Publications of the year

Doctoral Dissertations and Habilitation Theses

  • 1B. Scherrer.

    Contributions algorithmiques au contrôle optimal stochastique à temps discret et horizon infini, Université de Lorraine (Nancy), June 2016, Habilitation à diriger des recherches.


Articles in International Peer-Reviewed Journals

  • 2R. Azaïs, A. Muller-Gueudin.

    Optimal choice among a class of nonparametric estimators of the jump rate for piecewise-deterministic Markov processes, in: Electronic journal of statistics , 2016.

  • 3O. Collignon, J.-M. Monnez.

    Clustering of the values of a response variable and simultaneous covariate selection using a stepwise algorithm, in: Applied Mathematics, 2016, vol. 07, pp. 1639 - 1648. [ DOI : 10.4236/am.2016.715141 ]

  • 4C. Lacaux, G. Samorodnitsky.

    Time-changed Extremal Process as a Random Sup Measure, in: Bernoulli journal, 2016, vol. 22, no 4, pp. 1979–2000.

  • 5S. Li, F. Bonneu, J. J. Chadoeuf, D. Picart, A. Gégout-Petit, L. Guerin-Dubrana.

    Spatial and Temporal Pattern Analyses 1 of Esca Grapevine Disease in Vineyards in France, in: Phytopathology, 2017.

  • 6I.-C. Morarescu, S. Martin, A. Girard, A. Muller-Gueudin.

    Coordination in networks of linear impulsive agents, in: IEEE Transactions on Automatic Control, September 2016, vol. 61, no 9, pp. 2402-2415. [ DOI : 10.1109/TAC.2015.2492058 ]

  • 7G. Nichil, P. Vallois.

    Provisioning against borrowers default risk, in: Insurance: Mathematics and Economics, 2016, vol. 66, pp. 29-43. [ DOI : 10.1016/j.insmatheco.2015.10.004 ]

  • 8P. Retif, T. Bastogne, M. Barberi-Heyob.

    Robustness analysis of a Geant4-Gate simulator for nano-radiosensitizers characterization, in: IEEE Transactions on NanoBioscience, April 2016, vol. 15, no 3, pp. 209-217. [ DOI : 10.1109/TNB.2016.2527720 ]

  • 9P. Retif, A. Reinhard, H. Paquot, V. Jouan-Hureaux, A. Chateau, L. Sancey, M. Barberi-Heyob, S. Pinel, T. Bastogne.

    Monte Carlo simulations guided by imaging to predict the in vitro ranking of radiosensitizing nanoparticles, in: International Journal of Nanomedicine, November 2016, vol. 11, pp. 6169-6179. [ DOI : 10.2147/IJN.S111320 ]

  • 10B. Scherrer.

    Improved and Generalized Upper Bounds on the Complexity of Policy Iteration, in: Mathematics of Operations Research, February 2016, Markov decision processes ; Dynamic Programming ; Analysis of Algorithms. [ DOI : 10.1287/moor.2015.0753 ]

  • 11M. Toussaint, S. Pinel, F. Auger, N. Durieux, M. Thomassin, E. Thomas, A. Moussaron, D. Meng, F. Plénat, M. Amouroux, T. Bastogne, C. Frochot, O. Tillement, F. Lux, M. Barberi-Heyob.

    Proton MR spectroscopy and diffusion MR imaging monitoring to predict tumor response to interstitial photodynamic therapy for glioblastoma, in: Theranostics, 2017.

  • 12J.-B. Tylcz, T. Bastogne, A. Bourguignon, C. Frochot, M. Barberi-Heyob.

    Realtime tracking of the photobleaching trajectory during photodynamic therapy, in: IEEE Transactions on Biomedical Engineering, 2017, 8 p. [ DOI : 10.1109/TBME.2016.2620239 ]


Invited Conferences

  • 13M. Ben Abdallah, M. Blonski, S. Wantz-Mézières, Y. Gaudeau, L. Taillandier, J.-M. Moureaux.

