nzeusseu Toukap, A., Van den Eynde, B., Elewaut, D., Gala, J.-L., Durez, P., Houssiau, F., Helleputte, T., & Dupont, P. (2015). Heterogeneity of synovial molecular patterns in patients with arthritis. PLoS One, 10(4), e0122104 [1-18]. https://doi.org/10.1371/journal.pone.0122104 (Original work published 2015)
Papier de conférence
Branders, S., Frenay, B., & Dupont, P. (2015). Survival Analysis with Cox Regression and Random Non-linear Projections. Proceedings of the 23th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Published. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Bruges, Belgium.
Brevet
Feron, O., Dupont, P., Boidot, R., Branders, S., Helleputte, T., & et al. (2015). Signature of cycling hypoxia and use thereof for the prognosis of cancer (Patent No. PCT/EP2014/066643).
2014
Papier de conférence
Branders, S., D’Ambrosio, R., & Dupont, P. (2014). The Coxlogit model: feature selection from survival and classification data. Computational Intelligence in Multi-Criteria Decision-Making (MCDM), 2014 IEEE Symposium on, 137-143. https://doi.org/10.1109/MCDM.2014.7007199
Paul, J., & Dupont, P. (2014). Statistically interpretable importance indices for Random Forests. 23rd Annual Machine Learning Conference of Belgium and the Netherlands (BENELEARN), Brussels, Belgium.
Paul, J., & Dupont, P. (2014). Kernel methods for mixed feature selection. ESANN2014, 22th European Symposium on Artificial Neural Networks - Computational Intelligence and Machine Learning, 301-306.
Dessy, A., & Dupont, P. (2014). Computationally Efficient Test for Gene Set Dysregulation. International Workshop on Machine Learning in Systems Biology, Strasbourg, France.
Article de journal
Boidot, R., Branders, S., Helleputte, T., Illan Rubio, L., Dupont, P., & Feron, O. (2014). A generic cycling hypoxia-derived prognostic gene signature: application to breast cancer profiling. OncoTarget, 5(16), 6947-6963. (Original work published 2014)
2013
Papier de conférence
Renard, E., Dupont, P., & Verleysen, M. (2013). User control for adjusting conflicting objectives in parameter-dependent visualization of data. Workshop on Visual Analytics using Multidimensional Projections (EuroVis 2013), Leipzig (Germany).
Paul, J., Verleysen, M., & Dupont, P. (2013). Identification of Statistically Significant Features from Random Forests. ECML workshop on Solving Complex Machine Learning Problems with Ensemble Methods, Prague (Czech Republic).
Article de journal
Lee, J., Renard, E., Bernard, G., Dupont, P., & Verleysen, M. (2013). Type 1 and 2 mixtures of Kullback-Leibler divergences as cost functions in dimensionality reduction based on similarity preservation. Neurocomputing, 112(1), 92-108. https://doi.org/10.1016/j.neucom.2012.12.036 (Original work published 2013)
Grandjean, M., Sermeus, A., Branders, S., Defresne, F., Dieu, M., Dupont, P., Raes, M., De Ridder, M., & Feron, O. (2013). Hypoxia integration in the serological proteome analysis unmasks tumor antigens and fosters the identification of anti-phospho-eEF2 antibodies as potential cancer biomarkers. PLoS One, 8(10), e76508 [1-10]. https://doi.org/10.1371/journal.pone.0076508 (Original work published 2013)
Hernandez Lobato, D., Hernandez Lobato, J. M., & Dupont, P. (2013). Generalized spike-and-slab priors for bayesian group feature selection using expectation propagation. Journal of Machine Learning Research, 14, 1891-1945. (Original work published 2013)
2012
Article de journal
Walkinshaw, N., Lambeau, B., Damas, C., Bogdanov, K., & Dupont, P. (2012). STAMINA: A Competition to Encourage the Development and Assessment of Software Model Inference Techniques. Empirical Software Engineering : an international journal, 18(4), 791-824. https://doi.org/10.1007/s10664-012-9210-3 (Original work published 2013)
Seront, E., Rottey, S., Sautois, B., Kerger, J., D’Hondt, L., Verschaeve, V., Canon, J.-L., Dopchie, C., Vandenbulcke, J. M., Whenham, N., Goeminne, J. C., Clausse, M., Verhoeven, D., Glorieux, P., Branders, S., Dupont, P., Schoonjans, J., Feron, O., & Machiels, J.-P. (2012). Phase II study of everolimus in patients with locally advanced or metastatic transitional cell carcinoma of the urothelial tract: clinical activity, molecular response,and biomarkers. Annals of Oncology, 23(10), 2663-2670. https://doi.org/10.1093/annonc/mds057 (Original work published 2012)
Papier de conférence
Paul, J., Verleysen, M., & Dupont, P. (2012). The stability of feature selection and class prediction from ensemble tree classifiers. ESANN 2012 The 20 th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning - Proceedings - Bruges, Belgium from 25 to 27 April 2012 ., 263-268.
