Agliz Y, Audigier V, Niang N, Nadif M (2025). “Joint dimensionality reduction and clustering with missing data.” In Advanced Machine Learning and Data Science.
Audigier V, Niang N (2023). “Handling missing data in clustering using multiple imputation.” In Ecosta Econometrics and Statistics, number ISBN 978-9925-7812-7-0. Invited session, https://hal.science/hal-04529644.
Audigier V, Niang N (2023). “Multiple imputation for clustering on incomplete data.” In ClaDAG 2023. Invited, https://hal.science/hal-04127937.
Ameur Y, Aziz R, Audigier V, Bouzefrane S (2022). “Secure and non-interactive k-NN classifier using symmetric fully homomorphic encryption.” In Domingo-Ferrer, J., Laurent, (eds) M (eds.), Privacy in Statistical Databases. PSD 2022. Lecture Notes in Computer Science, vol 13463, volume 13463 series Lecture Notes in Computer Science, 142-154. doi:10.1007/978-3-031-13945-1_11. https://hal.science/hal-03933277.
Audigier V, Niang N, Resche-Rigon M (2022). “Clustering with missing data: which imputation model for which cluster analysis method?” In 17th conference of the International Federation of Classification Societies.
Hassini H, Niang N, Audigier V (2021). “SOM-based clusterwise regression.” In Data Science, Statistics and Visualisation. https://hal.science/hal-03544471.
Audigier V, Niang N (2021). “Cluster analysis after multiple imputation.” In ASMDA 2021. https://hal.science/hal-03544485.
Audigier V, Resche Rigon M (2019). “micemd: a smart multiple imputation R package for missing multilevel data.” In UseR!2019. https://hal.science/hal-03543542.
Faucheux L, Resche-Rigon M, Audigier V, Curis E, Soumelis V, Chevret S (2019). “Clustering with missing data: Pooling multiple imputation results with consensus clustering.” In 40th Annual Conference of the International Society for Clinical Biostatistics. Tomasz Burzykowski, Leuven (BE), Belgium. https://hal.science/hal-04000687.
Audigier V, White I, Jolani S, Debray TPA, Quartagno M, van Buuren S, Resche-Rigon M (2018). “Multiple imputation for multilevel data with continuous and binary variables.” In Chimiométrie XIX. Conservatoire National des Arts et Métiers and Société Française de Statistique, CNAM Paris, France. https://hal.science/hal-04000640.
Audigier V, White I, Jolani S, Debray T, Quartagno M, Carpenter J, van Buuren S, Resche-Rigon M (2016). “Comparison of multiple imputation methods for systematically and sporadically missing multilevel data.” In 37th Annual Conference of The International Society for Clinical Biostatistics.
Audigier V, Husson F, Josse J (2015). “Multiple imputation for categorical variables with multiple correspondence analysis.” In Correspondence Analysis and Related Methods 2015.
Audigier V, Husson F, Josse J (2015). “Multiple imputation for categorical data using MCA.” In missDATA2015. Agrocampus Ouest, Rennes, France.
Josse J, Husson F, Audigier V (2013). “Imputation methods in mixed datasets: Random forests versus PCA.” In 6th International Conference of the ERCIM WG on Computational and Methodological Statistics. https://www.cmstatistics.org/ERCIM2013/docs/BoA.pdf.
Husson F, Audigier V, Josse J (2012). “Missing values imputation for mixed data based on principal component methods.” In 20th International Conference on Computational Statistics. European Regional Section of the IASC, Limassol, Cyprus. http://www.compstat2012.org/.
Diallo B, Niang N, Bouhadjera F, Audigier V (2026). “Classification de données fonctionnelles et vectorielles.” In 57èmes Journées de Statistique. Société Française de Statistique, Clermond-Ferrand, France. https://hal.science/hal-05589708.
Audigier V, Niang N (2023). “Multiple imputation for clustering on incomplete data.” In Artificial intelligence for data science and cybersecurity machine learning workshop. Université Paris Cité, Paris, France. https://hal.science/hal-05575699.
Diallo B, Niang N, Audigier V, Bouhadjera F (2026). “Comparaison de méthodes de classification de données fonctionnelles.” Revue des Nouvelles Technologies de l’Information, Extraction et Gestion des Connaissances, RNTI-E-42, 121-132. https://hal.science/hal-05488620.
Agliz Y, Audigier V, Nadif M, Niang N (2025). “Clustering et réduction de la dimension avec données manquantes.” In 56ièmes Journées de Statistique de la SFDS. https://hal.science/hal-05047399.