    Evaluation statistique de la segmentation manuelle de données IRM de gliomes diffus de bas grade, in: 18e Colloque Compression et Représentation des Signaux Audiovisuels, CORESA 2016, Nancy, France, May 2016.

  • 14M. Ben Abdallah, M. Blonski, S. Wantz-Mézières, Y. Gaudeau, L. Taillandier, J.-M. Moureaux.

    Modèles prédictifs pour les gliomes diffus de bas grade sous chimiothérapie, in: 18e Colloque Compression et Représentation des Signaux Audiovisuels, CORESA 2016, Nancy, France, May 2016.

  • 15M. Ben Abdallah, M. Blonski, S. Wantz-Mézières, Y. Gaudeau, L. Taillandier, J.-M. Moureaux.

    Modèles prédictifs pour les gliomes diffus de bas grade sous chimiothérapie, in: Modélisation biostatistique et biomathématique des données d'imagerie en cancérologie, Bordeaux, France, Cancéropôle Grand Sud-Ouest, April 2016, Présentation Poster.

  • 16M. Ben Abdallah, M. Blonski, S. Wantz-Mézières, Y. Gaudeau, L. Taillandier, J.-M. Moureaux.

    Predictive models for diffuse low-grade glioma patients under chemotherapy, in: 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC’16, Orlando, Florida, United States, August 2016.

  • 17M. Ben Abdallah, M. Blonski, S. Wantz-Mézières, Y. Gaudeau, L. Taillandier, J.-M. Moureaux.

    Statistical evaluation of manual segmentation of a diffuse low-grade glioma MRI dataset, in: 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC’16, Orlando, Florida, United States, August 2016.


International Conferences with Proceedings

  • 18M. Achard, S. Acherar, P. Althuser, J.-C. Andre, A. Philippe, M. Barberi-Heyob, F. Baros, T. Bastogne, C. Boninsegna, C. Boura, L. Colombeau, C. Frochot, V. Jouan-Hureaux, S. Goria, J. Landon, A. Mohd Gazzali, S. Pinel, T. Roques-Carmes, N. Thomas, M. Toussaint, R. Vanderesse, Z. Youssef.

    PDTeam’s project: targeting to improve PDT selectivity, in: Photodynamic Therapy and Photodiagnosis update, Nancy, France, October 2016, pp. Poster PC-028, Présentation Poster.

  • 19K. Duarte, J.-M. Monnez, E. Albuisson.

    Valeur pronostique d'une estimation du volume plasmatique dans l'insuffisance cardiaque, in: 48èmes Journées de Statistique de la Société Française de Statistique, Montpellier, France, May 2016.

  • 20A. Gégout-Petit, S. Li.

    Two-step centered spatio-temporal auto-logistic regression model, in: SADA416, Applied Statistics for Development in Africa, Cotonou, Benin, November 2016.

  • 21J. Perolat, B. Piot, B. Scherrer, O. Pietquin.

    On the Use of Non-Stationary Strategies for Solving Two-Player Zero-Sum Markov Games, in: 19th International Conference on Artificial Intelligence and Statistics (AISTATS 2016), Cadiz, Spain, Proceedings of the International Conference on Artificial Intelligences and Statistics, May 2016.

  • 22J. Pérolat, B. Piot, M. Geist, B. Scherrer, O. Pietquin.

    Softened Approximate Policy Iteration for Markov Games, in: ICML 2016 - 33rd International Conference on Machine Learning, New York City, United States, June 2016.


Conferences without Proceedings

  • 23L. Batista, T. Bastogne, E.-H. Djermoune.

    Identification of dynamical biological systems based on mixed-effect models, in: 31st ACM Symposium on Applied Computing, Pisa, Italy, April 2016.

  • 24L. Batista, T. Bastogne, E.-H. Djermoune.

    Mixed-effects ARX model identification of dynamical systems, in: 25th Meeting of the Population Approach Group in Europe, PAGE 2016, Lisboa, Portugal, June 2016, PAGE 25 (2016) Abstr 5807 p, Présentation Poster.

  • 25P. Héna, A. Reinhard, P. Retif, A. Chateau, V. Jouan-Hureaux, L. Sancey, T. Bastogne, P. Quetin, S. Pinel, M. Barberi-Heyob.