2011
Papier de conférence
Lobato, D. H., Ducreux, J., Durez, P., Nzeusseu Toukap, A., Elewaut, D., Houssiau, F., Dupont, P., & Lauwerys, B. (2011). Feasibility of a molecular diagnosis of arthritis based on the iIdentification of specific transcriptomic profiles in knee synovial biopsies. Arthritis & Rheumatism, 63(sppl), 751. (Original work published 2011)
Zakharov, R., & Dupont, P. (2011). Ensemble logistic regression for feature selection. Lecture Notes in Computer Science, 7036, 133-144. https://doi.org/10.1007/978-3-642-24855-9_12 (Original work published 2011)
Hernandez-Lobato, D., Hernandez-Lobato, J. M., & Dupont, P. (2011). Robust Multi-Class Gaussian process classification. Neural Information Processing Systems conference (NIPS′11), Granada, Spain.
2010
Brevet
Dupont, P., Gaulis, S., & Helleputte, T. (2010). Method for classifying a cancer patient as responder or non-responder to immunotherapy (Patent No. WO/2010/029174).
Article de journal
Abeel, T., Helleputte, T., Van de Peer, Y., Dupont, P., & Saeys, Y. (2010). Robust biomarker identification for cancer diagnosis with ensemble feature selection methods. Bioinformatics, 26(3), 392-398. https://doi.org/10.1093/bioinformatics/btp630 (Original work published 2010)
Faust, K., Dupont, P., Callut, J., & van Helden, J. (2010). Pathway discovery in metabolic networks by subgraph extraction. Bioinformatics, 26(9), 1211-1218. https://doi.org/10.1093/bioinformatics/btq105 (Original work published 2010)
Papier de conférence
Walkinshaw, N., Bogdanov, K., Damas, C., Lambeau, B., & Dupont, P. (2010). A framework for the competitive evaluation of model inference techniques. In Roland Groz, Keqin Li (ed.), Proceedings of the First International Workshop on Model Inference In Testing (p. p. 1-9). ACM. https://doi.org/10.1145/1868044.1868045
Hernandez-Lobato, D., Hernández-Lobato, J. M., Helleputte, T., & Dupont, P. (2010). Expectation Propagation for Bayesian Multi-task Feature Selection. In Balcazar, J.L.; Bonchi, F.; Gionis, A.; Sebag, M.; (ed.), Machine Learning and Knowledge Discovery in Databases. European Conference, ECML PKDD 2010 (pp. 522-537). Springer.
2009
Papier de conférence
Narino Mendoza, J. P., Donnet, B., & Dupont, P. (2009). A comparative study of path performance metrics predictors. Advances in learning for networking, ACM workshop in conjunction with SIGMETRICS/Performance, Seattle, USA.
Helleputte, T., & Dupont, P. (2009). Feature selection by transfer learning with linear regularized models. In Buntine, W.; Grobelnik, M.; Mladenic, D.; Shawe-Taylor, J.; (ed.), Machine Learning and Knowledge Discovery in Databases. European Conference, ECML PKDD 2009 (p. p. 533-547). Springer-verlag.
Lambeau, B., Damas, C., & Dupont, P. (2009). State-merging DFA induction algorithms with mandatory merge constraints. In Clark, A.; Coste, F.; Miclet, L. (ed.), Grammatical Inference: Algorithms and Applications. 9th International Colloquim, ICGI 2008 (p. p. 139-153). Springer-verlaq.
Helleputte, T., & Dupont, P. (2009). Partially supervised feature selection with regularized linear models. In Andrea Danyluk, Léon Bottou, Michael Littman (ed.), ICML ’09 Proceedings of the 26th Annual International Conference on Machine Learning (p. p. 409-416). ACM.
