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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, February 2018, vol. 5, no 1, pp. 13-17. [ DOI : 10.1049/htl.2017.0013 ]

    https://hal.inria.fr/hal-01654158
  • 2R. Azaïs, B. Delyon, F. Portier.

    Integral estimation based on Markovian design, in: Advances in Applied Probability, 2018, vol. 50, no 3, pp. 833-857, https://arxiv.org/abs/1609.01165v2 - 45 pages. [ DOI : 10.1017/apr.2018.38 ]

    https://hal.archives-ouvertes.fr/hal-01360647
  • 3R. 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, 2018, vol. 47, no 8, pp. 1812-1829, https://arxiv.org/abs/1606.06130. [ DOI : 10.1080/03610926.2017.1327072 ]

    https://hal.archives-ouvertes.fr/hal-01334847
  • 4L. Batista, T. Bastogne, A. Delaunois, J.-P. Valentin, F. Atienzar.

    A novel statistical signal processing method to estimate effects of compounds on contractility of cardiomyocytes using impedance assays, in: Biomedical Signal Processing and Control, August 2018, vol. 45, pp. 202-212. [ DOI : 10.1016/j.bspc.2018.05.038 ]

    https://hal.archives-ouvertes.fr/hal-01621227
  • 5F. Bouguet.

    A Probabilistic Look at Growth-Fragmentation Equations, in: Séminaire de Probabilités, 2018, vol. XLIX, https://arxiv.org/abs/1609.02414.

    https://hal.archives-ouvertes.fr/hal-01362555
  • 6F. Bouguet, B. Cloez.

    Fluctuations of the Empirical Measure of Freezing Markov Chains, in: Electronic Journal of Probability, 2018, vol. 23, https://arxiv.org/abs/1705.02121. [ DOI : 10.1214/17-EJP130 ]

    https://hal.archives-ouvertes.fr/hal-01519611
  • 7K. Duarte, J.-M. Monnez, E. Albuisson.

    Methodology for Constructing a Short-Term Event Risk Score in Heart Failure Patients, in: Applied Mathematics, 2018, vol. 09, no 08, pp. 954 - 974. [ DOI : 10.4236/am.2018.98065 ]

    https://hal.inria.fr/hal-01933625
  • 8K. Duarte, J.-M. Monnez, E. Albuisson.

    Sequential linear regression with online standardized data, in: PLoS ONE, 2018, pp. 1-27. [ DOI : 10.1371/journal.pone.0191186 ]

    https://hal.archives-ouvertes.fr/hal-01538125
  • 9A. Lagnoux, S. Mercier, P. Vallois.

    Probability density function of the local score position, in: Stochastic Processes and their Applications, 2018.

    https://hal.archives-ouvertes.fr/hal-01835781
  • 10S. Toupance, D. Villemonais, D. Germain, A. Gégout-Petit, E. Albuisson, A. Benetos.

    The individual’s signature of telomere length distribution, in: Scientific Reports, 2018.

    https://hal.inria.fr/hal-01925000
  • 11G. Vogin, T. Bastogne, L. Bodgi, J. Gillet-Daubin, A. Canet, S. Pereira, N. Foray.

    The pATM Immunofluorescence assay: a high-performance radiosensitivity assay to predict post radiotherapy overreactions, in: International Journal of Radiation Oncology - Biology - Physics, July 2018, vol. 101, no 3, pp. 690–693. [ DOI : 10.1016/j.ijrobp.2018.03.047 ]

    https://hal.archives-ouvertes.fr/hal-01757771

International Conferences with Proceedings

Conferences without Proceedings

  • 16T. Bastogne, V. Jouan-Hureaux, M. Thomassin.

    A new approach for a physicochemical characterization of nanoparticles in complex media: a pilot study, in: NanoMedicine International Conference, NanoMedicine 2018, Venise, Italy, October 2018, Présentation Poster.

    https://hal.archives-ouvertes.fr/hal-01925854
  • 17L. Batista, T. Bastogne.

    Robust estimation of field potential duration in multi-electrode array signals, in: Annual Meeting of Safety Pharmacology Society, SPS 2018, Washington DC, United States, September 2018, Présentation Poster.

    https://hal.archives-ouvertes.fr/hal-01925650
  • 18L. Batista, R. Contu, B. Van Hese, F. Zanella, T. Bastogne.