Agliz Y, Audigier V, Nadif M, Niang N (2025). “Étude de variabilité par bootstrap résiduel pour une méthode de subspace clustering.” In 30emes Rencontres de la Société Francophone de Classification. https://hal.science/hal-05047407.
Audigier V, Niang N (2024). “Classification de données incomplètes par imputation multiple.” In 29èmes Rencontres de la Société Francophone de Classification. Société Francophone de Classification, Marseille (CIRM, Centre International de Rencontres Mathématiques), France. Invited, https://hal.science/hal-04696382.
Audigier V (2024). “Gestion des données manquantes.” In 29èmes Rencontres de la Société Francophone de Classification. Société Francophone de Classification, Marseille (CIRM, Centre International de Rencontres Mathématiques), France. Invited, https://hal.science/hal-04696568.
Agliz Y, Audigier V, Nadif M, Niang N (2024). “Subspace clustering sur données incomplètes par imputation multiple.” In 29èmes Rencontres de la Société Francophone de Classification. Société Francophone de Classification, Marseille (CIRM, Centre International de Rencontres Mathématiques), France. https://hal.science/hal-04696477.
Audigier V (2024). “Clustering sur données incomplètes avec clusterMI.” In 10èmes Rencontres R. Société Française de Statistique, Vannes (Bretagne, France), France. https://hal.science/hal-04550305.
Agliz Y, Audigier V, Niang N (2024). “Subspace clustering sur données incomplètes.” In 55èmes Journées de Statistique. SFDS, Bordeaux, France. https://hal.science/hal-04529094.
Audigier V, Sadou Zouleya F (2023). “Clustering sur données incomplètes : méthodes directes ou imputation multiple ?” In Les 54èmes Journées de Statistique. SFDS, Bruxelles, Belgium. https://hal.science/hal-04127905.
Audigier V, Resche-Rigon M, Bonneville EF (2022). “Gestion des données manquantes pour les analyses de survie.” In EPICLIN 2022, 29èmes journées des statisticiens des CLCC. Stefan Michiels and Xavier Paoletti, Paris, France. https://hal.science/hal-03953885.
Audigier V, Niang N, Resche-Rigon M (2021). “Clustering sur données incomplètes~: quel modèle d’imputation choisir~?” In EPICLIN 2021 – 15e Conférence francophone d’épidémiologie clinique – 28e Journées des statisticiens des centres de lutte contre le cancer, volume 69, S21-S22. Aix-Marseille Université and Institut Paoli-Calmettes de Marseille, Marseille, France. doi:10.1016/j.respe.2021.04.035. https://hal.science/hal-03542951.
Audigier V, Husson F, Josse J, Resche-Rigon M (2019). “Imputation multiple pour données mixtes par analyse factorielle.” In JdS2019 - 51es Journées de Statistique de la Société Française de Statistique. Société Française de Statistique, Vandœuvre-lès-Nancy, France. https://institut-agro-rennes-angers.hal.science/hal-02355840.
Audigier V, Bar-Hen A (2019). “An ensemble learning method for variable selection with missing values.” In Sino-French meeting. https://hal.science/hal-05575823.
Bar-Hen A, Audigier V (2018). “Une méthode d’ensemble pour la sélection de variables : application à la grande dimension et aux données manquantes.” In 50emes journées de la statistique. SFDS, Saclay, France. https://hal.science/hal-04000662.
Audigier V, White I, Jolani S, Debray TPA, van Buuren S, Resche-Rigon M (2018). “Multiple imputation for multilevel data with continuous and binary variables.” In Journée de rencontres scientifiques autour de la statistique pour la biologie et la médecine. LMA, Univ. Poitiers, Poitiers (Université de Poitiers), France. https://hal.science/hal-04000648.
Audigier V, White I, Jolani S, Debray T, Quartagno M, Carpenter J, van Buuren S, Resche-Rigon M (2016). “Comparison of multiple imputation methods for systematically and sporadically missing multilevel data.” Journées GDR / SFB 2016.
Audigier V (2015). “Multiple imputation with MCA.” Rencontres doctorales Lebesgue 2015. Université de Nantes, https://www.lebesgue.fr/fr/content/doctorales2015.
Audigier V, Husson F, Josse J (2015). “Imputation multiple pour variables qualitatives par analyse des correspondances multiples.” In JdS2015 - 47èmes Journées de Statistique de la Société Française de Statistique. Société Française de Statistique, Lille, France. https://papersjds15.sfds.asso.fr/submission_176.pdf.
Audigier V, Husson F, Josse J (2014). “Imputation multiple pour variables quantitatives par analyse en composantes principales Bayésienne.” In JdS2014 - 46èmes Journées de Statistique de la Société Française de Statistique. Société Française de Statistique, Rennes, France. https://papersjds14.sfds.asso.fr/submission_134.pdf.