Abeel, T., Helleputte, T., Van de Peer, Y., Dupont, P., & Saeys, Y. (2009). Robust biomarker identification for cancer diagnosis using ensemble feature selection methods. Third International Workshop on Machine Learning in Systems Biology (MLSB), Ljubljana, Slovenia.
2008
Papier de conférence
Callut, J., Dupont, P., Saerens, M., & Françoisse, K. (2008). Classification in Graphs using Discriminative Random Walks : Semi-supervised learning, large graphs, betweenness measure, passage times. 6th International Workshop on Mining and Learning with Graphs (MLG), Helsinki, Finland.
Callut, J., Françoisse, K., Dupont, P., & Saerens, M. (2008). Semi-supervised classification from discriminative random walks. Proceedings of the European Conference on Machine Learning, p. 162-177.
Faust, K., Callut, J., Dupont, P., & van Helden, J. (2008). Inference of pathways from metabolic networks by subgraph extraction. Second International Workshop on Machine Learning in Systems Biology (MLSB), Brussel, Belgium.
Callut, J., Dupont, P., Saerens, M., & Françoisse, K. (2008). Semi-supervised Classification in Graphs using Bounded Random Walks. 17th Annual Machine Learning Conference of Belgium and the Netherlands (Benelearn), Liège, Belgium.
Louahed, J., Dréno, B., Gaulis, S., Helleputte, T., Dupont, P., Gruselle, O., Spatz, A., Kruit, W., Lehmann, F., & Brichard, V. (2008). Clinical response to the MAGE-A3 immunotherapeutic in metastatic melanoma patients is associated with a specific gene profile present prior to treatment. Annals of Oncology, 19(Sppl. 8), VIII61-VIII62. (Original work published 2008)
Chapitre de livre
Callut, J., Dupont, P., Saerens, M., & Françoisse, K. (2008). Semi-supervised Classification from Discriminative Random Walks.
Lambeau, B., Damas, C., & Dupont, P. (2008). State-merging DFA Induction Algorithms with Mandatory Merge Constraints. In 9th International Colloquium on Grammatical Inference (ICGI) (p. p. 139-153). Springer-Verlag.
Article de journal
Dupont, P., Lambeau, B., Damas, C., & van Lamsweerde, A. (2008). The QSM algorithm and its application to software behavior model induction. Applied Artificial Intelligence : an international journal, 22(1-2), 77-115. https://doi.org/10.1080/08839510701853200 (Original work published 2008)
2007
Papier de conférence
Callut, J., & Dupont, P. (2007). Learning partially observable Markov models from first passage times. In Kok, J.N.; Koronacki, J.; de Mantaras, R.L.; Matwin, S.; Mladenic, D.; Skowron, A.; (ed.), Machine Learning: ECML 2007. Proceedings 18th European Conference onMachine Learning. (Lecture Notes in Artificial Intelligence vol. 4701) (pp. 91-103). Springer-verlag.
Faust, K., Dupont, P., Callut, J., & van Helden, J. (2007). Inference of pathways from metabolic networks by subgraph extraction. Benelux bioinformatics conference BBC07, Leuven, Belgium.
Monette, J.-N., Deville, Y., & Dupont, P. (2007). A position-based propagator for the open-shop problem. In Van Hentenryck, P.; Wolsey, L.; (ed.), Integration of AI and OR Techniques in Constraint Programming forCombinatorial Optimization Problems. Proceedings 4th InternationalConference, CPAIOR 2007 (p. p. 186-199). Springer.
Deville, Y., Dupont, P., Dooms, G., Monette, J.-N., Schaus, P., Zampelli, S., & Wodak, S. (2007). BioEdge: a tool box for advanced analyses of biochemical networks. Benelux Bioinformatics Conference (BBC′07), Leuven, Belgium.
Schaus, P., Deville, Y., Dupont, P., & Régin, J.-C. (2007). Simplification and extension of the SPREAD Constraint. Third international workshop on constraint propagation and implementation, Nantes, France.
Schaus, P., Deville, Y., Dupont, P., & Regin, J.-C. (2007). The deviation constraint. In Van Hentenryck, P.; Wolsey, L.; (ed.), Integration of AI and OR Techniques in Constraint Programming forCombinatorial Optimization Problems. Proceedings 4th InternationalConference, CPAIOR 2007 (p. p. 260-274). Springer.