    Automated classification of early afterdepolarizations grades in flipr calcium assays, in: Annual Meeting of Safety Pharmacology Society, SPS 2018, Washington DC, United States, September 2018, Présentation Poster.

    https://hal.archives-ouvertes.fr/hal-01925678
  • 19S. Deneuve, C. Mirjolet, M. Duclos, R. Blanchard, P. Retif, N. Foray, T. Bastogne, S. Pereira.

    Fast, reliable and cost-effective assay on lymphocytes to predict radiosensitivity: development on prostate and head and neck cohort, in: Annual Meeting of American Society for Therapeutic Radiology and Oncology, ASTRO 2018, San Antonio, Texas, United States, October 2018, Abstract published in International Journal of Radiation Oncology, 102(3):e171, November 2018. [ DOI : 10.1016/j.ijrobp.2018.07.643 ]

    https://hal.archives-ouvertes.fr/hal-01925681
  • 20S. Deneuve, C. Mirjolet, M. Duclos, G. Vogin, T. Bastogne, S. Pereira.

    Fast and binary assay for predicting radiosensitivity based on the theory of the ATM nucleoshuttling, in: 37th Annual Congress of the European Society for Radiotherapy & Oncology, ESTRO 37, Barcelona, Spain, April 2018, pp. EP-2274, Présentation Poster.

    https://hal.archives-ouvertes.fr/hal-01925684
  • 21K. Duarte, J.-M. Monnez, E. Albuisson.

    Construction d'un score d'événement à court terme pour les insuffisants cardiaques, in: 50èmes Journées de statistique de la Société Française de Statistique, Saclay, France, May 2018.

    https://hal.archives-ouvertes.fr/hal-01813148
  • 22K. Duarte, J.-M. Monnez, E. Albuisson.

    Score de risque d'événement et score en ligne pour des insuffisants cardiaques, in: SFC 2018 - XXVèmes Rencontres de la Société Francophone de Classification, Paris, France, September 2018.

    https://hal.archives-ouvertes.fr/hal-01879126
  • 23P. Guyot, B. Chenuel, E.-H. Djermoune, T. Bastogne.

    Early detection of Cheyne-Stokes breathing via ECG-derived respiration in patients with severe heart failure: a pilot study, in: 45th Computing in Cardiology Conference, CinC 2018, Maastricht, Netherlands, September 2018.

    https://hal.archives-ouvertes.fr/hal-01925852
  • 24P. Guyot, E.-H. Djermoune, T. Bastogne.

    Assessment of non-negative matrix factorization for the preprocessing of long-term ECG, in: Annual Meeting of Safety Pharmacology Society, SPS 2018, Washington DC, United States, September 2018, Présentation Poster.

    https://hal.archives-ouvertes.fr/hal-01925679
  • 25P. Guyot, P. Voiriot, E.-H. Djermoune, S. Papelier, C. Lessard, M. Felices, T. Bastogne.

    R-peak detection in holter ECG signals using non-negative matrix factorization, in: 45th Computing in Cardiology Conference, CinC 2018, Maastricht, Netherlands, September 2018.

    https://hal.archives-ouvertes.fr/hal-01925853
  • 26A. Gégout-Petit, C. Fritsch, M. Grosdidier, B. Marcais.

    Spatio-temporal modelling of the spread of chalara (illness of the ash tree) in France, in: CMStatistics 2018 - 11th International Conference of the ERCIM WG on Computational and Methodological Statistics, Pisa, Italy, December 2018.

    https://hal.inria.fr/hal-01925454
  • 27A. Gégout-Petit, N. Sahki, S. Mézières-Wantz.

    Change-point detection methods in the online context, in: ENBIS-18 18th Annual Conference of the European Network for Business and Industrial Statistics, Nancy, France, September 2018.

    https://hal.archives-ouvertes.fr/hal-01915726
  • 28C. Karmann, A. Gégout-Petit.

