Co-auteurs

Nombre de documents

140

PhL


Article dans une revue15 documents

  • Mouna Ben Ishak, Philippe Leray, Nahla Ben Amor. Probabilistic relational model benchmark generation: Principle and application. Intelligent Data Analysis, IOS Press, 2016, 20 (3), pp.615-635. 〈hal-01150688〉
  • Montassar Ben Messaoud, Philippe Leray, Nahla Ben Amor. SemCaDo: A serendipitous strategy for causal discovery and ontology evolution. Knowledge-Based Systems, Elsevier, 2015, 76, pp.79-95. 〈10.1016/j.knosys.2014.12.006〉. 〈hal-01113245〉
  • Maroua Haddad, Philippe Leray, Nahla Ben Amor. Apprentissage des réseaux possibilistes à partir de données. Revue des Sciences et Technologies de l'Information - Série RIA : Revue d'Intelligence Artificielle, Lavoisier, 2015, 29 (2), pp.229-252. 〈hal-01166897〉
  • Aida Jarraya, Philippe Leray, Afif Masmoudi. Implicit parameter estimation for conditional gaussian bayesian networks. International Journal of Computational Intelligence Systems, Atlantis Press, 2014, 7 (Supplement 1), pp.6-13. 〈hal-00864152〉
  • Aida Jarraya, Philippe Leray, Afif Masmoudi. Discrete exponential bayesian networks : definition, learning and application for density estimation. Neurocomputing, Elsevier, 2014, Advanced Intelligent Computing Theories and Methodologies — Selected papers from the 2012 Eighth International Conference on Intelligent Computing (ICIC 2012), Volume 137, pp.142-149. 〈10.1016/j.neucom.2013.05.061〉. 〈hal-00864150〉
  • Raphaël Mourad, Christine Sinoquet, N. Zhang, T. Liu, Philippe Leray. A survey on latent tree models and applications. Journal of Artificial Intelligence Research, Association for the Advancement of Artificial Intelligence, 2013, 47, pp.157-203. 〈hal-00828445〉
  • Raphaël Mourad, Christine Sinoquet, Philippe Leray. Probabilistic graphical models for genetic association studies. Briefings in Bioinformatics, Oxford University Press (OUP), 2012, 13 (1), pp.20-33. 〈10.1093/bib/BBR015〉. 〈hal-00573325〉
  • Raphaël Mourad, Christine Sinoquet, Christian Dina, Philippe Leray. Visualization of pairwise and multilocus linkage disequilibrium structure using latent forests.. PLoS ONE, Public Library of Science, 2011, 6 (12), pp.e27320. 〈10.1371/journal.pone.0027320〉. 〈hal-00655876〉
  • Raphaël Mourad, Christine Sinoquet, Philippe Leray. A hierarchical Bayesian network approach for linkage disequilibrium modeling and data-dimensionality reduction prior to genome-wide association studies.. BMC Bioinformatics, BioMed Central, 2011, 12 (1), pp.16. 〈10.1186/1471-2105-12-16〉. 〈hal-00567988〉
  • Karim Tabia, Philippe Leray. Alert correlation: Severe attack prediction and controlling false alarm rate tradeoffs. Intelligent Data Analysis, IOS Press, 2011, 15 (6), pp.?-?. 〈hal-00568027〉
  • Roland Donat, Philippe Leray, Laurent Bouillaut, Patrice Aknin. A dynamic bayesian network to represent discrete duration models. Neurocomputing / EEG Neurocomputing, Elsevier, 2010, 73 (4-6), pp.570-577. 〈hal-00425443〉
  • Stijn Meganck, Philippe Leray, Bernard Manderick. Causal discovery in non-ideal frameworks. Information interaction intelligence. Revue I3 - Information Interaction Intelligence, Cépaduès, 2009, 9 (1), pp.11-45. 〈hal-00476126〉
  • Hoai-Tuong Nguyen, Gérard Ramstein, Philippe Leray, Yannick Jacques. Reconstruction of gene regulation networks from microarray data by Bayesian networks. MODGRAPH - Journées Ouvertes en Biologie, Informatique et Mathématiques (JOBIM), 2009, pp.42-46. 〈hal-00582682〉
  • Philippe Leray, Patrick Gallinari. De l'utilisation d'OBD pour la sélection de variables dans les Perceptrons Multi-couches. Revue des Sciences et Technologies de l'Information - Série RIA : Revue d'Intelligence Artificielle, Lavoisier, 2001, 15 (3-4), pp.373-391. 〈10.3166/ria.15.373-391〉. 〈hal-01176949〉
  • Philippe Leray, Patrick Gallinari. Feature extraction with neural networks. Behaviormetrika, Behaviormetric Society of Japan, 1999, 26 (1), pp.145-166. 〈10.2333/bhmk.26.145〉. 〈hal-01184481〉

