CQFD - 2016
Overall Objectives
Application Domains
New Results
Bilateral Contracts and Grants with Industry
Overall Objectives
Application Domains
New Results
Bilateral Contracts and Grants with Industry


Publications of the year

Articles in International Peer-Reviewed Journals

  • 1J. Anselmi, F. Dufour, T. Prieto-Rumeau.

    Computable approximations for continuous-time Markov decision processes on Borel spaces based on empirical measures, in: Journal of Mathematical Analysis and Applications, 2016, vol. 443, no 2, pp. 1323 - 1361. [ DOI : 10.1016/j.jmaa.2016.05.055 ]

  • 2J. Anselmi, N. S. Walton.

    Decentralized Proportional Load Balancing, in: SIAM Journal on Applied Mathematics, 2016, vol. 76, no 1, pp. 391-410. [ DOI : 10.1137/140969361 ]

  • 3O. Costa, F. Dufour, A. B. Piunovskiy.

    Constrained and Unconstrained Optimal Discounted Control of Piecewise Deterministic Markov Processes, in: SIAM Journal on Control and Optimization, 2016, vol. 54, no 3, pp. 1444 - 1474. [ DOI : 10.1137/140996380 ]

  • 4B. De Saporta, E. Costa.

    Approximate Kalman-Bucy filter for continuous-time semi-Markov jump linear systems, in: IEEE Transactions on Automatic Control, 2016, vol. 61, no 8, pp. 2035 - 2048. [ DOI : 10.1109/TAC.2015.2495578 ]

  • 5B. De Saporta, F. Dufour, A. Geeraert.

    Optimal strategies for impulse control of piecewise deterministic Markov processes, in: Automatica, 2017. [ DOI : 10.1016/j.automatica.2016.11.039 ]

  • 6B. De Saporta, F. Dufour, C. Nivot.

    Partially observed optimal stopping problem for discrete-time Markov processes, in: 4OR: A Quarterly Journal of Operations Research, 2017. [ DOI : 10.1007/s10288-016-0337-8 ]

  • 7P. Del Moral, R. Kohn, F. Patras.

    On particle Gibbs samplers, in: Annales de l'IHP - Probabilités et Statistiques, 2016.

  • 8B. Delyon, B. De Saporta, N. Krell, L. Robert.

    Investigation of asymmetry in E. coli growth rate, in: CSBIGS (Case Studies in Business, Industry and Government Statistics, 2016, forthcoming.

  • 9F. Dufour, A. B. Piunovskiy.

    Impulsive Control for Continuous-Time Markov Decision Processes: A Linear Programming Approach, in: Applied Mathematics and Optimization, 2016, vol. 74, no 1, pp. 129 - 161. [ DOI : 10.1007/s00245-015-9310-8 ]

  • 10F. Dufour, T. Prieto-Rumeau.

    Conditions for the Solvability of the Linear Programming Formulation for Constrained Discounted Markov Decision Processes, in: Applied Mathematics and Optimization, 2016, vol. 74, no 1, pp. 27 - 51. [ DOI : 10.1007/s00245-015-9307-3 ]

  • 11M. Ellies-Oury, G. Cantalapiedra-Hijar, D. Durand, D. Gruffat, A. Listrat, D. Micol, I. Ortigues-Marty, J. Hocquette, M. Chavent, J. Saracco, B. Picard.

    An innovative approach combining Animal Performances, nutritional value and sensory quality of meat, in: Meat Science, 2016, vol. 122, pp. 163 - 172. [ DOI : 10.1016/j.meatsci.2016.08.004 ]

  • 12A. Genadot.

    Spatio-temporal averaging for a class of hybrid systems and application to conductance-based neuron models, in: Nonlinear Analysis: Hybrid Systems, November 2016, vol. 22, pp. 176-190. [ DOI : 10.1016/j.nahs.2016.03.003 ]

  • 13B. Liquet, J. Saracco.

    BIG-SIR: a Sliced Inverse Regression approach for massive data, in: Statistics and its interfaces, 2016, vol. 9, no 4, pp. 509-520.

  • 14Y. Martinez, E. Naredo, L. Trujillo, P. Legrand, U. Lopez.

    A comparison of fitness-case sampling methods for genetic programming, in: Journal of Experimental and Theoretical Artificial Intelligence, 2017.

  • 15Y. Martinez, L. Trujillo, P. Legrand, E. Galvan-Lopez.

