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Bibliography

Publications of the year

Articles in International Peer-Reviewed Journals

  • 1M. Abdallah, M. Blonski, S. Wantz-Mézières, Y. Gaudeau, L. Taillandier, J.-M. Moureaux.

    On the relevance of two manual tumor volume estimation methods for diffuse low-grade gliomas, in: Healthcare Technology Letters, 2018, forthcoming. [ DOI : 10.1049/htl.2017.0013 ]

    https://hal.inria.fr/hal-01654158
  • 2R. 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
  • 3T. T. Bastogne.

    Quality-by-Design of nano-pharmaceuticals - a state of the art, in: Nanomedicine: Nanotechnology, Biology and Medicine, October 2017, vol. 13, no 7, pp. 2151-2157. [ DOI : 10.1016/j.nano.2017.05.014 ]

    https://hal.archives-ouvertes.fr/hal-01544635
  • 4T. Bastogne, J.-L. Marchand, S. Pinel, P. Vallois.

    A branching process model of heterogeneous DNA damages caused by radiotherapy in in vitro cell cultures, in: Mathematical Biosciences, December 2017, vol. 294, pp. 100-109. [ DOI : 10.1016/j.mbs.2017.09.006 ]

    https://hal.archives-ouvertes.fr/hal-01669004
  • 5M. Benaïm, F. Bouguet, B. Cloez.

    Ergodicity of inhomogeneous Markov chains through asymptotic pseudotrajectories, in: The Annals of Applied Probability : an official journal of the institute of mathematical statistics, 2017, vol. 27, no 5, pp. 3004-3049, https://arxiv.org/abs/1601.06266. [ DOI : 10.1214/17-AAP1275 ]

    https://hal.archives-ouvertes.fr/hal-01401981
  • 6S. 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.

    https://hal.inria.fr/hal-01205332
  • 7M. Toussaint, S. Pinel, F. Auger, N. Durieux, M. Thomassin, E. Thomas, A. Moussaron, D. Meng, F. Plénat, M. Amouroux, T. 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, March 2017, vol. 7, no 2, pp. 436-451. [ DOI : 10.7150/thno.17218 ]

    https://hal.archives-ouvertes.fr/hal-01399256
  • 8J.-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, August 2017, vol. 64, no 8, pp. 1742-1749. [ DOI : 10.1109/TBME.2016.2620239 ]

    https://hal.archives-ouvertes.fr/hal-01205739

Conferences without Proceedings

  • 9T. Bastogne.

    Quality-by-design of nanopharmaceuticals. A state of the art, in: European Commission JRC Workshop: Bridging communitie in the field of nanomedicine, Ispra, Italy, September 2017.

    https://hal.archives-ouvertes.fr/hal-01670000
  • 10L. Batista, B. Bastien, T. Bastogne, P. Erbs, J. Folope.

    Analysis of in vivo responses by mixed-effect models, in: 8th International Meeting on Statistical Methods in Biopharmacy, SMB 2017, Paris, France, September 2017, Présentation Poster.

    https://hal.archives-ouvertes.fr/hal-01544653
  • 11L. Batista, B. Bastien, T. Bastogne, J. Foloppe, P. Erbs.

    Analysis of in vivo responses by mixed-effect models reference, in: 8th International Meeting on Statistical Methods in Biopharmacy, SMB 2017, Paris, France, September 2017, Présentation Poster.

    https://hal.archives-ouvertes.fr/hal-01670100
  • 12L. Batista, T. Bastogne, F. Atienzar, A. Delaunois, J.-P. Valentin.

    A data-driven modeling method to analyze cardiomyocyte impedance data, in: Safety Pharmacology Society 2017 Annual Meeting, SPS 2017, Berlin, Germany, September 2017, Présentation Poster.

    https://hal.archives-ouvertes.fr/hal-01670012
  • 13L. Batista, E.-H. Djermoune, T. Bastogne.