    Régression logistique polytomique pénalisée a logits cumulatifs, in: Journées de statistiques, Saclay, France, May 2018.

    https://hal.archives-ouvertes.fr/hal-01929996
  • 29Y. Kolasa, T. Bastogne, J.-P. Georges.

    Simulation and sensitivity analysis of sensors network for cardiac monitoring, in: 8th International Digital Health Conference, DH2018, Lyon, France, April 2018.

    https://hal.archives-ouvertes.fr/hal-01925649
  • 30Y. Kolasa, J.-P. Georges, T. Bastogne.

    Computer-aided design of ECG telemetry systems for online cardiac monitoring, in: Annual Meeting of Safety Pharmacology Society, SPS 2018, Washington DC, United States, September 2018, Présentation Poster.

    https://hal.archives-ouvertes.fr/hal-01925675

Scientific Books (or Scientific Book chapters)

  • 31R. Azaïs, A. Gégout-Petit, F. Greciet.

    Rupture Detection in Fatigue Crack Propagation, in: Statistical Inference for Piecewise-deterministic Markov Processes, Wiley, August 2018, pp. 173-207. [ DOI : 10.1002/9781119507338.ch6 ]

    https://hal.archives-ouvertes.fr/hal-01862267
  • 32E. Boissard, P. Cattiaux, A. Guillin, L. Miclo, F. Bouguet, J. Brossard, C. Leuridan, M. Capitaine, N. Champagnat, K. A. Coulibaly-Pasquier, D. Villemonais, H. E. Altman, P. Kratz, E. Pardoux, A. Lejay, P. McGill, G. Pagès, B. Wilbertz, P. Petit, B. Rajeev, L. Serlet, H. Tsukada.

    C. Donati-Martin, A. Lejay, A. Rouault (editors), Séminaire de probabilités XLIX, Lecture notes in mathematics, Springer, July 2018, vol. 2215. [ DOI : 10.1007/978-3-319-92420-5 ]

    https://hal.inria.fr/hal-01931202

Books or Proceedings Editing

Scientific Popularization

  • 34F. Greciet, R. Azaïs, A. Gégout-Petit.

    Detection and modeling of the propagation regimes in fatigue crack propagation, in: ENBIS 2018 - 18th Annual Conference of the European Network for Business and Industrial Statistics, Nancy, France, September 2018.

    https://hal.inria.fr/hal-01942243
  • 35A. Gégout-Petit, S. Wantz-Mézières, N. Sahki.

    Retours d'expériences autour de l'évaluation des objets connectés en santé, fiabilité et aide à la décision, in: 1ères rencontres académiques de l’Evaluation des objets connectés en santé, Paris, France, October 2018.

    https://hal.inria.fr/hal-01924979

Patents

Other Publications

  • 37R. Azaïs, S. Ferrigno, M.-J. Martinez.

    An R package for Cramér-von Mises goodness-of-fit tests in regression models, December 2018, CMStatistics 2018 - 11th International Conference of the ERCIM WG on Computational and Methodological Statistics, Poster.

    https://hal.inria.fr/hal-01935348
  • 38B. Bastien, H. Chakir, A. Gégout-Petit, A. Muller-Gueudin, Y. Shi.

    A statistical methodology to select covariates in high-dimensional data under dependence. Application to the classification of genetic profiles associated with outcome of a non-small-cell lung cancer treatment, November 2018, working paper or preprint.

    https://hal.archives-ouvertes.fr/hal-01939694
  • 39L. Batista, L. Doerr, K. Juhasz, S. Stoelzle-Feix, M. Beckler, T. Bastogne.

    Mixed-effects modeling for concentration effect profiling in cardiomyocyte contractility assays, September 2018, Annual Meeting of Safety Pharmacology Society, SPS 2018, Présentation Poster.

    https://hal.archives-ouvertes.fr/hal-01925651
  • 40A. Deveau, A. Gégout-Petit, C. Karmann.

    Penalized polytomous ordinal logistic regression using cumulative logits. Application to network inference of zero-inflated variables, May 2018, working paper or preprint.

    https://hal.archives-ouvertes.fr/hal-01799914
  • 41A. Gégout-Petit, L. Guérin-Dubrana, S. Li.