Communication dans un congrès104 documents

  • Youssef Benhaddou, Philippe Leray. Customer relationship management and small data - application of bayesian network elicitation techniques for building a lead scoring model. 14th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA 2017), 2017, Hammamet, Tunisia. 〈hal-01619307〉
  • Marwa El Abri, Philippe Leray, Nadia Essoussi. Learning probabilistic relational models with (partially structured) graph databases. 14th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA 2017), 2017, Hammamet, Tunisia. 〈hal-01619318〉
  • Maroua Haddad, Philippe Leray, Nahla Ben Amor. Possibilistic MDL: a new possibilistic likelihood based score function for imprecise data. Fourteenth European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2017), 2017, Lugano, Switzerland. Proceedings of the Fourteenth European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2017). 〈hal-01532488〉
  • Karim Tabia, Amélie Levray, Maroua Haddad, Philippe Leray. Learning the parameters of possibilistic networks from data: Empirical comparison. Thirtieth International Florida Artificial Intelligence Research Society Conference (FLAIRS 30), 2017, Marco Island, United States. Proceedings of the Thirtieth International Florida Artificial Intelligence Research Society Conference (FLAIRS 30). 〈hal-01532494〉
  • Thierno Kante, Philippe Leray. A probabilistic relational model approach for fault trees modeling. 30th International Conference on Industrial, Engineering, Other Applications of Applied Intelligent Systems (IEA/AIE 2017), 2017, Arras, France. Proceedings of the 30th International Conference on Industrial, Engineering, Other Applications of Applied Intelligent Systems (IEA/AIE 2017). 〈hal-01532490〉
  • Romain Rincé, Romain Kervarc, Philippe Leray. On the use of walkSAT based algorithms for MLN inference in some realistic applications. 30th International Conference on Industrial, Engineering, Other Applications of Applied Intelligent Systems (IEA/AIE 2017), 2017, Arras, France. Proceedings of the 30th International Conference on Industrial, Engineering, Other Applications of Applied Intelligent Systems (IEA/AIE 2017). 〈hal-01532492〉
  • Nourhene Ettouzi, Philippe Leray, Montassar Ben Messaoud. An exact approach to learning probabilistic relational model. 8th International Conference on Probabilistic Graphical Models (PGM 2016), 2016, Lugano, Switzerland. pp.171-182, Proceedings of the 8th International Conference on Probabilistic Graphical Models (PGM 2016). 〈hal-01347804〉
  • Toader Gherasim, Bouthayna Ed-Dahmouni, Philippe Leray. Détection et prédiction de défaillances dans un parc d'éoliennes à l'aide de réseaux bayésiens. 8èmes journées francophones de réseaux bayésiens (JFRB 2016), 2016, Clermont-Ferrand, France. 〈hal-01347808〉
  • Maroua Haddad, Philippe Leray, Amélie Levray, Karim Tabia. Possibilistic networks parameter learning: Preliminary empirical comparison. 8èmes journées francophones de réseaux bayésiens (JFRB 2016), 2016, Clermont-Ferrand, France. pp.?-?. 〈hal-01347810〉
  • Mouna Ben Ishak, Philippe Leray, Nahla Ben Amor. A hybrid approach for probabilistic relational models structure learning. 15th International Symposium on Intelligent Data Analysis (IDA 2016), 2016, Stockholm, Sweden. pp.?-?, 216, In Proceedings of the 15th International Symposium on Intelligent Data Analysis (IDA 2016). 〈hal-01347798〉
  • Mouna Rifi, Philippe Leray. État de l’art des méthodes de détections de communautés dans les réseaux bipartis binaires et pondérés.. In 7ème édition du colloque bisannuel Apprentissage Artificiel & Fouille de Données (AAFD) et 23èmes Rencontres annuelles de la Société Francophone de Classification (SFC), 2016, Marrakech, Maroc. pp.1-6. 〈hal-01348300〉
  • Anthony Coutant, Hoel Le Capitaine, Leray Philippe. On the equivalence between regularized NMF and similarity-augmented graph partitioning. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Apr 2015, Bruges, Belgium. Proceedings of the 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN) Conference, 2015. 〈hal-01183562〉
  • Anthony Coutant, Leray Philippe, Hoel Le Capitaine. Probabilistic Relational Models with Clustering Uncertainty. International Joint Conference on Neural Networks (IJCNN), Jul 2015, Killarney, Ireland. 2015, Proceedings of the 2015 International Joint Conference on Neural Networks (IJCNN) Conference. 〈hal-01183563〉
  • Duc-Thanh Phan, Philippe Leray, Christine Sinoquet. Impact du choix de la méthode de partitionnement pour les forêts d'arbres latents. SFC2015, Sep 2015, Nantes, France. Proc. SFC 2015, XXIIth Join Meeting of the French Society of Classification, pp.24-27. 〈hal-01205544〉