    Screening process of radiosensitizing nanoparticles based on basic in vitro experimental data and in silico analysis, in: 13e Colloque Nano-hybrides, Porquerolles, France, ILM, Lyon 1, May 2016, Présentation Poster.


Scientific Books (or Scientific Book chapters)

  • 26M. Schliemann-Bullinger, D. Fey, T. Bastogne, R. Findeisen, P. Scheurich, E. Bullinger.

    The experimental side of parameter estimation, in: Uncertainty in Biology - A Computational Modeling Approach, L. Geris, D. Gomez-Cabrero (editors), Studies in Mechanobiology, Tissue Engineering and Biomaterials, Springer, 2016, vol. 17, pp. 127-154.


Other Publications

References in notes
  • 36O. Arino, M. Kimmel, G. F. Webb.

    Mathematical modeling of the loss of telomere sequences, in: Journal of theoretical biology, 1995, vol. 177, no 1, pp. 45–57.
  • 37R. Azaïs.

    A recursive nonparametric estimator for the transition kernel of a piecewise-deterministic Markov process, in: ESAIM: Probability and Statistics, 2014, vol. 18, pp. 726–749.
  • 38R. Azaïs, F. Dufour, A. Gégout-Petit.

    Nonparametric estimation of the jump rate for non-homogeneous marked renewal processes, in: Annales de l'Institut Henri Poincaré, Probabilités et Statistiques, Institut Henri Poincaré, 2013, vol. 49, no 4, pp. 1204–1231.
  • 39R. Azaïs, F. Dufour, A. Gégout-Petit.

    Nonparametric estimation of the jump rate for piecewise-deterministic Markov processes, in: Scandinavian Journal of Statistics, 2014, 26 p.
  • 40J. M. Bardet, G. Lang, G. Oppenheim, A. Philippe, S. Stoev, M. Taqqu.

    Semi-parametric estimation of the long-range dependence parameter: a survey, in: Theory and applications of long-range dependence, Birkhauser Boston, 2003, pp. 557-577.
  • 41T. Bastogne, S. Mézières-Wantz, N. Ramdani, P. Vallois, M. Barberi-Heyob.

    Identification of pharmacokinetics models in the presence of timing noise, in: Eur. J. Control, 2008, vol. 14, no 2, pp. 149–157.

  • 42T. Bastogne, A. Samson, P. Vallois, S. Wantz-Mezieres, S. Pinel, D. Bechet, M. Barberi-Heyob.

    Phenomenological modeling of tumor diameter growth based on a mixed effects model, in: Journal of theoretical biology, 2010, vol. 262, no 3, pp. 544–552.
  • 43L. Batista, T. Bastogne, E.-H. Djermoune.

    Identification of dynamical biological systems based on random effects models, in: 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015, Milan, Italy, August 2015.

  • 44A. Benassi, S. Jaffard, D. Roux.

    Elliptic Gaussian random processes, in: Rev. Mat. Iberoamericana, 1997, vol. 13, no 1, pp. 19–90.
  • 45D. Bertsekas, J. Tsitsiklis.

    Neurodynamic Programming, Athena Scientific, 1996.
  • 46H. Biermé, C. Lacaux.

    Hölder regularity for operator scaling stable random fields, in: Stochastic Process. Appl., 2009, vol. 119, no 7, pp. 2222–2248.

  • 47H. Biermé, C. Lacaux, H.-P. Scheffler.

    Multi-operator Scaling Random Fields, in: Stochastic Processes and their Applications, 2011, vol. 121, no 11, pp. 2642-2677, MAP5 2011-01. [ DOI : 10.1016/j.spa.2011.07.002 ]

  • 48H. Biermé, C. Lacaux, Y. Xiao.

    Hitting probabilities and the Hausdorff dimension of the inverse images of anisotropic Gaussian random fields, in: Bull. Lond. Math. Soc., 2009, vol. 41, no 2, pp. 253–273.

  • 49T. Bourgeron, Z. Xu, M. Doumic, M. T. Teixeira.