Zampelli, S., Deville, Y., Solnon, C., Sorlin, S., & Dupont, P. (2007). Filtering for subgraph isomorphism. Principles and Practice of Constraint Programming. 13th International Conference, CP 2007, p. 728-742.
Schaus, P., Deville, Y., Dupont, P., & Régin, J.-C. (2007). La Contrainte Déviation. Journées Francophones de Programmation par Contraintes (JFPC′07), Rocquencourt, France.
Monette, J.-N., Schaus, P., Zampelli, S., Deville, Y., & Dupont, P. (2007). A CP Approach to the Balanced Academic Curriculum Problem. Symcon′07, The Seventh International Workshop on Symmetry and Constraint Satisfaction Problems, Providence, USA.
Zampelli, S., Deville, Y., Solnon, C., Sorlin, S., & Dupont, P. (2007). Filtrage pour l’isomorphisme de sous-graphe. Journées Francophones de Programmation par Contraintes (JFPC′07), Rocquencourt, France,.
Monette, J.-N., Deville, Y., & Dupont, P. (2007). Un propagateur basé sur les positions pour le problème d’Open-Shop. Journées Francophones de Programmation par Contraintes (JFPC′07), Rocquencourt, France,.
Chapitre de livre
Zampelli, S., Deville, Y., & Dupont, P. (2007). Symmetry breaking in subgraph pattern matching. In Frédéric Benhamou,Narendra Jussien,Barry O’Sullivan (ed.), Trends in Constraint Programming (p. p. 203-218).
Schaus, P., Deville, Y., & Dupont, P. (2007). Bound-Consistent Deviation Constraint. In Bessiere, Christian (ed.), Principles and Practice of Constraint Programming, CP 2007 (p. p. 620-634). Springer.
Schaus, P., Deville, Y., Dupont, P., & Regin, J.-C. (2007). Simplification and extension of the SPREAD Constraint. In Benhamou, Frédéric; Jussien, Narendra; O’Sullivan, Barry (Ed. by) (ed.), Trends in Constraint Programming (p. p. 95-99).
2006
Chapitre de livre
Dupont, P. (2006). Comment choisir la taille d’un groupe ? In Raucent, Benoît ; Vander Borght, Cécile (ed.), Etre enseignant - Magister ? Metteur en scène ? (p. p. 184-188). De Boeck (Bruxelles).
Dupont, P. (2006). Noisy Sequence Classification with Smoothed Markov Chains. In CAp 2006, Conférence d’Apprentissage (p. p. 187-201). Presses Universitaires de Grenoble.
Dupont, P. (2006). Quelles sont les compétences requises pour un tuteur dans les domaines scientifique et méthodologique ? In Raucent, Benoît ; Vander Borght, Cécile (ed.), Etre enseignant - Magister ? Metteur en scène ? (p. p. 329-332). De Boeck (Bruxelles).
Papier de conférence
Zampelli, S., Deville, Y., & Dupont, P. (2006). Symmetry Breaking in Subgraph Pattern Matching. In Frédéric Benhamou,Narendra Jussien, Barry O’Sullivan (ed.), Trends in Constraint Programming (p. p. 203-218). Wiley.
Schaus, P., Deville, Y., Dupont, P., & Régin, J.-C. (2006). Simplification and extension of the SPREAD Constraint. Third International Workshop on Constraint Propagation And Implementation (CPAI′06), Nantes, France.
Callut, J., & Dupont, P. (2006). Sequence discrimination using phase-type distributions. Lecture Notes in Computer Science, 4212, 78-89. https://doi.org/10.1007/11871842_12 (Original work published 2006)
Zampelli, S., Deville, Y., & Dupont, P. (2006). Elimination des symétries pour l’appariement de graphes. JFPC′06, Deuxièmes Journées Francophones de Programmation par Contraintes, Nîmes, France.
Document de travail
Dupont, P., Callut, J., Dooms, G., Monette, J.-N., & Deville, Y. (2006). Relevant subgraph extraction from random walks in a graph.
2005
Papier de conférence
Callut, J., & Dupont, P. (2005). Séparateurs à vaste marge optimisant la fonction Fbeta. CAp 2005, Conférence d’Apprentissage, Nice, France.
Callut, J., & Dupont, P. (2005). Inducing Hidden Markov Models to model long-term dependencies. Lecture Notes in Computer Science, 3720, 513-521. https://doi.org/10.1007/11564096_49 (Original work published 2005)
de Marneffe, M.-C., Archambeau, C., Dupont, P., & Verleysen, M. (2005). Local Vector-based Models for Sense Discrimination. Proceedings of IWCS 2005, 6th International Workshop on Computational Semantics, Tilburg (the Netherlands).
