| State-of-the-art on clustering data streams M Ghesmoune, M Lebbah, H Azzag Big Data Analytics 1 (1), 13, 2016 | 106 | 2016 |
| An evolutionary computing-based efficient hybrid task scheduling approach for heterogeneous computing environment M Sulaiman, Z Halim, M Lebbah, M Waqas, S Tu Journal of Grid Computing 19 (1), 11, 2021 | 71 | 2021 |
| A new growing neural gas for clustering data streams M Ghesmoune, M Lebbah, H Azzag Neural Networks 78, 36-50, 2016 | 58 | 2016 |
| Biophysical regions identification using an artificial neuronal network: A case study in the South Western Atlantic M Saraceno, C Provost, M Lebbah Advances in Space Research 37 (4), 793-805, 2006 | 44 | 2006 |
| From variable weighting to cluster characterization in topographic unsupervised learning N Grozavu, Y Bennani, M Lebbah | 41 | 2009 |
| SOM clustering using spark-mapreduce T Sarazin, H Azzag, M Lebbah 2014 IEEE International Parallel & Distributed Processing Symposium …, 2014 | 40 | 2014 |
| Transfer learning from synthetic labels for histopathological images classification N Dif, MO Attaoui, Z Elberrichi, M Lebbah, H Azzag Applied Intelligence 52 (1), 358-377, 2022 | 37 | 2022 |
| BeSOM: Bernoulli on self-organizing map M Lebbah, N Rogovschi, Y Bennani 2007 International joint conference on neural networks, 631-636, 2007 | 35 | 2007 |
| Deep embedded self-organizing maps for joint representation learning and topology-preserving clustering F Forest, M Lebbah, H Azzag, J Lacaille Neural Computing and Applications 33 (24), 17439-17469, 2021 | 32 | 2021 |
| A distributed approximate nearest neighbors algorithm for efficient large scale mean shift clustering G Beck, T Duong, M Lebbah, H Azzag, C Cérin Journal of Parallel and Distributed Computing 134, 128-139, 2019 | 32 | 2019 |
| S. Topological Map for Binary Data, ESANN 2000, Bruges M Lebbah, F Badran, F Thiria April 26-27-28, 2000, Proceedings, 2000 | 30* | 2000 |
| Micro-batching growing neural gas for clustering data streams using spark streaming M Ghesmoune, M Lebbah, H Azzag Procedia Computer Science 53, 158-166, 2015 | 29 | 2015 |
| Nearest neighbour estimators of density derivatives, with application to mean shift clustering T Duong, G Beck, H Azzag, M Lebbah Pattern Recognition Letters 80, 224-230, 2016 | 28 | 2016 |
| A scalable and effective rough set theory-based approach for big data pre-processing Z Chelly Dagdia, C Zarges, G Beck, M Lebbah Knowledge and Information Systems 62 (8), 3321-3386, 2020 | 26 | 2020 |
| Feature selection for self-organizing map K Benabdeslem, M Lebbah 2007 29th International Conference on Information Technology Interfaces, 45-50, 2007 | 26 | 2007 |
| A survey and implementation of performance metrics for self-organized maps F Forest, M Lebbah, H Azzag, J Lacaille arXiv preprint arXiv:2011.05847, 2020 | 25 | 2020 |
| Mixed Topological Map. M Lebbah, A Chazottes, F Badran, S Thiria ESANN 17, 47, 2005 | 24 | 2005 |
| Deep architectures for joint clustering and visualization with self-organizing maps F Forest, M Lebbah, H Azzag, J Lacaille Pacific-Asia Conference on Knowledge Discovery and Data Mining, 105-116, 2019 | 22 | 2019 |
| Deep embedded SOM: joint representation learning and self-organization F Forest, M Lebbah, H Azzag, J Lacaille The European Symposium on Artificial Neural Networks, 6, 2019 | 22* | 2019 |
| A distributed rough set theory based algorithm for an efficient big data pre-processing under the spark framework ZC Dagdia, C Zarges, G Beck, M Lebbah 2017 IEEE International Conference on Big Data (Big Data), 911-916, 2017 | 22 | 2017 |
Younès BennaniProfessor, Sorbonne Paris Nord UniversityVerified email at lipn.univ-paris13.fr