    The asymmetry of telomere replication contributes to replicative senescence heterogeneity, in: Scientific reports, 2015, vol. 5.
  • 50A. Chronopoulou, S. Tindel.

    On inference for fractional differential equations, in: Statistical Inference for Stochastic Processes, 2013, vol. 16, no 1, pp. 29–61.
  • 51J. F. Coeurjolly.

    Simulation and identification of the fractional brownian motion: a bibliographical and comparative study, in: Journal of Statistical Software, 2000, vol. 5, pp. 1–53.
  • 52S. Cohen, C. Lacaux, M. Ledoux.

    A general framework for simulation of fractional fields, in: Stochastic Process. Appl., 2008, vol. 118, no 9, pp. 1489–1517.

  • 53M. H. Davis.

    Piecewise-deterministic Markov processes: A general class of non-diffusion stochastic models, in: Journal of the Royal Statistical Society. Series B (Methodological), 1984, pp. 353–388.
  • 54A. Deya, S. Tindel.

    Rough Volterra equations. I. The algebraic integration setting, in: Stoch. Dyn., 2009, vol. 9, no 3, pp. 437–477.

  • 55J. A. Doornik, H. Hansen.

    An omnibus test for univariate and multivariate normality*, in: Oxford Bulletin of Economics and Statistics, 2008, vol. 70, no s1, pp. 927–939.
  • 56M. Doumic, M. Hoffmann, N. Krell, L. Robert.

    Statistical estimation of a growth-fragmentation model observed on a genealogical tree, in: Bernoulli, 2015, vol. 21, no 3, pp. 1760–1799.
  • 57J. Fearnley.

    Exponential lower bounds for policy iteration, in: 37th international colloquium conference on Automata, languages and programming: Part II, Berlin, Heidelberg, ICALP'10, Springer-Verlag, 2010, pp. 551–562.
  • 58S. Ferrigno, G. R. Ducharme.

    Un test d'adéquation global pour la fonction de répartition conditionnelle, in: Comptes Rendus Mathematique, 2005, vol. 341, no 5, pp. 313–316.
  • 59S. Ferrigno, M. Maumy-Bertrand, A. Muller.

    Uniform law of the logarithm for the local linear estimator of the conditional distribution function, in: C. R. Math. Acad. Sci. Paris, 2010, vol. 348, no 17-18, pp. 1015–1019.

  • 60J. Friedman, T. Hastie, R. Tibshirani.

    Sparse inverse covariance estimation with the graphical lasso, in: Biostatistics, 2008, vol. 9, no 3, pp. 432–441.
  • 61A. Genadot, M. Thieullen.

    Averaging for a fully coupled piecewise-deterministic markov process in infinite dimensions, in: Advances in Applied Probability, 2012, vol. 44, no 3, pp. 749–773.
  • 62C. Giraud, S. Huet, N. Verzelen.

    Graph selection with GGMselect, in: Statistical applications in genetics and molecular biology, 2012, vol. 11, no 3.
  • 63M. Grabisch, T. Murofushi, M. Sugeno.

    Fuzzy measure of fuzzy events defined by fuzzy integrals, in: Fuzzy Sets and Systems, 1992, vol. 50, no 3, pp. 293–313.
  • 64M. Gubinelli, S. Tindel.

    Rough evolution equations, in: Ann. Probab., 2010, vol. 38, no 1, pp. 1–75.

  • 65S. J. Haberman.

    Algorithm AS 51: Log-linear fit for contingency tables, in: Applied Statistics, 1972, pp. 218–225.
  • 66T. Hansen, U. Zwick.

    Lower Bounds for Howard's Algorithm for Finding Minimum Mean-Cost Cycles, in: ISAAC (1), 2010, pp. 415-426.
  • 67S. Herrmann, P. Vallois.

    From persistent random walk to the telegraph noise, in: Stoch. Dyn., 2010, vol. 10, no 2, pp. 161–196.

  • 68J. Hu, W.-C. Wu, S. Sastry.

