Bibliography

Publications of the year

Articles in International Peer-Reviewed Journals

• 1G. Celeux, C. Maugis-Rabusseau, M. Sedki.
  
  Variable selection in model-based clustering and discriminant analysis with a regularization approach, in: Advances in Data Analysis and Classification, 2018. [ DOI : 10.1007/s11634-018-0322-5 ]
  
  https://hal.inria.fr/hal-01053784
• 2F. Ducros, P. Pamphile.
  
  Bayesian estimation of Weibull mixture in heavily censored data setting, in: Reliability Engineering and System Safety, December 2018.
  
  https://hal.archives-ouvertes.fr/hal-01645618
• 3S. Fourati, A. Talla, M. Mahmoudian, J. Burkhart, R. Klén, R. Henao, T. Yu, Z. Aydın, K. Y. Yeung, M. E. Ahsen, R. Almugbel, S. Jahandideh, X. Liang, T. Nordling, M. Shiga, A. Stanescu, R. Vogel, G. Pandey, C. Chiu, M. McClain, C. Woods, G. Ginsburg, L. Elo, E. Tsalik, L. Mangravite, S. Sieberts, K. Bleakley.
  
  A crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection, in: Nature Communications, December 2018, vol. 9, n^o 1.
  
  https://hal.inria.fr/hal-01960254
• 4D. Garreau, S. Arlot.
  
  Consistent change-point detection with kernels, in: Electronic journal of statistics , December 2018, vol. 12, n^o 2, pp. 4440-4486, https://arxiv.org/abs/1612.04740.
  
  https://hal.archives-ouvertes.fr/hal-01416704
• 5F. Le Billan, L. Amazit, K. Bleakley, Q.-Y. Xue, E. Pussard, C. Lhadj, P. Kolkhof, S. Viengchareun, J. Fagart, M. Lombes.
  
  Corticosteroid receptors adopt distinct cyclical transcriptional signatures, in: FASEB Journal, October 2018, vol. 32, n^o 10, pp. 5626-5639.
  
  https://hal.inria.fr/hal-01960262
• 6I. Nikolayeva, P. Bost, I. Casademont, V. Duong, F. Koeth, M. Prot, U. Czerwinska, S. Ly, K. Bleakley, T. Cantaert, P. Dussart, P. Buchy, E. Simon-Loriere, A. Sakuntabhai, B. Schwikowski.
  
  A Blood RNA Signature Detecting Severe Disease in Young Dengue Patients at Hospital Arrival, in: Journal of Infectious Diseases, June 2018, vol. 217, n^o 11, pp. 1690-1698. [ DOI : 10.1093/infdis/jiy086 ]
  
  https://hal.inria.fr/hal-01960247
• 7L. Raynal, J.-M. Marin, P. Pudlo, M. Ribatet, C. Robert, A. Estoup, O. Stegle.
  
  ABC random forests for Bayesian parameter inference, in: Bioinformatics, October 2018.
  
  https://hal.archives-ouvertes.fr/hal-01961126

Invited Conferences

• 8C. Keribin, G. Celeux, V. Robert.
  
  The Latent Block Model: a useful model for high dimensional data, in: Mixture models : Theory and applications, Paris, France, June 2018.
  
  https://hal.archives-ouvertes.fr/hal-01957710

International Conferences with Proceedings

• 9F. Chazal, V. Divol.
  
  The density of expected persistence diagrams and its kernel based estimation, in: Symposium of Computational Geometry (SoCG 2018), Budapest, Hungary, June 2018, Extended version of a paper to appear in the proceedings of the Symposium of Computational Geometry 2018.
  
  https://hal.archives-ouvertes.fr/hal-01716181

Conferences without Proceedings

• 10C. Biernacki, B. Auder, G. Celeux, J. Demont, F. Langrognet, V. Kubicki, C. Poli, J. Renault.
  
  MASSICCC: A SaaS Platform for Clustering and Co-Clustering of Mixed Data, in: Workshop MixStatSeq: “Mixture models: Theory and applications”, Paris, France, June 2018.
  
  https://hal.archives-ouvertes.fr/hal-01949175
• 11C. Biernacki, G. Celeux, J. Josse, F. Laporte.
  
  Dealing with missing data in model-based clustering through a MNAR model, in: CMStatistics 2018 - 11th International Conference of the ERCIM WG on Computational and Methodological Statistics, Pise, Italy, December 2018.
  
  https://hal.archives-ouvertes.fr/hal-01949120
• 12C. Keribin, C. Biernacki.
  
  Co-clustering: A versatile way to perform clustering in high dimension, in: The 11th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2018), Pise, Italy, December 2018.
  
  https://hal.archives-ouvertes.fr/hal-01949116

Scientific Books (or Scientific Book chapters)

• 13S. Arlot.
  
  Cross-validation, in: Apprentissage statistique et données massives, M. Maumy-Bertrand, G. Saporta, C. Thomas-Agnan (editors), Editions Technip, May 2018, https://arxiv.org/abs/1703.03167.
  
  https://hal.archives-ouvertes.fr/hal-01485508
• 14S. Arlot.
  