  • Maroua Haddad, Philippe Leray, Nahla Ben Amor. Learning possibilistic networks from data: a survey.. 16th World Congress of the International Fuzzy Systems Association (IFSA) and the 9th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), 2015, Gijon, Spain. 〈hal-01150815〉
  • Maroua Haddad, Philippe Leray, Nahla Ben Amor. Evaluating product-based possibilistic networks learning algorithms. 13th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2015), 2015, Compiègne, France. 〈hal-01150813〉
  • Anthony Coutant, Hoel Le Capitaine, Philippe Leray. On the equivalence between regularized nmf and similarity-augmented graph partitioning. 23th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2015), 2015, Bruges, Belgium. 〈hal-01150691〉
  • Gérard Ramstein, Philippe Leray. CPD tree learning using contexts as background knowledge. 13th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2015), 2015, Compiègne, France. 〈hal-01150694〉
  • Anthony Coutant, Hoel Le Capitaine, Philippe Leray. Probabilistic relational models with clustering uncertainty. IEEE International Joint Conference on Neural Networks (IJCNN 2015), 2015, Killarney, Ireland. 〈hal-01150692〉
  • Rajani Chulyadyo, Philippe Leray. Integrating spatial information into probabilistic relational model. 2015 IEEE International Conference on Data Science and Advanced Analytics (IEEE DSAA'2015), 2015, Paris, France. pp.? - ?, Proceedings of 2015 IEEE International Conference on Data Science and Advanced Analytics (IEEE DSAA'2015). 〈hal-01201226〉
  • Duc-Thanh Phan, Philippe Leray, Christine Sinoquet. Modeling genetical data with forests of latent trees for applications in association genetics at a large scale. Which clustering method should be chosen?. International Conference on Bioinformatics Models, Methods and Algorithms, Bioinformatics2015, Nov 2014, Lisbon, Portugal. International Conference on Bioinformatics Models, Methods and Algorithms, Bioinformatics2015, Portugal, Lisbon, 12-15 january, pp.12, 2015, Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms, Bioinformatics2015. 〈hal-01084907〉
  • Mouna Ben Ishak, Leray Philippe, Nahla Ben Amor. Random generation and population of probabilistic relational models and databases. 26th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2014), Nov 2014, Limassol, Cyprus. pp.?-?, 2014. 〈hal-01084510〉
  • Rajani Chulyadyo, Philippe Leray. A Personalized Recommender System from Probabilistic Relational Model and Users’ Preferences. Knowledge-Based and Intelligent Information & Engineering Systems 18th Annual Conference, KES-2014, Sep 2014, Gdynia, Poland. 35, pp.1063-1072, 2014, Procedia Computer Science. 〈10.1016/j.procs.2014.08.193〉. 〈hal-01084449〉
  • Anthony Coutant, Leray Philippe, Hoel Le Capitaine. Learning Probabilistic Relational Models Using Non-Negative Matrix Factorization. International Florida Artificial Intelligence Research Society (FlAIRS) Conference, May 2014, Pensacola Beach, Floride, United States. Proceedings of the 27th International Florida Artificial Intelligence Research Society (FlAIRS) Conference, 2014. 〈hal-01183565〉
  • Anthony Coutant, Philippe Leray, Hoel Le Capitaine. Apprentissage de modèles relationnels probabilistes par factorisation non-négative de matrices. 7èmes journées francophones sur les réseaux bayésiens (JFRB 2014), 2014, Paris, France. 〈hal-01005777〉
  • Mouna Ben Ishak, Philippe Leray, Nahla Ben Amor. La génération aléatoire de réseaux bayésiens relationnels. 7ème journées francophones sur les réseaux bayésiens (JFRB 2014), 2014, Paris, France. 〈hal-01005772〉
  • Maroua Haddad, Nahla Ben Amor, Philippe Leray. Apprentissage des réseaux possibilistes à partir de données: un survol. 7èmes journées francophones sur les réseaux bayésiens (JFRB 2014), 2014, Paris, France. 〈hal-01005780〉
  • Ghada Trabelsi, Philippe Leray, Mounir Ben Ayed, Adel Alimi. Évaluation des algorithmes d'apprentissage de structure pour les réseaux bayésiens dynamiques.. 7èmes journées francophones sur les réseaux bayésiens (JFRB 2014), 2014, Paris, France. 〈hal-01005775〉
  • Anthony Coutant, Philippe Leray, Hoel Le Capitaine. Learning Probabilistic Relational Models using Non-Negative Matrix Factorization. The 27th International FLAIRS Conference, Uncertain Reasoning Special Track, May 2014, Pensacola Beach, Florida, United States. pp.? - ?, 2014, 〈http://www.aaai.org/ocs/index.php/FLAIRS/FLAIRS14/paper/view/7809〉. 〈hal-00958394〉
  • Aymeric Le Dorze, Béatrice Duval, Laurent Garcia, David Genest, Philippe Leray, et al.. Probabilistic Cognitive Maps Semantics of a Cognitive Map when the Values are Assumed to be Probabilities. International Conference on Agents and Artificial Intelligence (ICAART), 2014, Angers, France. pp.52-62, 2014. 〈hal-00957935〉