Deville, Y., Dooms, G., Zampelli, S., & Dupont, P. (2005). CP(Graph+Map) for Approximate Graph Matching. 1st International Workshop on Constraint Programming Beyond Finate Integer Domains, Stiges, Spain.
Dooms, G., Deville, Y., & Dupont, P. (2005). Constrained metabolic network analysis: discovering pathways using CP(Graph). Workshop on Constraint Based Methods for Bioinformatics, CP2005, Sitges, Spain.
Callut, J., & Dupont, P. (2005). F/sub beta / support vector machines. Proceedings of the International Joint Conference on Neural Networks2005 (IEEE Cat. No. 05CH37663C), Vol. 3, p. 1443-8.
Dooms, G., Deville, Y., & Dupont, P. (2005). CP(graph): Introducing a graph computation domain in constraint programming. Lecture Notes in Computer Science, 3709, 211-225. https://doi.org/10.1007/11564751_18 (Original work published 2005)
Zampelli, S., Deville, Y., & Dupont, P. (2005). Declarative Approximate Graph Matching Using a Constraint Approach. Second International Workshop on Constraint Propagation and Implementation, Stiges, Spain.
Zampelli, S., Deville, Y., & Dupont, P. (2005). Approximate constrained subgraph matching. Lecture Notes in Computer Science, 3709, 832-836. https://doi.org/10.1007/11564751_74 (Original work published 2005)
Vast, S., Dupont, P., & Deville, Y. (2005). Automatic extraction of relevant nodes in biochemical networks. Atelier Apprentissage et Bioinformatique, CAp 2005, Conférence d’Apprentissage, Nice, France.
Dooms, G., Deville, Y., & Dupont, P. (2005). A Mozart implementation of CP(BioNet). Lecture Notes in Computer Science, 3389, 237-250. https://doi.org/10.1007/978-3-540-31845-3_20 (Original work published 2005)
Document de travail
Callut, J., & Dupont, P. (2005). Learning hidden Markov models to fit long-term dependencies.
Saerens, M., Fouss, F., Yen, L., & Dupont, P. (2005). The principal components analysis of a graph and its relationships to spectral clustering (IAG Working Papers 2005/124).
Chapitre de livre
Dupont, P. (2005). Une expérience de Candis 2000. In Galand, Benoit ; Frenay Mariane (ed.), L’approche par problèmes et par projets dans l’enseignement supérieur : impact, enjeux et défis (p. p. 54-59). Presses universitaires de Louvain.
Article de journal
Damas, C., Lambeau, B., Dupont, P., & van Lamsweerde, A. (2005). Generating annotated behavior models from end-user scenarios. IEEE Transactions on Software Engineering, 31(12), 1056-1073. https://doi.org/10.1109/TSE.2005.138 (Original work published 2005)
Dupont, P., Denis, E., & Esposito, Y. (2005). Links between probabilistic automata and hidden Markov models: probability distributions, learning models and induction algorithms. Pattern Recognition, 38(9), 1349-1371. https://doi.org/10.1016/j.patcog.2004.03.020 (Original work published 2005)
2004
Papier de conférence
Saerens, M., Fouss, F., Dupont, P., & Pirotte, A. (2004). Collaborative filtering based on random walks on a graph. Workshop on Large Networks, UCL, LLN.
Saerens, M., Fouss, F., Yen, L., & Dupont, P. (2004). The principle components analysis of a graph, and its relationships to spectral clustering. In Boulicaut, J.-F.; Esposito, F.; Giannotti, F.; Pedreschi, D.; (ed.), Machine Learning: ECML 2004. 15th European Conference on MachineLearning. Proceedings (Lecture Notes in Artificial IntelligenceVol.3201) (p. p. 371-383). Springer-verlag.
Saerens, M., Fouss, F., Yen, L., & Dupont, P. (2004). The principal components analysis of a graph, and its relationships to spectral clustering. Lecture Notes in Computer Science, 3201, 371-383. (Original work published 2004)
de Marneffe, M.-C., & Dupont, P. (2004). Comparative study of statistical word sense discrimination,. Proceedings of the 7th International Conference on Textual Data Statistical Analysis, Louvain-la-Neuve, Belgique.
