| AntTree: A new model for clustering with artificial ants H Azzag, N Monmarche, M Slimane, G Venturini The 2003 Congress on Evolutionary Computation, 2003. CEC'03. 4, 2642-2647, 2003 | 128 | 2003 |
| A hierarchical ant based clustering algorithm and its use in three real-world applications H Azzag, G Venturini, A Oliver, C Guinot European Journal of Operational Research 179 (3), 906-922, 2007 | 102 | 2007 |
| State-of-the-art on clustering data streams M Ghesmoune, M Lebbah, H Azzag Big Data Analytics 1, 1-27, 2016 | 96 | 2016 |
| A new growing neural gas for clustering data streams M Ghesmoune, M Lebbah, H Azzag Neural Networks 78, 36-50, 2016 | 53 | 2016 |
| SOM clustering using spark-mapreduce T Sarazin, H Azzag, M Lebbah 2014 IEEE International Parallel & Distributed Processing Symposium …, 2014 | 40 | 2014 |
| Vrminer: A tool for multimedia database mining with virtual reality H Azzag, F Picarougne, C Guinot, G Venturini Processing and Managing Complex Data for Decision Support, 318-339, 2006 | 38 | 2006 |
| A new approach of data clustering using a flock of agents F Picarougne, H Azzag, G Venturini, C Guinot Evolutionary Computation 15 (3), 345-367, 2007 | 37 | 2007 |
| 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 | 29 | 2019 |
| Data and text mining with hierarchical clustering ants H Azzag, C Guinot, G Venturini Swarm intelligence in data mining, 153-189, 2006 | 29 | 2006 |
| 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 | 27 | 2016 |
| 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 | 26 | 2015 |
| How to use ants for hierarchical clustering H Azzag, C Guinot, G Venturini International Workshop on Ant Colony Optimization and Swarm Intelligence …, 2004 | 25 | 2004 |
| 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 | 24 | 2022 |
| Un survol des algorithmes biomimétiques pour la classification H Azzag, F Picarougne, C Guinot, G Venturini Classification et fouille de données, 2004 | 21 | 2004 |
| G-stream: Growing neural gas over data stream M Ghesmoune, H Azzag, M Lebbah Neural Information Processing: 21st International Conference, ICONIP 2014 …, 2014 | 20 | 2014 |
| Deep embedded SOM: joint representation learning and self-organization F Forest, M Lebbah, H Azzag, J Lacaille reconstruction 500, 500, 2000 | 20 | 2000 |
| Deep architectures for joint clustering and visualization with self-organizing maps F Forest, M Lebbah, H Azzag, J Lacaille Trends and Applications in Knowledge Discovery and Data Mining: PAKDD 2019 …, 2019 | 17 | 2019 |
| Clustering over data streams based on growing neural gas M Ghesmoune, M Lebbah, H Azzag Advances in Knowledge Discovery and Data Mining: 19th Pacific-Asia …, 2015 | 17 | 2015 |
| 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 | 16 | 2021 |
| Biclustering using spark-mapreduce T Sarazin, M Lebbah, H Azzag 2014 IEEE International Conference on Big Data (Big Data), 58-60, 2014 | 13 | 2014 |