    Modeling subtilin production in bacillus subtilis using stochastic hybrid systems, in: Hybrid Systems: Computation and Control, Springer, 2004, pp. 417–431.
  • 69R. Keinj, T. Bastogne, P. Vallois.

    Multinomial model-based formulations of TCP and NTCP for radiotherapy treatment planning, in: Journal of Theoretical Biology, June 2011, vol. 279, no 1, pp. 55-62. [ DOI : 10.1016/j.jtbi.2011.03.025 ]

  • 70R. Koenker.

    Quantile regression, Cambridge university press, 2005, no 38.
  • 71H. J. Kushner, G. Yin.

    Stochastic approximation and recursive algorithms and applications, Springer Science & Business Media, 2003, vol. 35.
  • 72Y. A. Kutoyants.

    Statistical inference for ergodic diffusion processes, Springer Series in Statistics, Springer-Verlag London Ltd., London, 2004, xiv+481 p.
  • 73C. Lacaux.

    Real Harmonizable Multifractional Lévy Motions, in: Ann. Inst. Poincaré., 2004, vol. 40, no 3, pp. 259–277.
  • 74C. Lacaux.

    Series representation and simulation of multifractional Lévy motions, in: Adv. in Appl. Probab., 2004, vol. 36, no 1, pp. 171–197.

  • 75C. Lacaux, J.-M. Loubes.

    Hurst exponent estimation of fractional Lévy motion, in: ALEA Lat. Am. J. Probab. Math. Stat., 2007, vol. 3, pp. 143–164.
  • 76C. Lacaux, R. Marty.

    From invariance principles to a class of multifractional fields related to fractional sheets, 2011, MAP5 2011-08.

  • 77M. Lavielle.

    Mixed effects models for the population approach: models, tasks, methods and tools, CRC Press, 2014.
  • 78L. Lebart.

    On the Benzecri's method for computing eigenvectors by stochastic approximation (the case of binary data), in: Compstat 1974 (Proc. Sympos. Computational Statist., Univ. Vienna, Vienna, 1974), Vienna, Physica Verlag, 1974, pp. 202–211.
  • 79B. Lesner, B. Scherrer.

    Non-Stationary Approximate Modified Policy Iteration, in: ICML 2015, Lille, France, July 2015.

  • 80T. Lyons, Z. Qian.

    System control and rough paths, Oxford mathematical monographs, Clarendon Press, 2002.

  • 81J.-L. Marichal.

    An axiomatic approach of the discrete Choquet integral as a tool to aggregate interacting criteria, in: Fuzzy Systems, IEEE Transactions on, 2000, vol. 8, no 6, pp. 800–807.
  • 82N. Meinshausen, P. Bühlmann.

    High-dimensional graphs and variable selection with the lasso, in: The Annals of Statistics, 2006, pp. 1436–1462.
  • 83J.-M. Monnez.

    Approximation stochastique en analyse factorielle multiple, in: Ann. I.S.U.P., 2006, vol. 50, no 3, pp. 27–45.
  • 84J.-M. Monnez.

    Stochastic approximation of the factors of a generalized canonical correlation analysis, in: Statist. Probab. Lett., 2008, vol. 78, no 14, pp. 2210–2216.

  • 85J.-M. Monnez.

    Convergence d'un processus d'approximation stochastique en analyse factorielle, in: Publ. Inst. Statist. Univ. Paris, 1994, vol. 38, no 1, pp. 37–55.
  • 86E. Nadaraya.

    On non-parametric estimates of density functions and regression curves, in: Theory of Probability & Its Applications, 1965, vol. 10, no 1, pp. 186–190.
  • 87A. Neuenkirch, I. Nourdin, A. Rößler, S. Tindel.

    Trees and asymptotic expansions for fractional stochastic differential equations, in: Ann. Inst. Henri Poincaré Probab. Stat., 2009, vol. 45, no 1, pp. 157–174.

  • 88A. Neuenkirch, S. Tindel.

    A least square-type procedure for parameter estimation in stochastic differential equations with additive fractional noise, in: Statistical Inference for Stochastic Processes, 2014, vol. 17, no 1, pp. 99–120.
  • 89I. Post, Y. Ye.

