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Menu Logo Principal AgroParisTech

MIA Paris

Céline Lévy-Leduc

Celine

Full Professor of Statistics

Co-head of the MMIP (Modélisation Mathématique, Informatique et Physique) department of AgroParisTech

Head of the "Stat & Genome" research group within the UMR MIA-Paris, which is an AgroParisTech-INRA research lab.

AgroParisTech (département MMIP)
16, Rue Claude Bernard
F-75231 Paris Cédex 05
France

Tél: 01.44.08.72.68
Fax: 01.44.08.16.66
EMail : celine.levy-leduc@agroparistech.fr

Publications

Articles in peer-reviewed journals

  1. M. Perrot-Dockès, C. Lévy-Leduc, L. Sansonnet, J. Chiquet. Variable selection in multivariate linear models with high-dimensional covariance matrix estimation, submitted.
  2. V. Brault, C. Lévy-Leduc, A. Mathieu, A. Jullien. Multivariate change-point estimation taking into account the dependence: Application to the vegetative development of oilseed rape, submitted.
  3. M. Perrot-Dockès, C. Lévy-Leduc, J. Chiquet, L. Sansonnet, M. Brégère, M.P. Etienne, S. Robin, G. Genta-Jouve. A multivariate variable selection approach for analyzing LC-MS metabolomics data, submitted.
  4. V. Brault, S. Ouadah, L. Sansonnet, C. Lévy-Leduc. Nonparametric homogeneity tests and multiple change-point estimation for analyzing large Hi-C data matrices, submitted.
  5. A. Bonnet, C. Lévy-Leduc, E. Gassiat, R. Toro, T. Bourgeron. Improving heritability estimation by a variable selection approach in sparse high dimensional linear mixed models, submitted.
  6. F.A. Fajardo, V.A. Reisen, C. Lévy-Leduc, M.S. Taqqu. Robust periodogram for time series with long-range dependence: an application to pollution levels, submitted
  7. A.M. Sgrancio, V.A. Reisen, F.A. Ziegelmann, E.Z. Monte, H. H. Aranda Cotta and C. Lévy-Leduc. Robust factor modeling for high-dimensional time series: An application to air pollution data, submitted.
  8. V. Brault, M. Delattre, E. Lebarbier, T. Mary-Huard, C. Lévy-Leduc. Estimating the number of change-points in a two-dimensional segmentation model without penalization, Scandinavian Journal of Statistics, vol. 44, n. 2, p. 563-580, 2017.
  9. V.A. Reisen, C. Lévy-Leduc, M.S. Taqqu. An M-estimator for the long-memory parameter, Journal of Statistical Planning and Inference, vol. 187, p. 44-55, 2017
  10. V. Brault, J. Chiquet, C. Lévy-Leduc. A fast approach for multiple change-point detection in two-dimensional data, Electronic Journal of Statistics, vol. 11, n. 1, p. 1570-1599, 2017.
  11. S. Chakar, E. Lebarbier, C. Lévy-Leduc, S. Robin. A robust approach to multiple change-point estimation in an AR(1) process, Bernoulli, vol. 23, n. 2, p. 1408-1447, 2017.
  12. V. A. Reisen, C. Lévy-Leduc, M. Bourguignon, H. Boistard. Robust Dickey-Fuller tests based on ranks for time series with additive outliers, Metrika, vol. 80, n. 1, p. 115–131, 2017.
  13. M. Jala, C. Lévy-Leduc, E. Moulines, E. Conil, J. Wiart. Sequential design of computer experiments for the assessment of fetus exposure to electromagnetic fields. Technometrics, vol. 58, n. 1, p. 30-42, 2016.
  14. A. Lung-Yut-Fong, C. Lévy-Leduc, O. Cappé. Homogeneity and change-point detection tests for multivariate data using rank statistics, Journal de la Société Française de Statistique, vol. 156, n. 4, p. 133-162, 2015[pdf]
  15. A. Bonnet, E. Gassiat, C. Lévy-Leduc. Heritability estimation in high dimensional linear mixed models. Electronic Journal of Statistics 2015, Vol. 9, n.2, p. 2099-2129, 2015. [pdf]
