Ndeye Niang

Ndeye Niang

Professor
Team: Méthodes statistiques de data-mining et apprentissage
Personal website:
Office: 35.3.10

2025

Journal Articles

  1. Ndao, M. L.; Youness, G.; Niang, N. and Saporta, G. Improving predictive maintenance: Evaluating the impact of preprocessing and model complexity on the effectiveness of eXplainable Artificial Intelligence methods. In Engineering Applications of Artificial Intelligence, 144: 110144, 2025. doi  www 

Conference Articles

  1. Agliz, Y.; Audigier, V.; Nadif, M. and Niang, N. 'Etude de variabilité par bootstrap résiduel pour une méthode de subspace clustering. In 30emes Rencontres de la Société Francophone de Classification, Dijon, France, 2025. www 
  1. Brito, P.; Niang, N.; Duarte Silva, A. P. and Bougeard, S. Multiblock Analysis of Distributional Data. In 9th conference of Data Science, Statistics, and Visualisation (DSSV 2025), Kruger National Park, South Africa, 2025. www 
  1. Agliz, Y.; Audigier, V.; Niang, N. and Nadif, M. Joint dimensionality reduction and clustering with missing data. In Advanced Machine Learning and Data Science, TOKYO, Japan, 2025. www 
  1. Niang, N.; Ouattara, M. and Ndao, M. L. Sparse weighted multi-view clustering. In 9th conference of Data Science, Statistics, and Visualisation (DSSV 2025), Kruger National Park, South Africa, 2025. www 
  1. Brito, P.; Niang, N.; Duarte Silva, A. P. and Bougeard, S. Multiblock Analysis of Distributional Data. In Symbolic Data Analysis Workshop 2025, Varav zdin, Croatia, 2025. www 
  1. Ndao, M. L.; Niang, N.; Youness, G. and Saporta, G. Enhancing Fuzzy Forests with Consensus Clustering for Unbiased and Robust Feature Selection. In JOCLAD 2025, pages 85-86, Porto, Portugal, 2025. www 
  1. Ndao, M. L.; Youness, G.; Niang, N. and Saporta, G. Une approche divisive et interprétable de réduction de dimension pour la prédiction de la RUL. In JDS2025: 56ièmes Journées de Statistique de la SFDS, Marseille, France, 2025. www 
  1. Ndao, M. L.; Youness, G.; Niang, N. and Saporta, G. A Divisive Unsupervised Feature Selection Approach for~Explainable Remaining Useful Life Prediction. In Database and Expert Systems Applications. DEXA 2025. Lecture Notes in Computer Science, pages 270-286, Springer Nature Switzerland, Bangkok, Thailand, Lecture Notes in Computer Science 16047, 2025. doi  www 
  1. Dieye, N. A.; Russolillo, G. and Niang, N. Assessing the capability of supervised classifiers to recover the true underlying probabilities. In International conference on Advanced Machine Learning and Data Science, Tokyo, Japan, 2025. www 
  1. Dieye, N. A.; Russolillo, G. and Niang, N. When standard calibration metrics fail in evaluating classifier calibration: A simulation study. In ClaDAG 2025, Naples, Italy, 2025. www 

Unpublished

  1. Zhang, Y.; Niang, N.; Saporta, G.; Wang, H. and Zhao, J. Incremental Singular Value Decomposition for Streaming and Scalable Network Embedding. , working paper or preprint. doi  www 

2024

Journal Articles

  1. Abdi, H.; Guillemot, V.; Liu, R.; Niang, N.; Saporta, G. and Yu, J-c. From Plain to Sparse Correspondence Analysis: a Generalized SVD Approach. In Statistica Applicata - Italian Journal of Applied Statistics, 35 (3): 301-338, 2024. doi  www 

