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CQFD - 2017
CQFD - 2017
Project-Team Cqfd
Personnel
Overall Objectives
Research Program
Application Domains
Highlights of the Year
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
Dissemination
Bibliography
Project-Team Cqfd
Personnel
Overall Objectives
Research Program
Application Domains
Highlights of the Year
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
Dissemination
Bibliography


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Bibliography

Publications of the year

Doctoral Dissertations and Habilitation Theses

Articles in International Peer-Reviewed Journals

  • 3J. Anselmi.

    Asymptotically optimal open-loop load balancing, in: Queueing Systems, September 2017, pp. 1–23. [ DOI : 10.1007/s11134-017-9547-9 ]

    https://hal.inria.fr/hal-01614892
  • 4J. Anselmi, D. Ardagna, J. C. S. Lui, A. Wierman, Y. Xu, Z. Yang.

    The Economics of the Cloud: Price Competition and Congestion, in: ACM Transactions on Modeling and Performance Evaluation of Computing Systems, September 2017, vol. 2, no 4, pp. 1 - 23. [ DOI : 10.1145/3086574 ]

    https://hal.inria.fr/hal-01615172
  • 5R. Azaïs, A. Genadot.

    A new characterization of the jump rate for piecewise-deterministic Markov processes with discrete transitions, in: Communication in Statistics - Theory and Methods, 2017, https://arxiv.org/abs/1606.06130, forthcoming.

    https://hal.archives-ouvertes.fr/hal-01334847
  • 6A. N. Bishop, P. Del Moral.

    On the Stability of Kalman–Bucy Diffusion Processes, in: SIAM Journal on Control and Optimization, November 2017, vol. 55, no 6, pp. 4015 - 4047. [ DOI : 10.1137/16M1102707 ]

    https://hal.inria.fr/hal-01669244
  • 7A. N. Bishop, P. Del Moral, S. D. Pathiraja.

    Perturbations and projections of Kalman–Bucy semigroups, in: Stochastic Processes and their Applications, November 2017, pp. 1-48. [ DOI : 10.1016/j.spa.2017.10.006 ]

    https://hal.inria.fr/hal-01669084
  • 8M. Chavent, V. Kuentz-Simonet, A. Labenne, J. Saracco.

    ClustGeo: an R package for hierarchical clustering with spatial constraints, in: Computational Statistics, 2017, pp. 1-26, https://arxiv.org/abs/1707.03897, forthcoming.

    https://hal.archives-ouvertes.fr/hal-01664018
  • 9E. Costa, B. De Saporta.

    Linear minimum mean square filters for Markov jump linear systems, in: IEEE Transactions on Automatic Control, 2017, vol. 62, no 7, pp. 3567-3572, https://arxiv.org/abs/1601.00772. [ DOI : 10.1109/TAC.2017.2692180 ]

    https://hal.archives-ouvertes.fr/hal-01251334
  • 10O. L. d. V. Costa, F. Dufour.

    Zero-Sum Discounted Reward Criterion Games for Piecewise Deterministic Markov Processes, in: Applied Mathematics and Optimization, 2017, forthcoming. [ DOI : 10.1007/s00245-017-9416-2 ]

    https://hal.archives-ouvertes.fr/hal-01643056
  • 11B. De Saporta, F. Dufour, A. Geeraert.

    Optimal strategies for impulse control of piecewise deterministic Markov processes, in: Automatica, 2017, vol. 77, pp. 219-229, https://arxiv.org/abs/1603.07859 . [ DOI : 10.1016/j.automatica.2016.11.039 ]

    https://hal.archives-ouvertes.fr/hal-01294286
  • 12B. 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, https://arxiv.org/abs/1602.04609. [ DOI : 10.1007/s10288-016-0337-8 ]

    https://hal.archives-ouvertes.fr/hal-01274645
  • 13P. Del Moral, A. Jasra.