  16. C. Lévy-Leduc, M. Delattre, T. Mary-Huard, S. Robin. Two-dimensional segmentation for analyzing HiC data, Bioinformatics, vol. 30, n.17, p. 386-392, 2014.
  17. C. Lévy-Leduc, M. S. Taqqu. Hermite ranks and U-statistics, Metrika, vol. 77, n. 1, p 105-136, 2014
  18. V. A. Reisen, A.J. Sarnaglia, N.C Reis, C. Lévy-Leduc and J.M Santos. Modeling and forecasting daily average PM10 concentrations by a seasonal long-memory model with volatility, Environmental Modelling & Software, vol. 51, p. 286–295, 2014.
  19. C. Lévy-Leduc, M. S. Taqqu. Long-range dependence and the ranks of decompositions, AMS Contemporary Mathematics,vol. 601, p. 289-305, 2013
  20. O. Kouamo, C. Lévy-Leduc, E. Moulines. Central limit theorem for the robust log-regression wavelet estimation of the memory parameter in the Gaussian semi-parametric context, Bernoulli, vol. 19, n. 1, p. 172-204, 2013[pdf]
  21. A. Lung-Yut-Fong, C. Lévy-Leduc, O. Cappé. Distributed detection/localization of change-points in high-dimensional network traffic data, Statistics and Computing, vol. 22, n. 2, p. 485-496, 2012 [pdf]
  22. C. Lévy-Leduc, H. Boistard, E. Moulines, M. S. Taqqu, V. A. Reisen. Asymptotic properties of U-processes under long-range dependence, Annals of Statistics, vol. 39, n. 3, p. 1399-1426, 2011.[pdf]
  23. C. Lévy-Leduc, H. Boistard, E. Moulines, M. S. Taqqu, V. A. Reisen. Large sample behavior of some well-known robust estimators under long-range dependence, Statistics, vol. 45, n. 1, p. 59-71, 2011.[pdf]
  24. C. Lévy-Leduc, H. Boistard, E. Moulines, M. S. Taqqu, V. A. Reisen. Robust estimation of the scale and of the autocovariance function of Gaussian short and long-range dependent processes, Journal of Time Series Analysis, vol. 32, n. 2, p. 135-156, 2011.[pdf]
  25. Z. Harchaoui, C. Lévy-Leduc. Multiple change-point estimation with a total variation penalty, Journal of the American Statistical Association, vol. 105, n. 492, p. 1480-1493, 2010.[pdf]
  26. A. J. Q. Sarnaglia, V. A. Reisen, C. Lévy-Leduc. Robust estimation of periodic autoregressive processes in the presence of additive outliers, Journal of Multivariate Analysis, vol. 101, n. 9, p. 2168-2183, 2010.
  27. C. Lévy-Leduc, F. Roueff. Detection and localization of change-points in high-dimensional network traffic data, Annals of Applied Statistics, vol. 3, n. 2, p. 637-662, 2009.[pdf]
  28. C. Lévy-Leduc, E. Moulines, F. Roueff. Frequency estimation based on the cumulated Lomb-Scargle periodogram, Journal of Time Series Analysis, vol. 29, n. 6, p. 1104-1131, 2008.[pdf]
  29. I. Castillo, C. Lévy-Leduc, C. Matias. Exact adaptive estimation of a periodic function with unknown period, Mathematical Methods of Statistics, vol. 15, n. 2, p. 146-175, 2006.[pdf]
  30. E. Gassiat, C. Lévy-Leduc. Efficient semiparametric estimation of the periods in a superposition of periodic functions with unknown shape, Journal of Time Series Analysis, vol. 27, n. 6, p. 877-910, 2006.[pdf]
  31. C. Lévy-Leduc. Efficient frequency estimation from a particular almost periodic function, Journal of Time Series Analysis, vol. 27, n. 5, p.637-670, 2006.
  32. M. Fromont, C. Lévy-Leduc. Adaptive tests for periodic signals detection with applications to laser vibrometry, ESAIM Probability and Statistics, vol. 10, p. 46-75, 2005.[pdf]
  33. M. Lavielle, C. Lévy-Leduc. Semiparametric estimation of the frequency of unknown periodic functions and its application to laser vibrometry signals, IEEE Transactions on Signal Processing, vol. 53, n. 7, p. 2306-2315, 2005.[pdf]