  • Philippe Leray. Advances in Learning with Bayesian Networks. 6th International Conference on Agents and Artificial Intelligence (ICAART 2014), Mar 2014, Angers, France. 〈hal-00957937〉
  • Mouna Ben Ishak, Rajani Chulyadyo, Ahmed Abdelwahab, Miriam Ramirez, Philippe Leray, et al.. Relational bayesian networks for recommender systems: review and comparative study. ENBIS-SFdS Spring Meeting on graphical causality models: Trees, Bayesian Networks and Big Data, Apr 2014, Paris, France. 〈hal-00957940〉
  • Edern Menou, Franck Tancret, Philippe Leray. New data mining techniques in materials science: Bayesian networks to predict the yield stress of Ni-base superalloys. TMS2014, 143rd Annual Meeting & Exhibition, 2014, San Diego, United States. 〈hal-01016497〉
  • Franck Tancret, Philippe Leray, Edern Menou. Bayesian networks in materials science: new tools to predict the properties of materials. TMS2014 - 143rd Annual Meeting & Exhibition, 2014, San Diego, United States. 〈hal-01016503〉
  • Anthony Coutant, Philippe Leray, Hoel Le Capitaine. Learning Probabilistic Relational Models using co-clustering methods. Structured Learning: Inferring Graphs from Structured and Unstructured Inputs (SLG 2013) ICML Workshop, 2013, Atlanta, United States. 〈hal-00819031〉
  • Christine Sinoquet, Raphaël Mourad, Philippe Leray. Modeling of genotype data with forests of latent trees to detect genetic causes of diseases. Ado2013 (Machine Learning and Omics Data), Dec 2013, Lille, France. 6 p. 〈hal-00915538〉
  • Montassar Ben Messaoud, Philippe Leray, Nahla Ben Amor. Active learning of causal bayesian networks using ontologies: a case study. International Joint Conference on Neural Networks, 2013, United States. pp.?-?, 2013. 〈hal-00864156〉
  • Ghada Trabelsi, Philippe Leray, Mounir Ben Ayed, Adel Alimi. Dynamic MMHC: a local search algorithm for dynamic bayesian network structure learning. International Symposium on Intelligent Data Analysis, 2013, London, United Kingdom. pp.?-?, 2013. 〈hal-00864162〉
  • Maroua Haddad, Nahla Ben Amor, Philippe Leray. Imputation of possibilistic data for structural learning of directed acyclic graphs Genova, Italy.. International Workshop on Fuzzy Logic and Applications, 2013, Italy. pp.?-?, 2013. 〈hal-00864157〉
  • Aymeric Le Dorze, Béatrice Duval, Laurent Garcia, David Genest, Philippe Leray, et al.. Probabilistic cognitive maps. Septièmes Journées de l'Intelligence Artificielle Fondamentale (JIAF), 2013, Aix en provence, France. 〈hal-00828271〉
  • Mouna Ben Ishak, Nahla Ben Amor, Philippe Leray. A relational Bayesian network-based recommender system architecture. International Conference on Modeling, Simulation and Applied Optimization (ICMSAO 2013), 2013, Tunisia. pp.1-6, 2013, 〈10.1109/ICMSAO.2013.6552609〉. 〈hal-00812168〉
  • Amanullah Yasin, Philippe Leray. Incremental bayesian network structure learning in high dimensional domains. International Conference on Modeling, Simulation and Applied Optimization (ICMSAO 2013), 2013, Hammamet, Tunisia. pp.1-6, 2013, 〈10.1109/ICMSAO.2013.6552635〉. 〈hal-00812175〉
  • Ghada Trabelsi, Philippe Leray, Mounir Ben Ayed, Adel Alimi. Benchmarking dynamic bayesian network structure learning algorithms. International Conference on Modeling, Simulation and Applied Optimization (ICMSAO 2013), 2013, Hammamet, Tunisia. pp.1-6, 2013, 〈10.1109/ICMSAO.2013.6552549〉. 〈hal-00812171〉
  • François Schnitzler, Sourour Ammar, Philippe Leray, Pierre Geurts, Louis Wehenkel. Approximation efficace de mélanges bootstrap d'arbres de markov pour l'estimation de densité.. Conférence francophone sur l'Apprentissage Automatique, 2012, Nancy, France. pp.16, 2012. 〈hal-00700464〉
  • Christine Sinoquet, Raphaël Mourad, Philippe Leray. Forests of latent tree models for the detection of genetic associations. International Conference on Bioinformatics Models, Methods and Algorithms (BIOINFORMATICS 2012), Feb 2012, Vilamoura, Portugal. pp.1-10, 2012. 〈hal-00637500〉
  • Aida Jarraya, Philippe Leray, Afif Masmoudi. Discrete exponential bayesian networks structure learning for density estimation. International Conference on Intelligent Computing, 2012, China. pp.?-?, 2012. 〈hal-00691834〉
  • Aida Jarraya, Philippe Leray, Afif Masmoudi. A new implicit parameter estimation for conditional gaussian bayesian networks. Uncertainty Modeling in Knowledge Engineering and Decision Making, 2012, Istanbul, Turkey. pp.?-?, 2012. 〈hal-00691835〉
  • François Schnitzler, Sourour Ammar, Philippe Leray, Pierre Geurts, Louis Wehenkel. Approximation efficace de mélanges bootstrap d'arbres de Markov pour l'estimation de densité. Laurent Bougrain. Conférence Francophone sur l'Apprentissage Automatique - CAp 2012, May 2012, Nancy, France. 16 p., 2012, Actes de la Conférence Francophone sur l'Apprentissage Automatique - CAp 2012. 〈hal-00745501〉