Conference Articles

  1. Brito, P.; Dias, S. and Niang, N. Quality Measures for Clusterwise Regression. In 18th conference of the International Federation of Classification Societies, San José, Costa Rica, 2024. www 
  1. Niang, N.; Ouattara, M. and Saporta, G. Clustering variables: a survey and some new developments. In Sensometrics 2024, Paris, France, 2024. www 
  1. Dieye, N. A.; Russolillo, G. and Niang, N. Sensibilité des indices de qualité d'un classifieur probabiliste. In 55ièmes Journées de Statistique, Bordeaux, France, 2024. www 
  1. Agliz, Y.; Audigier, V.; Nadif, M. and Niang, N. Subspace clustering sur données incomplètes par imputation multiple. In 29èmes Rencontres de la Société Francophone de Classification, Marseille (CIRM, Centre International de Rencontres Mathématiques), France, 2024. www 
  1. Niang, N. Unsupervised learning for multiview data. In XXXI Conference on Classification and Data Analysis (JOCLAD 2024), Leiria, Portugal, 2024. www 
  1. Agliz, Y.; Audigier, V. and Niang, N. Subspace clustering sur données incomplètes. In 55èmes Journées de Statistique, Bordeaux, France, 2024. www 
  1. Serbouh, C.; Ahriz, I.; Niang, N. and Piperno, A. Predictive Modeling of Autonomous Vehicle Behavior With Imbalanced & Mixed Data. In 2024 International Conference on Software, Telecommunications and Computer Networks (SoftCOM), pages 1-6, IEEE, Split, France, 2024. doi  www 
  1. Niang, N. and Ouattara, M. Weighted Consensus Clustering for Unbiased Feature Importance in Random Forests. In 18th conference of the International Federation of Classification Societies, San José, Costa Rica, 2024. www 
  1. Ndao, L. M.; Youness, G.; Niang, N. and Saporta, G. Effet de la complexité du réseau LSTM sur léxplicabilité en Maintenance Prédictive. In JdS 2024: 55ièmes Journées de Statistique, Bordeaux, France, 2024. www 
  1. Ndao, M-L.; Youness, G.; Niang, N. and Saporta, G. Enhancing Explainability in Predictive Maintenance : Investigating the Impact of Data Preprocessing Techniques on XAI Effectiveness. In Florida Online Journals. Proceedings of FLAIRS, Florida, United States, Special Track: Explainable, Fair, and Trustworthy AI 37, 2024. doi  www 
  1. Audigier, V. and Niang, N. Classification de données incomplètes par imputation multiple. In 29èmes Rencontres de la Société Francophone de Classification, Marseille (CIRM, Centre International de Rencontres Mathématiques), France, 2024. www 

Miscellaneous

  1. Dieye, N. A.; Niang, N. and Russolillo, G. Sensibilité des indices de qualité d'un classifieur probabiliste. , Poster. www 

2023

Journal Articles

  1. Bry, X.; Niang, N.; Verron, T. and Bougeard, S. Clusterwise elastic-net regression based on a combined information criterion. In Advances in Data Analysis and Classification, 17: 75-107, 2023. doi  www 
  1. Liu, R.; Niang, N.; Saporta, G. and Wang, H. Sparse correspondence analysis for large contingency tables. In Advances in Data Analysis and Classification, 17 (4): 1037-1056, 2023. doi  www 

Conference Articles

  1. Liu, R.; Niang, N. and Saporta, G. Sparse non-symmetrical correspondence analysis. In CARME - Correspondence Analysis and Related Methods, Bonn, Germany, 2023. www 
  1. Niang, N.; Ouattara, M. and Saporta, G. A comparison of some methods for clustering of variables of mixed types. In Programme and Book of Abstracts, pages 85-86, Viana Do Castelo, Portugal, 2023. www 
  1. Audigier, V. and Niang, N. Multiple imputation for clustering on incomplete data. In ClaDAG 2023, Salerno (Italy), Italy, 2023. www 
  1. Niang, N.; Ouattara, M. and Saporta, G. Une comparaison de quelques méthodes de classification de variables mixtes. In Rencontres de la Société Francophone de Classification, pages 115-116, Strasbourg, France, 2023. www 
  1. Ndao, M-L.; Youness, G.; Niang, N. and Saporta, G. Une revue systématique de la littérature autour du biais, de l'équité et de léxplicabilité. In CNIA 2023 - Conférence Nationale en Intelligence Artificielle, pages 87-98, Strasbourg, France, 2023. www 
  1. Audigier, V. and Niang, N. Handling missing data in clustering using multiple imputation. In Ecosta Econometrics and Statistics, Berlin (Germany), Germany, 2023. www 
  1. Ndao, M-L.; Niang, N.; Youness, G. and Saporta, G. Consensus de partitions en NLP pour une revue systématique de la littérature autour de l'XAI du biais et de l'équité. In Rencontres de la Société Francophone de Classification, pages 43-48, Strasbourg, France, 2023. www 