    The simplex method is strongly polynomial for deterministic Markov decision processes, arXiv:1208.5083v2, 2012.
  • 90M. Puterman.

    Markov Decision Processes, Wiley, New York, 1994.
  • 91Q. Qi, J. A. Wattis, H. M. Byrne.

    Stochastic simulations of normal aging and Werner’s syndrome, in: Bulletin of mathematical biology, 2014, vol. 76, no 6, pp. 1241–1269.
  • 92P. Retif.

    Modeling, digital simulation and analysis of nanoparticles-X ray interaction. Applications to augmented radiotherapy., Université de Lorraine, March 2016.

  • 93B. Roynette, P. Vallois, M. Yor.

    Brownian penalisations related to excursion lengths, VII, in: Annales de l'IHP Probabilités et statistiques, 2009, vol. 45, no 2, pp. 421–452.
  • 94F. Russo, P. Vallois.

    Stochastic calculus with respect to continuous finite quadratic variation processes, in: Stochastics: An International Journal of Probability and Stochastic Processes, 2000, vol. 70, no 1-2, pp. 1–40.
  • 95F. Russo, P. Vallois.

    Elements of stochastic calculus via regularization, in: Séminaire de Probabilités XL, Berlin, Lecture Notes in Math., Springer, 2007, vol. 1899, pp. 147–185.

  • 96P. Salminen, P. Vallois.

    On maximum increase and decrease of Brownian motion, in: Annales de l'Institut Henri Poincare (B) Probability and Statistics, Elsevier, 2007, vol. 43, no 6, pp. 655–676.
  • 97B. Scherrer, M. Ghavamzadeh, V. Gabillon, B. Lesner, M. Geist.

    Approximate Modified Policy Iteration and its Application to the Game of Tetris, in: Journal of Machine Learning Research, 2015, vol. 16, pp. 1629–1676, A paraître.

  • 98B. Scherrer, B. Lesner.

    On the Use of Non-Stationary Policies for Stationary Infinite-Horizon Markov Decision Processes, in: NIPS 2012 - Neural Information Processing Systems, South Lake Tahoe, United States, December 2012.

  • 99B. Scherrer.

    Performance Bounds for Lambda Policy Iteration and Application to the Game of Tetris, in: Journal of Machine Learning Research, January 2013, vol. 14, pp. 1175-1221.

  • 100B. Scherrer.

    Approximate Policy Iteration Schemes: A Comparison, in: ICML - 31st International Conference on Machine Learning - 2014, Pékin, China, June 2014.

  • 101B. Scherrer.

    Improved and Generalized Upper Bounds on the Complexity of Policy Iteration, in: Mathematics of Operations Research, 2015, A paraître.
  • 102L. Shapley.

    Stochastic Games, in: Proceedings of the National Academy of Sciences, 1953, vol. 39, no 10, pp. 1095-1100.
  • 103C. A. Tudor, F. G. Viens.

    Statistical aspects of the fractional stochastic calculus, in: Ann. Statist., 2007, vol. 35, no 3, pp. 1183–1212.

  • 104P. Vallois, C. S. Tapiero.

    Memory-based persistence in a counting random walk process, in: Phys. A., 2007, vol. 386, no 1, pp. 303–307.

  • 105P. Vallois.

    The range of a simple random walk on Z, in: Advances in applied probability, 1996, pp. 1014–1033.
  • 106N. Villa-Vialaneix.

    An introduction to network inference and mining, 2015, http://wikistat.fr/, (consulté le 22/07/2015).

  • 107Z. Xu, K. D. Duc, D. Holcman, M. T. Teixeira.

    The length of the shortest telomere as the major determinant of the onset of replicative senescence, in: Genetics, 2013, vol. 194, no 4, pp. 847–857.
  • 108Y. Ye.

    The Simplex and Policy-Iteration Methods Are Strongly Polynomial for the Markov Decision Problem with a Fixed Discount Rate, in: Math. Oper. Res., 2011, vol. 36, no 4, pp. 593-603.