    A sharp first order analysis of Feynman–Kac particle models, Part I: Propagation of chaos, in: Stochastic Processes and their Applications, January 2018, vol. 128, no 1, pp. 332 - 353. [ DOI : 10.1016/j.spa.2017.04.007 ]

    https://hal.inria.fr/hal-01669381
  • 14P. Del Moral, A. Jasra.

    A sharp first order analysis of Feynman–Kac particle models, Part II: Particle Gibbs samplers, in: Stochastic Processes and their Applications, January 2018, vol. 128, no 1, pp. 354 - 371. [ DOI : 10.1016/j.spa.2017.05.001 ]

    https://hal.inria.fr/hal-01669385
  • 15P. Del Moral, A. Kurtzmann, J. Tugaut.

    On the Stability and the Uniform Propagation of Chaos of a Class of Extended Ensemble Kalman–Bucy Filters, in: SIAM Journal on Control and Optimization, 2017, vol. 55, no 1, pp. 119 - 155, https://arxiv.org/abs/1606.08256. [ DOI : 10.1137/16M1087497 ]

    https://hal.inria.fr/hal-01469198
  • 16P. Del Moral, D. Villemonais.

    Exponential mixing properties for time inhomogeneous diffusion processes with killing, in: Bernoulli, May 2018, vol. 24, no 2, pp. 1010 - 1032, https://arxiv.org/abs/1412.2627. [ DOI : 10.3150/16-BEJ845 ]

    https://hal.inria.fr/hal-01593882
  • 17A. Genadot.

    Averaging for some simple constrained Markov processes, in: Probability and Mathematical Statistics, 2017, https://arxiv.org/abs/1606.07577, forthcoming.

    https://hal.archives-ouvertes.fr/hal-01336752
  • 18F. Giraud, P. Del Moral.

    Nonasymptotic analysis of adaptive and annealed Feynman–Kac particle models, in: Bernoulli, 2017, vol. 23, no 1, pp. 670 - 709, https://arxiv.org/abs/1209.5654. [ DOI : 10.3150/14-BEJ680 ]

    https://hal.inria.fr/hal-01469193
  • 19I. Jlassi, J. Saracco.

    Variable importance assessment in sliced inverse regression for variable selection, in: Communications in Statistics - Simulation and Computation, September 2017, pp. 1 - 31. [ DOI : 10.1080/03610918.2017.1375522 ]

    https://hal.archives-ouvertes.fr/hal-01662513
  • 20Y. 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.

    https://hal.inria.fr/hal-01389047
  • 21P. D. Moral, A. Jasra, K. J. H. Law, Y. Zhou.

    Multilevel Sequential Monte Carlo Samplers for Normalizing Constants, in: ACM Transactions on Modeling and Computer Simulation, September 2017, vol. 27, no 3, pp. 1 - 22. [ DOI : 10.1145/3092841 ]

    https://hal.inria.fr/hal-01669115
  • 22P. D. Moral, A. Jasra, Y. Zhou.

    Biased Online Parameter Inference for State-Space Models, in: Methodology and Computing in Applied Probability, September 2017, vol. 19, no 3, pp. 727 - 749. [ DOI : 10.1007/s11009-016-9511-x ]

    https://hal.inria.fr/hal-01669132
  • 23H. Zhang, B. De Saporta, F. Dufour, D. Laneuville, A. Nègre.

    Stochastic Control of Observer Trajectories in Passive Tracking with Acoustic Signal Propagation Optimization, in: IET Radar Sonar and Navigation, 2017, forthcoming.

    https://hal.inria.fr/hal-01610189

Articles in National Peer-Reviewed Journals

  • 24M. P. Ellies-Oury, G. Cantalapiedra Hijar, D. Durand, D. Gruffat, A. Listrat, D. D. Micol, I. Ortigues-Marty, J.-F. Hocquette, M. Chavent, J. Saracco, B. Picard.

    Une nouvelle approche méthodologique pour piloter la conduite en élevage, in: Viandes & Produits Carnés, 2017, vol. 33, no 3, pp. 1-8.

    https://hal.archives-ouvertes.fr/hal-01664209

Invited Conferences

  • 25A. Cleynen, B. De Saporta.