  • Amanullah Yasin, Philippe Leray. Local Skeleton Discovery for Incremental Bayesian Network Structure Learning. Proc. IEEE Int Conference on Computer Networks and Information Technology (ICCNIT), Jul 2011, Peshawar, Pakistan. 〈hal-00595152〉
  • Montassar Ben Messaoud, Philippe Leray, Nahla Ben Amor. SemCaDo: a serendipitous causal discovery algorithm for ontology evolution. The IJCAI-11 Workshop on Automated Reasoning about Context and Ontology Evolution, Jul 2011, Barcelone, Spain. 〈hal-00596261〉
  • Montassar Ben Messaoud, Philippe Leray, Nahla Ben Amor. SemCaDo: a serendipitous strategy for learning causal bayesian networks using ontologies. The 11th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, Jun 2011, Belfast, Ireland. pp.182-193. 〈hal-00596260〉
  • Mouna Ben Ishak, Philippe Leray, Nahla Ben Amor. A two-way approach for probabilistic graphical models structure learning and ontology enrichment.. KEOD 2011, 2011, France. pp.?-?, 2011. 〈hal-00644993〉
  • Aida Jarraya, Philippe Leray, Afif Masmoudi. Discrete exponential bayesian networks: an extension of bayesian networks to discrete natural exponential families. ICTAI 2011, 2011, Palm Beach County, United States. pp.?-?, 2011. 〈hal-00645003〉
  • Amanullah Yasin, Philippe Leray. immpc: A local search approach for incremental bayesian network structure learning. IDA 2011, 2011, Porto, Portugal. pp.401-412, 2011. 〈hal-00645014〉
  • Montassar Ben Messaoud, Philippe Leray, Nahla Ben Amor. Semcado: a serendipitous causal discovery algorithm for ontology evolution. ARCOE 2011, 2011, Spain. pp.43-47, 2011. 〈hal-00645000〉
  • Mouna Ben Ishak, Philippe Leray, Nahla Ben Amor. Ontology-based generation of object oriented bayesian networks. BMAW 2011, 2011, Spain. pp.9-17, 2011. 〈hal-00644992〉
  • François Schnitzler, Sourour Ammar, Philippe Leray, Pierre Geurts, Louis Wehenkel. Efficiently approximating markov tree bagging for high-dimensional density estimation. ECML-PKDD 2011, 2011, Athens, Greece. pp.113-128, 2011. 〈hal-00645009〉
  • Hoai-Tuong Nguyen, Philippe Leray, Gérard Ramstein. Summarizing and visualizing a set of bayesian networks with quasi essential graphs. ASMDA 2011, 2011, Italy. pp.?-?, 2011. 〈hal-00645005〉
  • Sourour Ammar, Philippe Leray. Mixture of markov trees for bayesian network structure learning with small datasets in high dimensional space. ECSQARU 2011, 2011, Belfast, Ireland. pp.229-238, 2011. 〈hal-00644991〉
  • Hoai-Tuong Nguyen, Philippe Leray, Gérard Ramstein. Multiple hypothesis testing and quasi essential graph for comparing two sets of bayesian networks. KES 2011, 2011, Kaiserslautern, Germany. pp.?-?, 2011. 〈hal-00645006〉
  • Montassar Ben Messaoud, Nahla Ben Amor, Philippe Leray. L'intégration des connaissances ontologiques pour l'apprentissage des réseaux bayesiens causaux. 5èmes Journées Francophones sur les Réseaux Bayésiens (JFRB2010), May 2010, Nantes, France. 〈hal-00474395〉
  • Sourour Ammar, Philippe Leray, Louis Wehenkel. Mélanges sous-quadratiques d'arbres de Markov pour l'estimation de la densité de probabilité. 5èmes Journées Francophones sur les Réseaux Bayésiens (JFRB2010), May 2010, Nantes, France. 〈hal-00474295〉
  • Karim Tabia, Philippe Leray, Ludovic Mé. From redundant/irrelevant alert elimination to handling idss' reliability and controlling severe attack prediction/false alarm rate tradeoffs. 5th Conference on Network and Information Systems Security (SARSSI'10), 2010, Rocquebrune Cap-Martin, France. 〈hal-00870800〉
  • Karim Tabia, Philippe Leray, Ludovic Mé. From redundant/irrelevant alert elimination to handling IDSes reliability and controlling severe attack prediction/false alarm rate tradeoffs. 5ème Conférence sur la sécurité des architectures réseaux et systèmes d'information, May 2010, Menton, France. pp.NC, 2010. 〈hal-00534569〉
  • Raphaël Mourad, Christine Sinoquet, Philippe Leray. Apprentissage de réseaux bayésiens hiérarchiques latents pour les études d'association pangénomiques. Proc. JFRB 2010, 5th French-speaking meeting on Bayesian networks, Nantes, May 2010, Nantes, France. pp.11-12. 〈hal-00484706〉
  • Raphaël Mourad, Christine Sinoquet, Philippe Leray. Learning Hierarchical Bayesian Networks for Genome-Wide Association Studies. COMPSTAT, Nineteenth International Conference on Computational Statististics, Aug 2010, Paris, France. pp.549-556, 2010. 〈hal-00484696〉
  • Raphaël Mourad, Christine Sinoquet, Philippe Leray. Réseaux bayésiens hiérarchiques avec variables latentes pour la modélisation des dépendances entre SNP: une approche pour les études d'association pangénomiques. Proc. SFC 2010, XVIIth Join Meeting of the French Society of Classification, France, Saint-Denis de la Réunion, 9-11 june, Jun 2010, Saint-Denis de la Réunion, France. pp.25-29. 〈hal-00484705〉