Book chapters

  1. V.A. Reisen, C. Lévy-Leduc, H.H.A. Cotta. Long-memory models under outliers: an application to air pollution levels. Air and Noise Pollution, vol. 3 of the Series "Environmental Science and Engineering (12 Vols.)", 2017.
  2. C. Lévy-Leduc. Several approaches for detecting anomalies in network traffic data, In: Nicholas Heard, Niall Adams , Data analysis for network cyber-security. GBR : Niall Adams and Nicholas Heard, 2014.

Articles in proceedings

  1. V. Brault, J. Chiquet, C. Lévy-Leduc. Fast Detection of Block Boundaries in Block-wise Constant Matrices. Machine Learning and Data Mining, 2016.
  2. C. Lévy-Leduc, M. Delattre, T. Mary-Huard, S. Robin. Two-dimensional segmentation for analyzing HiC data, ECCB 2014.supplementary_eccb.pdf
  3. M. Jala, C. Lévy-Leduc, E. Moulines, E. Conil, J. Wiart. Sequential design of computer experiments for parameter estimation, EUSIPCO 2012.
  4. C. Lévy-Leduc, M. S. Taqqu, E. Moulines, H. Boistard, V. A. Reisen. Asymptotic properties of U-processes under long-range dependence and applications, Bulletin of the International Statistical Institute, 2011.
  5. A. Lung-Yut-Fong, C. Lévy-Leduc, O. Cappé. Estimation robuste de ruptures multiples dans un signal multivarié, GRETSI 2011.
  6. O. Kouamo, C. Lévy-Leduc, E. Moulines. Robust estimation of the memory parameter of Gaussian time series using wavelets, IEEE International Workshop on Statistical Signal Processing (SSP) 2011.
  7. A. Lung-Yut-Fong, C. Lévy-Leduc, O. Cappé. Robust retrospective multiple change-point estimation for multivariate data, IEEE International Workshop on Statistical Signal Processing (SSP) 2011.
  8. T. Rebafka, C. Lévy-Leduc, M. Charbit. Regularization methods for intercepted radar signals, IEEE Radar Conderence 2011.
  9. A. Lung-Yut-Fong, C. Lévy-Leduc, O. Cappé. Robust changepoint detection based on multivariate rank statistics, International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2011.
  10. A. Lung-Yut-Fong, C. Lévy-Leduc, O. Cappé. Distributed detection/localization of network anomalies using rank tests, IEEE International Workshop on Statistical Signal Processing (SSP) 2009.
  11. A. Lung-Yut-Fong, O. Cappé, C. Lévy-Leduc, F. Roueff. Détection et localisation décentralisées d'anomalies dans le trafic internet, GRETSI 2009.
  12. C. Lévy-Leduc. Detection of network anomalies using rank tests, EUSIPCO 2008.
  13. Z. Harchaoui, C. Lévy-Leduc. Catching change-points with Lasso, NIPS 2007
  14. B. Benmammar, C. Lévy-Leduc, F. Roueff. Algorithme de détection d'attaques de type SYN Flooding, GRETSI 2007.
  15. Z. Harchaoui, C. Lévy-Leduc. Méthode de détection de ruptures utilisant l'algorithme LARS, GRETSI 2007.
  16. C. Lévy-Leduc. Frequency estimation from a particular almost periodic function, ICASSP 2006.
  17. C. Lévy-Leduc, M. Prenat. Laser vibrometry: estimation of the frequency of a rotating object, PSIP 2005.
  18. C. Lévy-Leduc. Algorithmes d'estimation de la fréquence de fonctions périodiques inconnues et applications à la vibrométrie laser, GRETSI 2003

Science popularization

  1. C. Lévy-Leduc, S. Robin. Les nouveaux défis de la biologie moléculaire. Symbiose, 2015.

Softwares

1. M. Perrot-Dockès, C. Lévy-Leduc, J. Chiquet (2017). R package: MultiVarSel (available on the CRAN). This package is dedicated to the variable selection issue in high dimensional multivariate linear models taking into account the dependence between the columns of the observation matrix. The corresponding methodology is described in the paper: "A multivariate variable selection approach for analyzing LC-MS metabolomics data", arXiv:1704.00076.

2. A. Bonnet, C. Lévy-Leduc (2015). R package: EstHer (available on the CRAN) for estimating the heritability in high dimensional sparse linear mixed models using variable selection. The methodology used in this package is described in the paper "Improving heritability estimation by a variable selection approach in sparse high dimensional linear mixed models" by A. Bonnet, C. Lévy-Leduc, E. Gassiat, R. Toro, T. Bourgeron, arXiv:1507.06245.

3. C. Lévy-Leduc (2014). R package: HiCseg (available on the CRAN) which allows you to detect domains in HiC data. The methodology that is used in this package is described in the paper “Two-dimensional segmentation for analyzing HiC data” by C. Lévy-Leduc, M. Delattre, T. Mary-Huard and S. Robin, Bioinformatics, vol. 30, n.17, p. 386-392.

4. S. Chakar, E. Lebarbier, C. Lévy-Leduc, S. Robin (2014). R package: AR1seg (available on the CRAN) corresponds to the implementation of the robust approach for estimating change-points in the mean of an AR(1) Gaussian process by using the methodology described in the paper that we wrote arXiv 1403.1958

5. B. Benmammar, C. Lévy-Leduc, F. Roueff (2008). TopRank software (developped in C for detecting and localizing network anomalies), registered at the “Agence pour la Protection des Programmes”, IDDN.FR.001.100004.000.S.P.2008.000.20700, in 2008

Teaching