Audigier V (2014). “Multiple imputation with MCA.” Journées STAR 2014. Université Rennes 1, https://perso.univ-rennes1.fr/valerie.monbet/JSTAR2014.html.
Audigier V, Husson F, Josse J (2013). “Imputation multiple à l’aide des méthode d’analyse factorielle.” In JdS2013 - 45èmes Journées de Statistique de la Société Française de Statistique. Société Française de Statistique, Toulouse, France.
Audigier V, Husson F, Josse J (2012). “Imputation de données manquantes pour des données mixtes via les méthodes factorielles grâce à missMDA.” In 1ères Rencontres R. https://hal.science/hal-00716876.
Audigier V, Niang N (2023). “Multiple imputation for clustering on incomplete data.” In Séminaire du Laboratoire de Mathématiques de Bretagne. https://hal.science/hal-05575596.
Audigier V, Niang N (2023). “Multiple imputation for clustering on incomplete data.” In Séminaire du laboratoire ERIC. Laboratoire ERIC, Lyon, France. https://hal.science/hal-05575648.
Audigier V, Niang N, Resche-Rigon M (2021). “Clustering with missing data: which imputation model for which cluster analysis method?” In Missing Data, Imputation & Analysis seminar. Missing Data, Imputation & Analysis group, Londres, France. https://hal.science/hal-05575746.
Audigier V, Niang N, Resche-Rigon M (2021). “Clustering with missing data: which imputation model for which cluster analysis method?” In Séminaire de Statistique du MAP5. MAP5, Paris, France. https://hal.science/hal-05575768.
Audigier V, Bar-Hen A (2019). “An ensemble learning method for variable selection: application to high dimensional data and missing values.” In Séminaire du Service de Biostatistique et Information Médicale de l’Hôpital Saint-Louis. https://hal.science/hal-05575806.
Audigier V, White I, Jolani S, Debray T, Quartagno M, Carpenter J, van Buuren S, Resche-Rigon M (2017). “Multiple imputation for multilevel data with continuous and binary variables.” In Séminaire de Statistique et Probabilités Appliquées du Laboratoire Jean Kuntzmann. Laboratoire Jean Kuntzmann, Grenoble, France. https://hal.science/hal-05575965.
Audigier V, Bar-Hen A (2018). “An ensemble learning method for variable selection.” In Missing Data, Imputation & Analysis Seminar. Missing Data, Imputation & Analysis group, Londres, United Kingdom. https://hal.science/hal-05575936.
Audigier V, Husson F, Josse J (2017). “Multiple imputation with principal component methods.” Presented at the Data Science Seminar of the LTCI.
Audigier V (2017). “Handling missing data by multiple imputation.” In MSDMA Seminar. Laboratoire CEDRIC, Paris, France. https://hal.science/hal-05576031.
Audigier V, White I, Jolani S, Debray T, Quartagno M, Carpenter J, van Buuren S, Resche-Rigon M (2016). “Comparison of multiple imputation methods for systematically and sporadically missing multilevel data.” Presented at the INRIA MODAL Seminar.
Audigier V, White I, Jolani S, Debray T, Quartagno M, Carpenter J, van Buuren S, Resche-Rigon M (2016). “Comparison of multiple imputation methods for systematically and sporadically missing multilevel data.” Presented at the Missing Data, Imputation & Analysis Seminar.
Audigier V, Husson F, Josse J (2016). “Imputation multiple par analyse factorielle.” Presented at the IRMA Seminar.
Audigier V, Husson F, Josse J (2016). “Multiple imputation with principal component methods.” Presented at the Missing Data, Imputation & Analysis Seminar.
Audigier V, Husson F, Josse J (2016). “Multiple imputation with principal component methods.” Presented at the ISPED Seminar.
Audigier V, Husson F, Josse J (2015). “Multiple imputation with principal component methods.” Presented at the SBIM Seminar.
Josse J, Husson F, Audigier V (2014). “Multiple imputation with Bayesian PCA.” Presented at the IMB Seminar.
Zenuni A, Resche-Rigon M, Audigier V (2022). “Multiple imputation for heterogeneous biological data.” diiP Workshop Day: Data intelligence Problems and Ideas. Poster, https://hal.science/file/index/docid/5574843/filename/posterImputationMultiple.pdf.
Audigier V, White I, Jolani S, Debray T, Quartagno M, Carpenter J, van Buuren S, Resche-Rigon M (2017). “Multiple imputation for multilevel data with continuous and binary variables.” In 8th International Meeting Statistical Methods in Biopharmacy. https://hal.science/file/index/docid/5574823/filename/poster_audigier_smb2017.pdf.