    Optimal Stopping for Change-point Detection of Piecewise Deterministic Markov Processes, in: CT 2017 - SIAM Conference on Control and Its Applications, Pittsburgh, United States, 2017.

    https://hal.archives-ouvertes.fr/hal-01563234
  • 26E. Costa, B. De Saporta.

    Clustered Information Filter for Markov Jump Linear Systems, in: CT 2017 - SIAM Conference on Control and Its Applications, Pittsburgh, United States, July 2017.

    https://hal.archives-ouvertes.fr/hal-01563236
  • 27B. De Saporta, F. Dufour.

    Méthode numérique pour le contrôle des PDMP, in: Statistique pour les processus de Markov déterministes par morceaux, Nancy, France, Romain Azaïs, Florian Bouguet, February 2017.

    https://hal.archives-ouvertes.fr/hal-01549078
  • 28F. Dufour, A. Genadot, A. Piunovskiy.

    The Expected Total Reward Criterion for Markov Decision Processes, in: IMA and OR Society Conference on Mathematics of Operational Research, Birmingham, United Kingdom, April 2017.

    https://hal.inria.fr/hal-01665757
  • 29F. Dufour, T. Prieto-Rumeau.

    Approximations for Average Markov Decision Processes in Continuous-time, in: SIAM Conference on Control and its Applications, Pittsburgh, United States, July 2017.

    https://hal.inria.fr/hal-01665755

International Conferences with Proceedings

  • 30H. Zhang, F. Dufour, J. Anselmi, D. Laneuville, A. Nègre.

    Piecewise Optimal Trajectories of Observer for Bearings-Only Tracking by Quantization, in: 20th International Conference on Information Fusion, Xi'an, China, July 2017, pp. 1458-1464.

    https://hal.archives-ouvertes.fr/hal-01591013
  • 31H. Zhang, F. Dufour, J. Anselmi, D. Laneuville, A. Nègre.

    Piecewise Optimal Trajectories of Observer for Bearings-Only Tracking of Maneuvering Target, in: Proceedings of IEEE Aerospace Conference, Bigsky, United States, March 2018.

    https://hal.inria.fr/hal-01649429

Conferences without Proceedings

  • 32S. Badillo, M. Chavent, M. Joliot, N. Tzourio-Mazoyer, J. Saracco, B. Mazoyer.

    Are production, reading, and listening co-lateralized ? fMRI investigation in 296 healthy individuals, in: OHBM 2017 - Organization for Human Brain Mapping, Vancouver, Canada, June 2017.

    https://hal.archives-ouvertes.fr/hal-01663987
  • 33M. Chavent, G. Chavent.

    Approche bloc en ACP group-sparse: le package sparsePCA, in: AngletR 2017 - 6ème Rencontres R, Anglet, France, June 2017, 1 p.

    https://hal.archives-ouvertes.fr/hal-01662652
  • 34H. Lorenzo, R. Thiebaut, J. Saracco.

    Multi-block high-dimensional lasso-penalized analysis with imputation of missing data applied to postgenomic data in an Ebola vaccine trial, in: Annual workshop on Statistical Methods for Post Genomic Data - SMPGD 2018, Montpellier, France, January 2018.

    https://hal.archives-ouvertes.fr/hal-01664610
  • 35J. Saracco, I. Jlassi.

    Evaluation de l’importance des variables dans la méthode SIR (Sliced Inverse Regression), in: JDS 2017 - 49èmes Journées de Statistique, Avignon, France, May 2017.

    https://hal.archives-ouvertes.fr/hal-01664081

Scientific Books (or Scientific Book chapters)

  • 36T. 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.

    https://hal.inria.fr/hal-01388426

Internal Reports

Other Publications

References in notes
  • 51N. Duan, K.-C. Li.

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

    http://dx.doi.org/10.1214/aos/1176348109
  • 52R. Duda, P. Hart, D. Stork.

    Pattern Classification, John Wiley, 2001.
  • 53K.-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.


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