2022

Journal Articles

  1. Audigier, V. and Niang, N. Clustering with missing data: which equivalent for Rubin's rules?. In Advances in Data Analysis and Classification, 2022. doi  www 

Conference Articles

  1. Audigier, V.; Niang, N. and Resche-Rigon, M. Clustering with missing data: which imputation model for which cluster analysis method?. In 17th conference of the International Federation of Classification Societies, Porto, Portugal, 2022. www 

2021

Conference Articles

  1. Bougeard, S.; Bry, X.; Verron, T. and Niang, N. Combined-information criterion for clusterwise elastic-net regression. Application to omic data. In 8th Channel Network Conference, Paris, France, 2021. www 
  1. Audigier, V.; Niang, N. and Resche-Rigon, M. 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, pages S21-S22, Elsevier Masson, Marseille, France, 2021. doi  www 
  1. Audigier, V. and Niang, N. Cluster analysis after multiple imputation. In ASMDA 2021, Athènes, Greece, 2021. www 
  1. Diallo, A. W.; Niang, N. and Ouattara, M. Sparse Subspace K-means. In 3rd IEEE ICDM Workshop on Deep Learning and Clustering. In conjunction with IEEE ICDM 2021 December 7-10, 2021., pages 678-685, IEEE, Auckland, New Zealand, 2021. doi  www 
  1. Fateri Gouard, N.; Niang, N. and Ouattara, M. Unbiased Feature selection in Random Forests using Consensus Feature Clustering. In Data Science, Statistics & Visualisation(DSSV) and European Conference on Data Analysis (ECDA), Rotterdam, Netherlands, 2021. www 
  1. Hassini, H.; Niang, N. and Audigier, V. SOM-based clusterwise regression. In Data Science, Statistics and Visualisation, Rotterdam, Netherlands, 2021. www 
  1. Niang-Keita, N.; Ouattara, M. and Saporta, G. Sparse Divisive Feature Clustering. In Program and Book of Abstracts, pages 75-76, Covilh~a, Portugal, Program and Book of Abstracts , 2021. www 

Unpublished

  1. Audigier, V.; Niang, N. and Resche-Rigon, M. Clustering with missing data: which imputation model for which cluster analysis method?. , working paper or preprint. www 

2020

Journal Articles

  1. Yala, K.; Niang, N.; Brajard, J.; Mejia, C.; Ouattara, M.; El Hourany, R.; Crépon, M. and Thiria, S. Estimation of phytoplankton pigments from ocean-color satellite observations in the Senegalo--Mauritanian region by using an advanced neural classifier. In Ocean Science, 16 (2): 513-533, 2020. doi  www 

Unpublished

  1. Liu, R.; Niang, N.; Saporta, G. and Wang, H. Sparse Correspondence Analysis for Contingency Tables. , working paper or preprint. www 
  1. Audigier, V. and Niang, N. Clustering with missing data: which equivalent for Rubin's rules?. , 39 pages. www 

2019

Journal Articles

  1. Bougeard, S.; Chauvin, C.; Saporta, G. and Niang, N. Régression multibloc sur classes latentes. Application `a l'usage d'antibiotiques en élevages de lapins. In Epidémiologie et Santé Animale, 76: 43-53, 2019. www 

Conference Articles

  1. Niang, N. and Ouattara, M. Weighted consensus clustering for multiblock data. In Actes SFC 2019, Paris, France, 2019. www 
  1. Saporta, G.; Liu, R.; Niang Keita, N. and Wang, H. Sparse Methods for Unsupervised Data Analysis. In The 4th International Symposium on Interval Data Modelling (SIDM 2019), Pékin, China, 2019. www 
  1. Saporta, G.; Liu, R.; Niang Keita, N. and Wang, H. Sparse Correspondence Analysis. In ASMDA 2019. 18th Conference of the Applied Stochastic Models and Data Analysis International Society, Florence, Italy, 2019. www 