Zampelli, S., Deville, Y., & Dupont, P. (2004). Finding Patterns in Biochemical Networks. 5h Open Days in Biology, Computer Science and Mathematics (JOBIM 2004), Montreal, Canada.
Dooms, G., Deville, Y., & Dupont, P. (2004). Recherche de chemins contraints dans les réseaux biochimiques. Treizièmes Journées Francophones de Programmation en Logique et de Programmation par contraintes (JFPLC 2004), Angers, France.
Callut, J., & Dupont, P. (2004). A Markovian approach to the induction of regular string distributions. Lecture Notes in Computer Science, 3264, 77-90. https://doi.org/10.1007/978-3-540-30195-0_8 (Original work published 2004)
Dooms, G., Deville, Y., & Dupont, P. (2004). Constrained Path Finding in Biochemical Networks: a Constraint Programming Approach. 5th Open Days in Biology, Computer Science and Mathematics (JOBIM 2004), Montreal, Canada.
Article de journal
Kermorvant, C., de la Higuera, C., & Dupont, P. (2004). Learning typed automata from automatically labeled data. Journal electonique d’intelligence artificielle, 6(45). (Original work published 2004)
Chapitre de livre
Kermorvant, C., de la Higuera, C., & Dupont, P. (2004). Improving probabilistic automata learning with additional knowledge. In Fred, A.; Caelli, T.; Duin, R.P.W.; Campilho, A.; Ridder, D.d. (ed.), Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshops, SSPR 2004 and SPR 2004 (p. p. 260-268). Springer-Verlag.
2003
Papier de conférence
Kermorvant, C., de la Higuera, C., & Dupont, P. (2003). Construction de Modèles de Langages par Inférence d’Automates Typés à partir de Données Etiquetées Automatiquement. Conférence d’apprentissage, Laval, France.
2002
Chapitre de livre
Kermorvant, C., & Dupont, P. (2002). Stochastic grammatical inference with multinomial tests. In P. Adriaans ; H. Fernau ; M. van Zaanen (ed.), Grammatical Inference: Algorithms and Applications (p. p. 149-160). Springer-Verlag.
Kermorvant, C., & Dupont, P. (2002). Improved smoothing for Probabilistic Suffix Trees seen as variable order Markov chains. In T. Elomaa; H. Mannila ; H. Toivonen (ed.), Machine Learning: ECML 2002 (p. p. 185-194). Springer Verlag.
Esposito, Y., Lemay, A., Denis, F., & Dupont, P. (2002). Learning Probabilistic Residual Finite Automata. In P. Adriaans ; H. Fernau ; M. van Zaanen (ed.), Grammatical Inference: Algorithms and Applications (p. p. 77-91). Springer-Verlag.
Papier de conférence
Kermorvant, C., & Dupont, P. (2002). Mélanges de Chaînes de Markov lissées pour la détection de domaines dans les protéines. Proceedings des Journées ouvertes biologie informatique mathématique, Saint-Malo, France.
2001
Papier de conférence
Kermorvant, C., & Dupont, P. (2001). Inférence d’automates et correction d’erreurs pour la classification des protéines. Conférence d’Apprentissage, Grenoble.
González, J., Juan, A., Dupont, P., Vidal, E., & Casacuberta, F. (2001). A Bernoulli mixture model for word categorisation. Proceedings of Simposium Nacional de Reconocimiento de Formas y Análisis de Imágenes, Benicàssim (Spain).
2000
Chapitre de livre
Thollard, F., Dupont, P., & de la Higuera, C. (2000). Probabilistic DFA Inference using Kullback-Leibler Divergence and Minimality. In Pat Langley (ed.), International Conference on Machine Learning (p. p. 975 - 982). Morgan Kauffman.
Dupont, P., & Amengual, J.-C. (2000). Smoothing probabilistic automata: an error-correcting approach. In Arlindo L. Oliveira (ed.), Grammatical Inference: Algorithms and Applications (p. p. 51-64). Springer-Verlag.
Papier de conférence
Thollard, F., & Dupont, P. (2000). Inférence Grammaticale Probabiliste utilisant la divergence de Kullback-Leibler et un principe de minimalité. Conférence d’Apprentissage, Saint-Etienne, France.
1999
Papier de conférence
Thollard, F., & Dupont, P. (1999). Entropie relative et algorithmes d’inférence grammaticale probabiliste. Conférence d’apprentissage, Palaiseau, France.