  • Raphaël Mourad, Christine Sinoquet, Philippe Leray. Apprentissage de réseaux bayésiens hiérarchiques latents pour les études d'association pangénomiques. 5èmes Journées Francophones sur les Réseaux Bayésiens (JFRB2010), May 2010, Nantes, France. 〈hal-00467399〉
  • Karim Tabia, Philippe Leray. Handling idss' reliability in alert correlation: A bayesian network-based model for handling IDS's reliability and controlling prediction/false alarm rate tradeoffs. International Conference on Security and Cryptography (SECRYPT'10), 2010, Athens, Greece. SciTePress, pp.14-24, 2010. 〈hal-00866587〉
  • François Schnitzler, Philippe Leray, Louis Wehenkel. Vers un apprentissage subquadratique pour les mélanges d'arbres. 5èmes Journées Francophones sur les Réseaux Bayésiens (JFRB2010), May 2010, Nantes, France. 〈hal-00467066〉
  • Karim Tabia, Philippe Leray. Approches basées sur les réseaux Bayésiens pour la prédiction d'attaques sévères. 5èmes Journées Francophones sur les Réseaux Bayésiens (JFRB2010), May 2010, Nantes, France. 〈hal-00467656〉
  • Raphaël Mourad, Christine Sinoquet, Philippe Leray. Hierarchical Bayesian networks applied to association genetics. MODGRAPH 2010 (Modèles graphiques probabilistes pour l'intégration de données hétérogènes et la découverte de modèles causaux en biologie), Journée satellite de JOBIM 2010, Sep 2010, Montpellier, France. 〈hal-00915546〉
  • François Schnitzler, Philippe Leray, Louis Wehenkel. Towards sub-quadratic learning of probability density models in the form of mixtures of trees. ESANN 2010, 2010, Bruges, Belgium. pp.219-224, 2010. 〈hal-00487354〉
  • Sourour Ammar, Philippe Leray, Louis Wehenkel. Sub-quadratic markov tree mixture models for probability density estimation. COMPSTAT 2010, 2010, Paris, France. pp.?-?, 2010. 〈hal-00487353〉
  • Karim Tabia, Philippe Leray. Handling IDS' reliability in alert correlation: A Bayesian network-based model for handling IDS's reliability and controlling prediction/false alarm rate tradeoffs. International Conference on Security and Cryptography (SECRYPT'2010), Jul 2010, Athène, Greece. pp.11, 2010. 〈hal-00481054〉
  • Karim Tabia, Philippe Leray. Bayesian network-based approaches for severe attack prediction and handling IDSs' reliability. International Conference on Information Processing and Management of Uncertainty (IPMU'10), Jun 2010, Dortmund, Germany. pp.12, 2010. 〈hal-00481056〉
  • Karim Tabia, Philippe Leray, Ludovic Mé. From redundant/irrelevant alert elimination to handling IDSs' reliability and controlling severe attack prediction/false alarm rate tradeoffs. Fifth Conference on Network and Information Systems Security (SARSSI 2010), May 2010, Nice, France. pp.15, 2010. 〈hal-00481061〉
  • Sourour Ammar, Philippe Leray, François Schnitzler, Louis Wehenkel. Sub-quadratic Markov tree mixture learning based on randomizations of the Chow-Liu algorithm. PGM 2010, Sep 2010, Helsinki, Finland. pp.17-25, 2010. 〈hal-00568028〉
  • Hoai-Tuong Nguyen, Gérard Ramstein, Leray Philippe, Yannick Jacques. Differential study of the cytokine network in the immune system: An evolutionary approach based on the Bayesian networks. The 2nd Asian Conference on Intelligent Information and Database Systems (ACIIDS), Mar 2010, Hue City, Vietnam. pp.?-?, 2010. 〈hal-00656723〉
  • Raphaël Mourad, Christine Sinoquet, Philippe Leray. Modélisation des dépendances locales entre SNP à l'aide d'un réseau bayésien. Gérard d'Aubigny. Proc. SFC'09, XVIth Join Meeting of the French Society of Classification, actes des 16èmes rencontres de la Société Francophone de Classification, Sep 2009, Grenoble, France. pp.169-172, 2009. 〈hal-00423461〉
  • Sourour Ammar, Philippe Leray, Boris Defourny, Louis Wehenkel. Probability density estimation by perturbing and combining tree structured markov networks. CAp 2009, 2009, Hammamet, Tunisia. pp.65-79, 2009. 〈hal-00412883〉
  • Montassar Ben Messaoud, Philippe Leray, Nahla Ben Amor. Integrating ontological knowledge for iterative causal discovery and vizualisation. Workshop on Machine Learning and Visualization, 2009, Hammamet, Tunisia. 〈hal-00412890〉
  • Sourour Ammar, Philippe Leray, Boris Defourny, Louis Wehenkel. Probability density estimation by perturbing and combining tree structured markov networks. ECSQARU 2009, 2009, Verona, Italy. pp.156-167, 2009. 〈hal-00412283〉
  • Montassar Ben Messaoud, Philippe Leray, Nahla Ben Amor. Integrating ontological knowledge for iterative causal discovery and vizualisation. ECSQARU 2009, 2009, Verona, Italy. pp.168-179, 2009. 〈hal-00412286〉