2018

Journal Articles

  1. Bougeard, S.; Cariou, V.; Saporta, G. and Niang, N. Prediction for regularized clusterwise multiblock regression. In Applied Stochastic Models in Business and Industry, 34 (6): 852-867, 2018. doi  www 
  1. Bougeard, S.; Abdi, H.; Saporta, G. and Niang, N. Clusterwise analysis for multiblock component methods. In Advances in Data Analysis and Classification, 12 (2): 285-313, 2018. doi  www 
  1. Beck, G.; Azzag, H.; Bougeard, S.; Lebbah, M. and Niang, N. A New Micro-Batch Approach for Partial Least Square Clusterwise Regression. In Procedia Computer Science, 144: 239-250, 2018. doi  www 
  1. Bougeard, S.; Niang Keita, N.; Bry, X. and Verron, T. Current multiblock methods: competition or complementarity? A comparative study in a unified framework. In Chemometrics and Intelligent Laboratory Systems, 182: 131-148, 2018. doi  www 

Conference Articles

  1. Niang, N.; Bougeard, S. and Saporta, G. Clusterwise multiblock PLS. In SFC 2018, Paris, France, 2018. www 
  1. Bougeard, S.; Niang Keita, N.; Verron, T. and Bry, X. Current multiblock methods: competition or complementarity? A comparative study in a unified framework. In Agrostat 2018, Marseille, France, 2018. www 

Miscellaneous

  1. Niang, N. Multiblock consensus clustering. , Poster. www 

2017

Conference Articles

  1. Bougeard, S.; Niang-Keita, N.; Preda, C. and Saporta, G. Clusterwise Sparse PLS. In PLS'17, Macao, Macau SAR China, 2017. www 
  1. Hocine, M.; Feropontova, N.; Niang, N.; Ait Bouziad, K. and Saporta, G. Importance of factors contributing to work-related stress: comparison of four metrics. In ASMDA 2017, London, United Kingdom, 2017. www 

2016

Journal Articles

  1. Kaly, F. c.; Niang, N.; Ouattara, M.; Awa, N.; Thiria, S.; Marticorena, B. and Janicot, S. Two step soft subspace SOM : une méthode de classification multi-bloc avec sélection de variables. In Revue des Nouvelles Technologies de l'Information: 51-66, 2016. www 
  1. Niang Keita, N.; Saporta, G.; Crucianu, M. and Rigaux, P. Le certificat `` Analyste de données massives '' du Conservatoire national des arts et métiers. In Statistique et Enseignement, 2016. www 

Conference Articles

  1. Saporta, G.; Bernard, A.; Bougeard, S.; Niang, N. and Preda, C. Some Sparse Methods for High Dimensional Data. In H2DM International Workshop on High Dimensional Data Mining, Naples, Italy, 2016. www 
  1. Bougeard, S.; Niang, N. and Saporta, G. Regularized clusterwise multiblock regression. In Compstat 2016, Oviedo, Spain, 2016. www 
  1. Niang, N.; Bougeard, S. and Saporta, G. Prédiction en régression clusterwise PLS. In 48 èmes Journées de Statistique, Montpellier, France, 2016. www 
  1. Khalil, Y.; Brajard, J.; Crépon, M.; Machu, '. and Niang, N. Determination of phytoplankton groups from space: application to senegalo-mauritanean upwelling. In EGU General Assembly, pages 15098, Vienne, Austria, 2016. www 

2015

Conference Articles

  1. Niang-Keita, N.; Bougeard, S.; Saporta, G. and Abdi, H. Clusterwise multiblock PLS. In CARME 2015: Correspondence Analysis and Related Methods, Napoli, Italy, 2015. www 
  1. Saporta, G.; Bougeard, S. and Niang-Keita, N. Les méthodes `` clusterwise '' : principes et applications. In XXII èmes rencontres de la Société Francophone de Classification, Nantes, France, 2015. www 
  1. Niang-Keita, N.; Bougeard, S. and Saporta, G. Clusterwise multiblock PLS regression. In CFE-CMStats, London, United Kingdom, 2015. www 