    Identification of dynamical systems population described by a mixed effect ARX model structure, in: 20th IFAC World Congress, IFAC 2017, Toulouse, France, July 2017.

    https://hal.archives-ouvertes.fr/hal-01544656
  • 14L. Batista, Y. Kolasa, T. Bastogne.

    i-Cellulo: a SaaS platform for the automatic statistical analysis of cell impedance signals, in: 8th International Meeting on Statistical Methods in Biopharmacy, SMB 2017, Paris, France, September 2017, Présentation Poster.

    https://hal.archives-ouvertes.fr/hal-01670076
  • 15R. Duponnois, T. Docquier, T. Aiguier, T. Bastogne.

    Statistical design of in silico experiments for the robustness analysis of electrophysiologic response simulators, in: Safety Pharmacology Society 2017 Annual Meeting, SPS 2017, Berlin, Germany, December 2017.

    https://hal.archives-ouvertes.fr/hal-01669909
  • 16L. Guo, M. Furniss, L. Batista, T. Bastogne, Y. Zhuge, J. Wu, S. Eldridge, M. Davis.

    Assessing functional and structural cardiotoxicity in cultured human iPSC-cardiomyocytes in a single plate format, in: Safety Pharmacology Society 2017 Annual Meeting, SPS 2017, Berlin, Germany, September 2017, Présentation Poster.

    https://hal.archives-ouvertes.fr/hal-01669498
  • 17P. Guyot, L. Batista, E.-H. Djermoune, J.-M. Moureaux, L. Doerr, M. Beckler, T. T. Bastogne.

    Comparison of compression solutions for impedance and field potential signals of cardiomyocytes, in: Computing in Cardiology, CinC 2017, Rennes, France, September 2017, Présentation Poster.

    https://hal.archives-ouvertes.fr/hal-01544642
  • 18P. Guyot, P. Voiriot, S. Papelier, L. Batista, T. Bastogne.

    A comparison of methods for delineation of wave boundaries in 12 Lead ECG, in: Safety Pharmacology Society 2017 Annual Meeting, SPS 2017, Berlin, Germany, September 2017, Présentation poster.

    https://hal.archives-ouvertes.fr/hal-01669454
  • 19A. Gégout-Petit, B. Bastien, A. Muller-Gueudin, Y. Shi.

    Aggregated methods for covariates selection and ranking in high-dimensional data under dependence, in: ENBIS 2017 - 17th Annual Conference of the European Network for Business and Industrial Statistics, Naples, Italy, September 2017.

    https://hal.archives-ouvertes.fr/hal-01541159
  • 20A. Gégout-Petit, A. Muller-Gueudin, Y. Shi, B. Bastien.

    Aggregated methods for covariates selection in high-dimensional data under dependence, in: European Meeting of Statisticians 2017, Helsinki, Finland, July 2017.

    https://hal.archives-ouvertes.fr/hal-01541157

Internal Reports

  • 21B. Bastien, Y. Shi, A. Muller-Gueudin, A. Gegout-Petit.

    Analyse de données transcriptomiques et protéomiques en oncologie, Inria Nancy Grand-Est, équipe BIGS, January 2017, 46 p.

    https://hal.inria.fr/hal-01462840

Patents

Other Publications

References in notes
  • 33R. 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.
  • 34R. 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.
  • 35R. Azaïs, F. Dufour, A. Gégout-Petit.

    Non-Parametric Estimation of the Conditional Distribution of the Interjumping Times for Piecewise-Deterministic Markov Processes, in: Scandinavian Journal of Statistics, December 2014, vol. 41, no 4, pp. 950–969. [ DOI : 10.1111/sjos.12076 ]

    https://hal.archives-ouvertes.fr/hal-01103700
  • 36R. 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.

    https://hal.archives-ouvertes.fr/hal-01168651
  • 37J. 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.
  • 38T. 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.

    http://dx.doi.org/10.3166/ejc.14.149-157
  • 39T. 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.
  • 40L. 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.

    https://hal.archives-ouvertes.fr/hal-01159193
  • 41D. Bertsekas, J. Tsitsiklis.

    Neurodynamic Programming, Athena Scientific, 1996.
  • 42H. 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 ]

    http://hal.archives-ouvertes.fr/hal-00551707/en/
  • 43H. Cardot, P. Cénac, J.-M. Monnez.