  • Raphaël Mourad, Christine Sinoquet, Philippe Leray. A Bayesian network approach to model local dependencies among SNPs. MODGRAPH 2009 Probabilistic graphical models for integration of complex data and discovery of causal models in biology, satellite meeting of JOBIM 2009, Jun 2009, Nantes, France. 〈hal-00470528〉
  • Roland Donat, Philippe Leray, Laurent Bouillaut, Patrice Aknin. Réseaux bayésiens dynamiques pour la représentation de modèles de durée en temps discret. Journées Francophone sur les Réseaux Bayésiens, May 2008, Lyon, France. 〈hal-00259009〉
  • Stijn Meganck, Philippe Leray, Bernard Manderick. UnCaDo: Unsure Causal Discovery. Journées Francophone sur les Réseaux Bayésiens, May 2008, Lyon, France. 〈hal-00259692〉
  • Olivier François, Laurent Bouillaut, Patrice Aknin, Philippe Leray, S. Dubois. Approche semi-markovienne pour la modélisation de stratégies de maintenance: application à la prévention de rupture du rail. MOSIM'2008, 2008, Paris, France. pp.CDROM, 2008. 〈hal-00412887〉
  • Laurent Bouillaut, Roland Donat, Patrice Aknin, Philippe Leray. Approches markovienne et semi-markovienne pour la modélisation de la fiabilité et des actions de maintenance d'un système ferroviaire. Workshop Surveillance, Sûreté et Sécurité des Grands Systèmes (3SGS'08), 2008, Troyes, France. 〈hal-00412902〉
  • Ahmad Faour, Philippe Leray, Bassam Eter. Evolutivité d'une architecture en temps réel de filtrage d'alertes générées par les systèmes de détection d'intrusions sur les réseaux. RFIA 2008, 2008, Amiens, France. pp.CDROM, 2008. 〈hal-00412885〉
  • Sourour Ammar, Philippe Leray, Boris Defourny, Louis Wehenkel. Density estimation with ensembles of randomized poly-trees. BENELEARN 2008, May 2008, Spa, Belgium. pp.31-32, 2008. 〈hal-00568050〉
  • Sourour Ammar, Philippe Leray, Louis Wehenkel. Estimation de densité par ensembles aléatoires de poly-arbres. Journées Francophone sur les Réseaux Bayésiens, May 2008, Lyon, France. 〈hal-00259868〉
  • Sourour Ammar, Philippe Leray, Boris Defourny, Louis Wehenkel. High-dimensional probability density estimation with randomized ensembles of tree structured bayesian networks. PGM 2008, 2008, Hirtshals, Denmark. pp.9-16, 2008. 〈hal-00412288〉
  • Roland Donat, Laurent Bouillaut, Patrice Aknin, Philippe Leray. Reliability analysis using graphical duration models. ARES 2008, 2008, Barcelona, Spain. pp.795-800, 2008. 〈hal-00412299〉
  • Laurent Bouillaut, Olivier François, Philippe Leray, Patrice Aknin, Stéphane Dubois. Dynamic bayesian networks modelling maintenance strategies: Prevention of broken rails. WCCR'08, 2008, Seoul, South Korea. 2008. 〈hal-00412291〉
  • Roland Donat, Laurent Bouillaut, Patrice Aknin, Philippe Leray, Sandrine Bondeux. Specific graphical models for analyzing the reliability. MED'08, 2008, Ajaccio, France. pp.621-626, 2008. 〈hal-00412495〉
  • Olivier François, Philippe Leray. Generation of incomplete test-data using bayesian networks. IJCNN, 2007, Orlando, United States. pp.2391-2396, 2007. 〈hal-00412939〉
  • Ahmad Faour, Philippe Leray, Bassam Eter. Growing hierarchical self-organizing map for alarm filtering in network intrusion detection systems. NTMS'07, 2007, Paris, France. pp.CDROM, 2007. 〈hal-00412943〉
  • Stijn Meganck, Philippe Leray, Bernard Manderick. Causal graphical models with latent variables: Learning and inference. ECSQARU, 2007, Hammamet, Tunisia. pp.5-16, 2007. 〈hal-00412946〉
  • Roland Donat, Laurent Bouillaut, Patrice Aknin, Philippe Leray, D. Levy. A generic approach to model complex system reliability using graphical duration models. Mathematical Methods in Reliability: Methodology and Practice (MMR 2007),, 2007, Glasgow, United Kingdom. 〈hal-00412501〉
  • G. Mallet, Ph. Leray, H. Polaert, C. Tolant, Ph. Eudeline. Dynamic Compact Thermal Model with Neural Networks for Radar Applications. THERMINIC 2006, Sep 2006, Nice, France. TIMA Editions, pp.118-122, 2006. 〈hal-00171366〉
  • Philippe Leray, Hugo Zaragoza, Florence D'Alché-Buc. Pertinence des mesures de confiance en classification. Conférence francophone RFIA, Feb 2000, Paris, France. Conférence francophone RFIA. 〈hal-01573394〉
  • Philippe Leray, Patrick Gallinari. Data Fusion for Diagnosis in a Telecommunication Network. ICANN 1998 - 8th International Conference of Artificial Neural Networks, Sep 1998, Skövde, Sweden. Springer, ICANN 1998 - 8th International Conference of Artificial Neural Networks, pp.767-772, 〈10.1007/978-1-4471-1599-1_118〉. 〈hal-01617480〉
  • Lionel Oisel, Frederic Fleuret, P. Horain, Luce Morin, Jean-Marc Vezien, et al.. Analyse de séquences non calibrées pour la reconstruction 3D de scène. Actes 11ème Congrès AFCET-RFIA (RFIA'98), Jan 1998, Clermont-Ferrand, France. 1, pp.189-198, 1998. 〈hal-00272421〉