2014

Conference Articles

  1. Niang Keita, N. and Saporta, G. Régression typologique pour données multi-blocs. In 46 émes journées de statistique, Rennes, France, 2014. www 
  1. Kaly, F. c.; Niang Keita, N.; Ouattara, M.; Awa, N. and Thiria, S. H2S-SOM : Une méthode de soft-subspace clustering basée sur SOM pour la sélection de variables en classification. In African Conference on Research in Computer Science and Applied Mathematics (CARI), pages 13, Saint Louis, Senegal, 2014. www 
  1. Niang Keita, N. and Ouattara, M. Imputation multiple avec SOM. In Soci?t? Francophone de Classification, pages 6, Rabat, Morocco, 2014. www 
  1. Ouattara, M.; Niang Keita, N.; Gasri, R.; Badran, F. and Mandin, C. Une approche basée sur STATIS pour la fusion decartes topologiques auto-organisées. In 14?mes Journ?es Francophones ''Extraction et Gestion des Connaissances'' EGC 2014, pages xxx, Rennes, France, 2014. www 

2013

Journal Articles

  1. Niang Keita, N.; Fogliatto, F. and Saporta, G. Non parametric on-line control of batch processes based on STATIS and clustering. In Journal de la Societe Franc caise de Statistique, 154 (3): 124-142, 2013. www 

Conference Articles

  1. Ouattara, M.; Niang Keita, N.; Badran, F. and Mandin, C. Soft Subpace clustering pour données multiblocsbasée sur les cartes topologiques auto-organiséesSOM : 2S-SOM. In SFDS 2013, pages xx, Toulouse, France, 2013. www 
  1. Niang Keita, N. and Ouattara, M. STATIS BASED MULTIBLOCK CLUSTERING. In International Federation of Classification Societies Conference IFCS 2013, pages xx, Tilburg, Netherlands, 2013. www 

Miscellaneous

  1. Niang Keita, N. CLUSTERING INDIVIDUALS DESCRIBED BY MULTI BLOCK VARIABLES. , Poster. www 
  1. Ouattara, M. and Niang Keita, N. Classification multi blocs basée sur les cartes topologiques. , Poster. www 

2012

Conference Articles

  1. Niang Keita, N.; Saporta, G. and Fogliatto, F. Contr^ole non paramétrique de procédés par lots basé sur STATIS et la classification. In 12èmes Journées Européennes AGRO-INDUSTRIE ET METHODES STATISTIQUES (AGROSTAT 2012), pages 163-169, Paris, France, 2012. www 
  1. Ouattara, M. and Niang Keita, N. Classification multi blocs pondérée basée sur les cartes topologiques auto-organisées (ConSOM). In XIX conf?rence de la Soci?t? Fran?aise de classification SFC : 2012, pages x, Marseille, France, 2012. www 
  1. Ouattara, M.; Niang, N.; Thiria, S.; Mandin, C. and Badran, F. Weighted Hierarchical Mixed Topological Map: une méthode de classification hiérarchique `a deux niveaux. In Extraction et Fouille des données Complexe, pages 10, bordeaux, France, 2012. www 

Miscellaneous

  1. Niang Keita, N.; Ouattara, M.; Badran, F.; Thiria, S. and Mandin, C. Weighted Hierarchical Mixed Topological Map: une méthode de classification hiérarchique `a deux niveaux. , Poster. www 

2011

Conference Articles

  1. Niang Keita, N. and Ouattara, M. Hierarchical-MTM (HMTM): Classification d'individus décrits par des variables mixtes structurées en blocs. In JDS'2011, 43e Journ?es de Statistique, pages xx, tunis, Tunisia, 2011. www 

2009

Book Sections

  1. Saporta, G. and Niang Keita, N. Principal Component Analysis: application to Statistical Process Control. In Data Analysis, pages 1-23, ISTE, 2009. doi  www 

Conference Articles

  1. Niang, N.; Fogliatto, F. and Saporta, G. Contr^ole multivarié de procédés par lots `a l'aide de Statis. In 41èmes Journées de Statistique, SFdS, Bordeaux, Bordeaux, France, France, 2009. www 
  1. Niang Keita, N. and Fogliatto, F. Multivariate statistical control of batch processes with variable duration. In IEEE International Conference on Industrial Engineering and Engineering Management (IEEM09), pages 434-438, X, France, 2009. www 
  1. Niang Keita, N.; Fogliatto, F. and Saporta, G. Batch Process Monitoring by Three-way Data Analysis Approach. In ASMDA'09 XIII International Conference on Applied Stochastic Models and Data Analysis, pages 294-298, Vilnius, Lithuania, 2009. www 