    A fast and recursive algorithm for clustering large datasets with k-medians, in: Computational Statistics & Data Analysis, 2012, vol. 56, no 6, pp. 1434–1449.
  • 44J. 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.
  • 45M. 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.
  • 46A. Deya, S. Tindel.

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

    http://dx.doi.org/10.1142/S0219493709002737
  • 47M. 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.
  • 48S. 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.
  • 49S. 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.

    http://dx.doi.org/10.1016/j.crma.2010.08.003
  • 50J. Friedman, T. Hastie, R. Tibshirani.

    Sparse inverse covariance estimation with the graphical lasso, in: Biostatistics, 2008, vol. 9, no 3, pp. 432–441.
  • 51C. Giraud, S. Huet, N. Verzelen.

    Graph selection with GGMselect, in: Statistical applications in genetics and molecular biology, 2012, vol. 11, no 3.
  • 52F. Greciet, R. Azaïs, A. Gegout-Petit, M. Biret.

    Modèle markovien déterministe par morceaux caché pour la propagation de fissure, October 2016, Mathématiques, oxygène du numérique, Poster.

    https://hal.archives-ouvertes.fr/hal-01398288
  • 53T. Hansen, U. Zwick.

    Lower Bounds for Howard's Algorithm for Finding Minimum Mean-Cost Cycles, in: ISAAC (1), 2010, pp. 415-426.
  • 54S. Herrmann, P. Vallois.

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

    http://dx.doi.org/10.1142/S0219493710002905
  • 55J. 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.
  • 56R. 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 ]

    http://hal.inria.fr/hal-00588935/en
  • 57R. Koenker.

    Quantile regression, Cambridge university press, 2005, no 38.
  • 58Y. A. Kutoyants.

    Statistical inference for ergodic diffusion processes, Springer Series in Statistics, Springer-Verlag London Ltd., London, 2004, xiv+481 p.
  • 59C. Lacaux.

    Real Harmonizable Multifractional Lévy Motions, in: Ann. Inst. Poincaré., 2004, vol. 40, no 3, pp. 259–277.
  • 60L. 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.
  • 61B. Lesner, B. Scherrer.

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

    https://hal.inria.fr/hal-01186664
  • 62T. Lyons, Z. Qian.

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

    http://books.google.com/books?id=H9fRQNIngZYC
  • 63N. Meinshausen, P. Bühlmann.

    High-dimensional graphs and variable selection with the lasso, in: The Annals of Statistics, 2006, pp. 1436–1462.
  • 64J.-M. Monnez.

    Approximation stochastique en analyse factorielle multiple, in: Ann. I.S.U.P., 2006, vol. 50, no 3, pp. 27–45.
  • 65J.-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.

    http://dx.doi.org/10.1016/j.spl.2008.01.088
  • 66J.-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.
  • 67E. 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.
  • 68I. Post, Y. Ye.

    The simplex method is strongly polynomial for deterministic Markov decision processes, arXiv:1208.5083v2, 2012.
  • 69M. Puterman.

    Markov Decision Processes, Wiley, New York, 1994.
  • 70B. 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.
  • 71F. 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.
  • 72F. 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.

    http://dx.doi.org/10.1007/978-3-540-71189-6_7
  • 73B. 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.

    https://hal.inria.fr/hal-01091341
  • 74B. 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.

    https://hal.inria.fr/hal-00758809
  • 75B. 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.

    https://hal.inria.fr/hal-00759102
  • 76B. Scherrer.

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

    https://hal.inria.fr/hal-00989982
  • 77B. 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 ]

    https://hal.inria.fr/hal-00829532
  • 78P. Vallois, C. S. Tapiero.

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

    http://dx.doi.org/10.1016/j.physa.2007.08.027
  • 79P. Vallois.

    The range of a simple random walk on Z, in: Advances in applied probability, 1996, pp. 1014–1033.
  • 80N. Villa-Vialaneix.

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

    http://www.nathalievilla.org/doc/pdf//wikistat-network_compiled.pdf
  • 81Y. 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.


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