Ouvrage (y compris édition critique et traduction)2 documents

  • Patrick Naïm, Pierre-Henri Wuillemin, Philippe Leray, Olivier Pourret, Anna Becker. Réseaux bayésiens. Eyrolles, pp.424, 2007, Algorithmes. 〈hal-00412267〉
  • Patrick Naïm, Pierre-Henri Wuillemin, Philippe Leray, Olivier Pourret, Anna Becker. Réseaux Bayésiens. Eyrolles, pp.224, 2004, Algorithmes. 〈hal-00412269〉

Chapitre d'ouvrage7 documents

  • Duc-Thanh Phan, Philippe Leray, Christine Sinoquet. Latent Forests to Model Genetical Data for the Purpose of Multilocus Genome-wide Association Studies. Which clustering should be chosen?. Communication in Computer and Information Science, Springer, pp.17, 2015, BIOSTEC2015. 〈hal-01204956〉
  • Aymeric Le Dorze, Béatrice Duval, Laurent Garcia, David Genest, Philippe Leray, et al.. A Probabilistic Semantics for Cognitive Maps. Agents and Artificial Intelligence (ICAART revised selected papers), 8946, Springer, pp.151-169, 2015, Lecture Notes in Artificial Intelligence, 〈10.1007/978-3-319-25210-0_10〉. 〈hal-01205961〉
  • Salem Benferhat, Philippe Leray, Karim Tabia. Modèles graphiques pour l'incertitude : inférence et apprentissage. P. Marquis, O. Papini, H. Prade. Panorama de l'Intelligence Artificielle, volume 2: Algorithmes pour l'intelligence artificielle, Cepadues, 26 p., 2014, 9782364930414. 〈hal-01020910〉
  • Christine Sinoquet, Raphaël Mourad, Philippe Leray. Forests of latent tree models to decipher genotype-phenotype associations. J. Gariel, J. Schier, S. Van Huffel, E. Conchon, C. Correia, A. Fred and H. Gamboa. Biomedical Engineering Systems and Technologies, Communication in Computer and Information Science 357, Springer Berlin Heidelberg, pp.113-134, 2013, 978-3-642-38255-0. 〈10.1007/978-3-642-38256-7_8〉. 〈hal-00915532〉
  • Roland Donat, Laurent Bouillaut, Patrice Aknin, Philippe Leray. A dynamic graphical model to represent complex survival distributions. Advances in Mathematical Modeling for Reliability, IOS Press, pp.17-24, 2008. 〈hal-00412259〉
  • Philippe Leray, Stijn Meganck, Sam Maes, Bernard Manderick. Causal graphical models with latent variables : learning and inference. Holmes, D. E. and Jain, L. Innovations in Bayesian Networks: Theory and Applications, Springer, pp.219-249, 2008, Studies in Computational Intelligence, vol.156/2008, 〈10.1007/978-3-540-85066-3_9〉. 〈hal-00412263〉
  • Sam Maes, Stijn Meganck, Philippe Leray. An integral approach to causal inference with latent variables. Russo, F. and Williamson, J. Causality and Probability in the Sciences, London College Publications, pp.17-41, 2007, Texts In Philosophy series. 〈hal-00412264〉

Direction d'ouvrage, Proceedings, Dossier1 document

  • Philippe Leray. Revue d'Intelligence Artificielle VOL 21/3 - 2007 - numéro spécial Modèles graphiques probabilistes. Hermes, pp.157, 2007. 〈hal-00412919〉

Autre publication4 documents

  • Philippe Leray, Gregory Nuel. Editorial: Réseaux bayésiens et modèles graphiques probabilistes. DO. Revue d'Intelligence Artificielle, number 29:2/2015. pp. 149-150. Hermès. 2015. 〈hal-01168124〉
  • Salem Benferhat, Philippe Leray. Editorial: Uncertainty in artificial intelligence and databases - International Journal of Approximate Reasoning, 54(7). DO. International Journal of Approximate Reasoning, 54(7). 2013, pp.825-826. 〈10.1016/j.ijar.2013.04.001〉. 〈hal-00864163〉
  • Thomas Morisseau, Raphaël Mourad, Christian Dina, Philippe Leray, Christine Sinoquet. GWAS-AS: assistance for a thorough evaluation of advanced algorithms dedicated to genome-wide association studies. software suite, genome-wide association study. 2010. 〈hal-00915535〉
  • Raphaël Mourad, Christine Sinoquet, Philippe Leray. Forests of hierarchical latent models for association genetics. Research report. 2010. 〈hal-00503013〉

Pré-publication, Document de travail1 document

  • Raphaël Mourad, Christine Sinoquet, Philippe Leray. Learning a forest of Hierarchical Bayesian Networks to model dependencies between genetic markers. Research Report. 2010. 〈hal-00444087v2〉

Rapport5 documents

  • Mouna Ben Ishak, Rajani Chulyadyo, Philippe Leray. Probabilistic Relational Model Benchmark Generation. [Technical Report] LARODEC Laboratory, ISG, Université de Tunis, Tunisia; DUKe research group, LINA Laboratory UMR 6241, University of Nantes, France; DataForPeople, Nantes, France. 2016. 〈hal-01273307〉
  • Maroua Haddad, Philippe Leray, Nahla Ben Amor. Possibilistic Networks: Parameters Learning from Imprecise Data and Evaluation strategy. [Research Report] Laboratoire d'Informatique de Nantes Atlantique. 2016. 〈hal-01344821〉
  • Rajani Chulyadyo, Philippe Leray. Probabilistic Relational Models for Customer Preference Modelling and Recommendation. [Research Report] Laboratoire d'Informatique de Nantes Atlantique. 2013. 〈hal-00967044〉
  • Ghada Trabelsi, Philippe Leray, Mounir Ben Ayed, Adel Alimi. Benchmarking dynamic Bayesian network structure learning algorithms. 2012. 〈hal-00771258〉
  • Hoai-Tuong Nguyen, Gérard Ramstein, Philippe Leray. On Evaluation of a Population of Bayesian Networks. 2012. 〈hal-00657482〉

HDR1 document

  • Ph. Leray. Réseaux bayésiens : Apprentissage et diagnostic de systemes complexes. Modélisation et simulation. Université de Rouen, 2006. 〈tel-00485862〉