Miclet, L., Chodorowski, J., & Dupont, P. (1999). Apprentissage et évaluation de modèles de langage par des techniques de correction d’erreurs. Conférence d’Apprentissage, Palaiseau, France.
Article de journal
Boë, L.-J., Bimbot, F., Bonastre, J.-F., & Dupont, P. (1999). Des évaluations des systèmes de vérification du locuteur à la mise en cause des expertises vocales en identification juridique. Cahiers d’Etudes et de Recherches Francophones. Langues, 2(4), 270-288. (Original work published 1999)
1998
Chapitre de livre
Dupont, P., & Chase, L. (1998). Using symbol clustering to improve probabilistic automaton inference. In Vasant Honavar, Giora Slutzki (ed.), Grammatical Inference, Ames, Iowa, USA, July 12-14, 1998 (p. p. 232 - 243). Springer-Verlag.
Article de journal
Dupont, P., & Miclet, L. (1998). Inférence grammaticale régulière : fondements théoriques et principaux algorithmes. Institut National de Recherche en Informatique et en Automatique. Rapports de Recherche, 3449, 1-83. (Original work published 1998)
1997
Document de travail
Dupont, P., & Rosenfeld, R. (1997). Lattice based language models.
Dupont, P. (1997). Polynomial regular inference (Technical report EURISE 9705).
1996
Chapitre de livre
Dupont, P. (1996). Incremental Regular Inference. In Laurent Miclet, Colin de la Higuera (ed.), Grammatical Inference: learning syntax from sentences (p. p. 222 -- 237). Springer-Verlag.
1995
Papier de conférence
Miclet, L., Dupont, P., & Vial, S. (1995). Inférence Grammaticale Régulière : méthodes semi-itératives et mesure de performance. Journées Francophones d’Apprentissage, Grenoble, France.
Sadek, D., Bretier, P., Cadoret, V., Cozannet, P., Dupont, P., Ferrieux, A., & Panaget, F. (1995). 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.
Dupont, P. (1995). Interpolated Word and Class Bigram Models for Spanish Conversational Speech Recognition. IEEE Workshop on Automatic Speech Recognition, Snowbird, Utah, USA.
1994
Chapitre de livre
Dupont, P. (1994). Regular Grammatical Inference from Positive and Negatives Samples by Genetic Search : the GIG method. In R. Carrasco, J. Oncina (ed.), Grammatical Inference and Applications, Alicante, Spain, September 21-23, 1994 (p. p. 236--245). Springer-Verlag.
Dupont, P., Miclet, L., & Vidal, E. (1994). What is the search space of Regular Inference? In R. Carrasco, J. Oncina (ed.), Grammatical Inference and Applications, Alicante, Spain, September 21-23, 1994 (p. p. 25-37). Springer-Verlag.
Papier de conférence
Dupont, P., & Pinson, F. (1994). Inférence Grammaticale Régulière par Optimisation Génétique à partir d’échantillons positifs et négatifs : la méthode GIG. Journées Francophones d’Apprentissage, Strasbourg, France.
1993
Papier de conférence
Dupont, P. (1993). Dynamic Use of Syntactical Knowledge in Continuous Speech Recognition. Proceedings European Conference on Speech Communication and Technology, Berlin, Germany.
Chapitre de livre
Dupont, P. (1993). Efficient Integration of Context-Free Based Language Models in Continuous Speech Recognition. In A. Rubio Ayuso, J. López Soler (ed.), New Advances and Trends in Speech Recognition and Coding (p. p. 179-182). Springer -Verlag.
1991
Chapitre de livre
Dupont, P., & Kamp, Y. (1991). Guiding Speech Recognition by a Language Model. In André Thayse (ed.), From Natural Language Processing to Logic for Expert Systems (p. p. 1-48). John Wiley & Sons.
1990
Article de journal
Dupont, P., & Thayse, A. (1990). Montague’s Semantics and Boolean Semantics for Natural Language Representation. Philips Journal of Research, 45(1), 41-66. (Original work published 1990)
Chapitre de livre
Dupont, P., & Kamp, Y. (1990). Reconnaissance de la parole pilotée par un modèle linguistique. In André Thayse (ed.), Approche logique de l’intelligence artificielle. 3. Du traitement de la langue à la logique des systèmes experts (p. p. 1-61). Bordas.