  Tutorial on statistical learning, in: Apprentissage statistique et données massives, M. Maumy-Bertrand, G. Saporta, C. Thomas-Agnan (editors), Editions Technip, May 2018.
  
  https://hal.archives-ouvertes.fr/hal-01485506
• 15G. Celeux, S. Frühwirth-Schnatter, C. Robert.
  
  Model Selection for Mixture Models-Perspectives and Strategies, in: Handbook of Mixture Analysis, CRC Press, December 2018.
  
  https://hal.archives-ouvertes.fr/hal-01961077
• 16S. Frühwirth-Schnatter, G. Celeux, C. P. Robert.
  
  Handbook of Mixture Analysis, Chapman & Hall/CRC Handbooks of Modern Statistical Methods, CRC Press, November 2018, pp. 1-536.
  
  https://hal.inria.fr/hal-01928103
• 17C. Robert, G. Celeux, K. Kamary, G. Malsiner-Walli, J.-M. Marin.
  
  Computational Solutions for Bayesian Inference in Mixture Models, in: Handbook of Mixture Analysis, CRC Press, December 2018, https://arxiv.org/abs/1812.07240.
  
  https://hal.archives-ouvertes.fr/hal-01961038

Internal Reports

• 18Y. Auffray.
  
  A variational interpretation of classification EM, Dassault Aviation, September 2018.
  
  https://hal.inria.fr/hal-01882980
• 19M. Lerasle, Z. Szabó, T. Mathieu, G. Lecué.
  
  MONK – Outlier-Robust Mean Embedding Estimation by Median-of-Means, CNRS / LMO - Laboratoire de Mathématiques d'Orsay, Orsay ; Ecole Polytechnique (Palaiseau, France) ; Laboratoire de Mathématiques d'Orsay ; ENSAE ParisTech ; Inria Saclay, équipe SELECT, October 2018.
  
  https://hal.archives-ouvertes.fr/hal-01705881

Other Publications

• 20E. Aamari, J. Kim, F. Chazal, B. Michel, A. Rinaldo, L. Wasserman.
  
  Estimating the Reach of a Manifold, January 2018, https://arxiv.org/abs/1705.04565 - working paper or preprint.
  
  https://hal.archives-ouvertes.fr/hal-01521955
• 21S. Arlot, S. Marmi, D. Papini.
  
  Coupling the Yoccoz-Birkeland population model with price dynamics: chaotic livestock commodities market cycles, May 2018, https://arxiv.org/abs/1803.05404 - 26 pages, 19 figures.
  
  https://hal.archives-ouvertes.fr/hal-01812794
• 22M. Baelde, C. Biernacki, R. Greff.
  
  Real-Time Monophonic and Polyphonic Audio Classification from Power Spectra, July 2018, working paper or preprint.
  
  https://hal.archives-ouvertes.fr/hal-01834221
• 23C. Brécheteau, A. Fischer, C. Levrard.
  
  Robust Bregman Clustering, December 2018, https://arxiv.org/abs/1812.04356 - working paper or preprint.
  
  https://hal.archives-ouvertes.fr/hal-01948051
• 24G. Chinot, G. Lecué, M. Lerasle.
  
  Statistical learning with Lipschitz and convex loss functions, November 2018, https://arxiv.org/abs/1810.01090 - working paper or preprint. [ DOI : 10.01090 ]
  
  https://hal.archives-ouvertes.fr/hal-01923033
• 25A. HAVET, M. Lerasle, É. Moulines.
  
  Density estimation for RWRE, June 2018, https://arxiv.org/abs/1806.05839 - working paper or preprint.
  
  https://hal.archives-ouvertes.fr/hal-01815990
• 26S. Le Corff, M. Lerasle, E. Vernet.
  
  A Bayesian nonparametric approach for generalized Bradley-Terry models in random environment, August 2018, https://arxiv.org/abs/1808.08104 - working paper or preprint.
  
  https://hal.archives-ouvertes.fr/hal-01860352
• 27G. Lecué, M. Lerasle.
  
  Robust machine learning by median-of-means : theory and practice, November 2018, https://arxiv.org/abs/1711.10306 - 48 pages, 6 figures.
  
  https://hal.archives-ouvertes.fr/hal-01923036
• 28G. Lecué, M. Lerasle, T. Mathieu.
  
  Robust classification via MOM minimization, November 2018, https://arxiv.org/abs/1808.03106 - working paper or preprint.
  
  https://hal.archives-ouvertes.fr/hal-01923035
• 29Y. Liu, C. Keribin, T. Popova, Y. Rozenholc.
  
  Statistical estimation of genomic alterations of tumors, January 2018, working paper or preprint.
  
  https://hal.inria.fr/hal-01688885
• 30M.-L. J. Nguyen.
  
  Nonparametric method for sparse conditional density estimation in moderately large dimensions, January 2018, https://arxiv.org/abs/1801.06477 - working paper or preprint.
  
  https://hal.archives-ouvertes.fr/hal-01688664
• 31C. Robert, G. Celeux, J. Jewson, J. Josse, J.-M. Marin, C. P. Robert.
  
  Some discussions on the Read Paper "Beyond subjective and objective in statistics" by A. Gelman and C. Hennig, January 2019, https://arxiv.org/abs/1705.03727 - working paper or preprint.
  
  https://hal.archives-ouvertes.fr/hal-01968779