    Prediction of Expected Performance for a Genetic Programming Classifier, in: Genetic Programming and Evolvable Machines, 2016, vol. 17, no 4, pp. 409–449. [ DOI : 10.1007/s10710-016-9265-9 ]

  • 16E. Naredo, L. Trujillo, P. Legrand, S. Silva, L. Munoz.

    Evolving Genetic Programming Classifiers with Novelty Search, in: Information Sciences, November 2016, vol. 369, pp. 347–367. [ DOI : 10.1016/j.ins.2016.06.044 ]

  • 17E. Z-Flores, L. Trujillo, A. Sotelo, P. Legrand, L. Coria.

    Regularity and Matching Pursuit Feature Extraction for the Detection of Epileptic Seizures, in: Journal of Neuroscience Methods, 2016.


Invited Conferences

  • 18M. Chavent.

    Multivariate analysis of mixed data: The PCAmixdata R package, in: 9th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2016), Seville, Spain, December 2016.

  • 19A. Geeraert, B. De Saporta, F. Dufour.

    Impulse control of piecewise deterministic processes, in: 28th European Conference on Operational Research, Poznan, Poland, 2016.

  • 20J. Saracco, I. Jlassi.

    Variable importance assessment in sliced inverse regression for variable selection, in: 9th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2016), Séville, Spain, December 2016.


International Conferences with Proceedings

  • 21E. Costa, B. De Saporta.

    Precomputable Kalman-based filter for Markov Jump Linear Systems, in: 3rd International Conference on Control and Fault-Tolerant Systems, Barcelone, Spain, 2016, pp. 387-392.

  • 22J. E. Hernandez-Beltran, V. H. Díaz-Ramírez, L. Trujillo, P. Legrand.

    Restoration of degraded images using genetic programming, in: Optics and photonics for information processing X, San Diego, United States, August 2016, vol. 9970.

  • 23V. R. López-López, L. Trujillo, P. Legrand, G. Olague.

    Genetic Programming: From design to improved implementation, in: Gecco 2016, Denver, United States, June 2016.


Conferences without Proceedings

  • 24V. Sautron, M. Chavent, N. Viguerie, N. Villa-Vialaneix.

    Multiway-SIR for longitudinal multi-table data integration, in: 22nd International Conference on Computational Statistics (COMPSTAT), Oviedo, Spain, August 2016.


Scientific Books (or Scientific Book chapters)

  • 25S. Girard, J. Saracco.

    Supervised and unsupervised classification using mixture models, in: Statistics for Astrophysics: Clustering and Classification, D. Fraix-Burnet, S. Girard (editors), EAS Publications Series, EDP Sciences, May 2016, vol. 77, pp. 69-90.

  • 26T. Leonardo, E. Z-Flores, P. S. Juarez Smith, P. Legrand, S. Silva, M. Castelli, L. Vanneschi, O. Schütze, L. Munoz.

    Local Search is Underused in Genetic Programming, in: Genetic Programming Theory and Practice XIV, A. Arbor (editor), Springer, 2017.

  • 27J. Saracco, M. Chavent.

    Clustering of Variables for Mixed Data, in: Statistics for Astrophysics: Clustering and Classification, EAS Publications Series, EDP Sciences, 2016, vol. 77, pp. 91-119.


Books or Proceedings Editing

  • 28S. Bonnevay, P. Legrand, N. Monmarché, E. Lutton, M. Schoenauer (editors)

    Artificial Evolution 2015, LNCS - Lecture Notes in Computer Science, Springer, Lyon, France, 2016, vol. 9554. [ DOI : 10.1007/978-3-319-31471-6 ]

  • 29O. Schuetze, L. Trujillo, P. Legrand, Y. Maldonado (editors)

    NEO 2015 - Numerical and Evolutionary Optimization: Results of the Numerical and Evolutionary Optimization Workshop NEO 2015 held at September 23-25 2015 in Tijuana, Mexico, Studies in Computational Intelligence, Springer, Tijuana, Mexico, 2016.


Other Publications

References in notes
  • 42N. Duan, K.-C. Li.

    Slicing regression: a link-free regression method, in: Ann. Statist., 1991, vol. 19, no 2, pp. 505–530.

  • 43R. Duda, P. Hart, D. Stork.

    Pattern Classification, John Wiley, 2001.
  • 44K.-C. Li.

    Sliced inverse regression for dimension reduction, in: J. Amer. Statist. Assoc., 1991, vol. 86, no 414, pp. 316–342, With discussion and a rejoinder by the author.