    A new centered spatio-temporal autologistic regression model. Application to spatio-temporal analysis of esca disease in a vineyard, November 2018, https://arxiv.org/abs/1811.06782 - working paper or preprint.

    https://hal.inria.fr/hal-01926115
  • 42A. Lejay, L. Lenôtre, G. Pichot.

    An exponential timestepping algorithm for diffusion with discontinuous coefficients, June 2018, working paper or preprint.

    https://hal.inria.fr/hal-01806465
  • 43J.-M. Monnez, A. Skiredj.

    Convergence of a normed eigenvector stochastic approximation process and application to online principal component analysis of a data stream, July 2018, working paper or preprint.

    https://hal.archives-ouvertes.fr/hal-01844419
References in notes
  • 44R. 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.
  • 45R. 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.
  • 46R. 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
  • 47R. 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
  • 48R. Azaïs, A. Genadot.

    Level Crossings and Absorption of an Insurance Model, in: Statistical Inference for Piecewise-deterministic Markov Processes, R. Azaïs, F. Bouguet (editors), Wiley, August 2018, pp. 65-105. [ DOI : 10.1002/9781119507338.ch3 ]

    https://hal.archives-ouvertes.fr/hal-01862266
  • 49J. 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.
  • 50T. 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
  • 51T. Bastogne, A. Samson, P. Vallois, S. Wantz-Mézières, 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.
  • 52D. Bertsekas, J. Tsitsiklis.

    Neurodynamic Programming, Athena Scientific, 1996.
  • 53H. 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/
  • 54H. 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.
  • 55J. 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.
  • 56M. 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.
  • 57A. 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
  • 58M. 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.
  • 59S. 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.
  • 60S. Ferrigno, M. Maumy-Bertrand, A. Muller-Gueudin.

    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
  • 61J. Friedman, T. Hastie, R. Tibshirani.

    Sparse inverse covariance estimation with the graphical lasso, in: Biostatistics, 2008, vol. 9, no 3, pp. 432–441.
  • 62C. Giraud, S. Huet, N. Verzelen.

    Graph selection with GGMselect, in: Statistical applications in genetics and molecular biology, 2012, vol. 11, no 3.
  • 63T. Hansen, U. Zwick.

    Lower Bounds for Howard's Algorithm for Finding Minimum Mean-Cost Cycles, in: ISAAC (1), 2010, pp. 415-426.
  • 64S. 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
  • 65J. 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.
  • 66R. 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
  • 67R. Koenker.

    Quantile regression, Cambridge university press, 2005, no 38.
  • 68Y. A. Kutoyants.

    Statistical inference for ergodic diffusion processes, Springer Series in Statistics, Springer-Verlag London Ltd., London, 2004, xiv+481 p.
  • 69C. Lacaux.

    Real Harmonizable Multifractional Lévy Motions, in: Ann. Inst. Poincaré., 2004, vol. 40, no 3, pp. 259–277.
  • 70L. 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.
  • 71B. Lesner, B. Scherrer.

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

    https://hal.inria.fr/hal-01186664
  • 72T. Lyons, Z. Qian.

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

    http://books.google.com/books?id=H9fRQNIngZYC
  • 73N. Meinshausen, P. Bühlmann.

    High-dimensional graphs and variable selection with the lasso, in: The Annals of Statistics, 2006, pp. 1436–1462.
  • 74J.-M. Monnez.

    Approximation stochastique en analyse factorielle multiple, in: Ann. I.S.U.P., 2006, vol. 50, no 3, pp. 27–45.
  • 75J.-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
  • 76J.-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.
  • 77E. 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.
  • 78I. Post, Y. Ye.

    The simplex method is strongly polynomial for deterministic Markov decision processes, arXiv:1208.5083v2, 2012.
  • 79M. Puterman.

    Markov Decision Processes, Wiley, New York, 1994.
  • 80B. 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.
  • 81F. 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.
  • 82F. 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
  • 83B. 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
  • 84B. 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
  • 85B. 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
  • 86B. 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
  • 87B. 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
  • 88P. 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
  • 89P. Vallois.

    The range of a simple random walk on Z, in: Advances in applied probability, 1996, pp. 1014–1033.
  • 90N. 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
  • 91Y. 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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