2008

Conference Articles

  1. Niang Keita, N.; Fogliatto, F. and Gonzalez, P-L. Multivariate statistical control of batch processes with varying duration. In Congr?s SFDS-SSC, Ottawa, Canada May 2008, X, France, 2008. www 
  1. Niang Keita, N. and Fogliatto, F. Three-way Strategies for Monitoring Batch Processes. In COMPSTAT'08, Porto, Portugal, 2008, X, France, 2008. www 

2007

Journal Articles

  1. Plasse, M.; Niang Keita, N.; Saporta, G.; Villeminot, A. and Leblond, L. Combined use of association rules mining and clustering methods to find relevant links between binary rare attributes in a large data set. In Computational Statistics and Data Analysis, 52 (1): 596-613, 2007. doi  www 

Conference Articles

  1. Niang Keita, N. and Saporta, G. Resampling ROC curves. In Proceedings IASC 07, pages xx, Aveiro, Portugal, 2007. www 
  1. Fogliatto, F. and Niang Keita, N. Controle multivariado de processos em batelada com durac c~ao vari'avel. In ENEGEP'07, Foz do Iguassu. Anais do XXVII ENEGEP. Rio de Janeiro, RS : ABEPRO, pages 1-8, X, France, 2007. www 

2006

Book Sections

  1. Saporta, G. and Niang Keita, N. Correspondence analysis and classification. In Multiple Correspondence Analysis and Related Methods, pages 371-392, Chapman and Hall/CRC, 2006. www 

Conference Articles

  1. Plasse, M.; Niang Keita, N.; Saporta, G.; Villeminot, A. and Leblond, L. Méthodes de classification pour léxtraction de règles. In SFC'06. Rencontres de la Société Francophone de Classification, pages 4, Metz, France, 2006. www 
  1. Plasse, M.; Niang Keita, N.; Saporta, G. and Leblond, L. Une comparaison de certains indices de pertinence des règles d'association. In Actes des sixièmes journées Extraction et Gestion des Connaissances,, pages 561-568, Lille, France, Actes des sixièmes journées Extraction et Gestion des Connaissances, RNTI 06, 2006. www 
  1. Saporta, G. and Niang, N. Model assessment. In KNEMO'06 Knowledge Extraction and Modeling, Capri, Italy, 2006. www 
  1. Plasse, M.; Niang Keita, N. and Saporta, G. Classification préalable `a la recherche de règles d'association. In RIAS'06 Rencontres Inter-Associations sur le thème de la classification, pages 1, Lyon, France, 2006. www 

2005

Conference Articles

  1. Plasse, M.; Niang Keita, N. and Saporta, G. Utilisation conjointe des règles d'association et de la classification de variables. In 37 èmes Journées de Statistique, Pau, France, 2005. www 
  1. Plasse, M.; Niang Keita, N.; Saporta, G. and Gauthier, D. Combined use of association rules mining and clustering methods. In 3rd world Conf. on Computational Statistics Data Analysis, Limassol, Cyprus, 2005. www 

2003

Book Sections

  1. Saporta, G. and Niang, N. Analyse en composantes principales. In Analyse des données, pages 19-42, Hermes, 2003. www 

2002

Book Sections

  1. Niang Keita, N. Multidimensional methods for statistical process control. In Multidimensional methods for statistical process control, 2002. www 

2001

Conference Articles

  1. Yacoub, M.; Niang Keita, N.; Badran, F. and Thiria, S. A New Hierarchical Clustering Method using Topological Map. In 10th International Symposium on Applied Stochastique Models and Data Analysis (AMSDA2001), Compiègne, France, 2001. www 

1995

Journal Articles

  1. Niang, N. and Saporta, G. Période opérationnelle moyenne de la carte de moyennes mobiles équipondérées pour le contr^ole du centrage d'un procédé. In Revue de Statistique Appliquée, 43 (3): 5-20, 1995. www 
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