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Hanene Azzag
Hanene Azzag-Khelif – Hanane Azzag
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2020 – today
- 2024
- [j17]Kodjo Mawuena Amekoe
, Hanane Azzag, Zaineb Chelly Dagdia, Mustapha Lebbah, Gregoire Jaffre:
Exploring accuracy and interpretability trade-off in tabular learning with novel attention-based models. Neural Comput. Appl. 36(30): 18583-18611 (2024) - [c87]Quang Anh Nguyen, Nadi Tomeh, Mustapha Lebbah, Thierry Charnois, Hanene Azzag, Santiago Cordoba Muñoz:
Enhancing Few-Shot Topic Classification with Verbalizers. a Study on Automatic Verbalizer and Ensemble Methods. LREC/COLING 2024: 5956-5965 - [c86]Bilal Faye, Hanane Azzag, Mustapha Lebbah, Fangchen Fang:
Normalisation Contextuelle : Une Nouvelle Approche pour la Stabilité et l'Amélioration des Performances des Réseaux de Neurones. EGC 2024: 95-106 - [c85]Abdellah Madane, Florent Forest, Hanane Azzag, Mustapha Lebbah, Jérôme Lacaille:
AESim: A Data-Driven Aircraft Engine Simulator. IJCAI 2024: 8737-8740 - [c84]Bilal Faye, Hanane Azzag, Mustapha Lebbah, Fangchen Fang:
UAN: Unsupervised Adaptive Normalization. IJCNN 2024: 1-8 - [c83]Abdellah Madane, Florent Forest, Hanane Azzag, Mustapha Lebbah, Jérôme Lacaille:
One-Pass Generation of Multivariate Time Series through Conditional Multivariate Modeling. IJCNN 2024: 1-9 - [c82]Reda Khoufache, Anisse Belhadj, Hanene Azzag, Mustapha Lebbah:
Distributed MCMC Inference for Bayesian Non-parametric Latent Block Model. PAKDD (1) 2024: 271-283 - [c81]Reda Khoufache, Mustapha Lebbah, Hanene Azzag, Étienne Goffinet, Djamel Bouchaffra:
Distributed Collapsed Gibbs Sampler for Dirichlet Process Mixture Models in Federated Learning. SDM 2024: 815-823 - [e5]Annalisa Appice
Foundations of Intelligent Systems - 27th International Symposium, ISMIS 2024, Poitiers, France, June 17-19, 2024, Proceedings. Lecture Notes in Computer Science 14670, Springer 2024, ISBN 978-3-031-62699-9 [contents] - [i24]Reda Khoufache, Anisse Belhadj, Hanene Azzag, Mustapha Lebbah:
Distributed MCMC inference for Bayesian Non-Parametric Latent Block Model. CoRR abs/2402.01050 (2024) - [i23]Bilal Faye, Hanane Azzag, Mustapha Lebbah, Djamel Bouchaffra:
Context-Based Multimodal Fusion. CoRR abs/2403.04650 (2024) - [i22]Bilal Faye, Hanane Azzag, Mustapha Lebbah:
Cluster-Based Normalization Layer for Neural Networks. CoRR abs/2403.16798 (2024) - [i21]Bilal Faye, Mustapha Lebbah, Hanane Azzag:
Supervised Batch Normalization. CoRR abs/2405.17027 (2024) - [i20]Binta Sow, Bilal Faye, Hanane Azzag, Mustapha Lebbah:
LightMDETR: A Lightweight Approach for Low-Cost Open-Vocabulary Object Detection Training. CoRR abs/2408.10787 (2024) - [i19]Bilal Faye, Hanane Azzag, Mustapha Lebbah, Fangchen Fang:
Unsupervised Adaptive Normalization. CoRR abs/2409.04757 (2024) - [i18]Bilal Faye, Hanane Azzag, Mustapha Lebbah, Djamel Bouchaffra:
Adaptative Context Normalization: A Boost for Deep Learning in Image Processing. CoRR abs/2409.04759 (2024) - [i17]Kodjo Mawuena Amekoe, Mustapha Lebbah, Gregoire Jaffre, Hanene Azzag, Zaineb Chelly Dagdia:
Evaluating the Efficacy of Instance Incremental vs. Batch Learning in Delayed Label Environments: An Empirical Study on Tabular Data Streaming for Fraud Detection. CoRR abs/2409.10111 (2024) - [i16]Bilal Faye, Hanane Azzag, Mustapha Lebbah:
OneEncoder: A Lightweight Framework for Progressive Alignment of Modalities. CoRR abs/2409.11059 (2024) - [i15]Quang Anh Nguyen, Nadi Tomeh, Mustapha Lebbah, Thierry Charnois, Hanene Azzag, Santiago Cordoba Muñoz:
Manual Verbalizer Enrichment for Few-Shot Text Classification. CoRR abs/2410.06173 (2024) - [i14]Djamel Bouchaffra, Fayçal Ykhlef, Bilal Faye, Hanane Azzag, Mustapha Lebbah:
Game Theory Meets Statistical Mechanics in Deep Learning Design. CoRR abs/2410.12264 (2024) - 2023
- [j16]Mohammed Oualid Attaoui
Regions of interest selection in histopathological images using subspace and multi-objective stream clustering. Vis. Comput. 39(4): 1683-1701 (2023) - [c80]Kodjo Mawuena Amekoe, Mohamed Djallel Dilmi, Hanene Azzag, Zaineb Chelly Dagdia, Mustapha Lebbah
TabSRA: An Attention based Self-Explainable Model for Tabular Learning. ESANN 2023 - [c79]Reda Khoufache, Mohamed Djallel Dilmi, Hanene Azzag, Étienne Goffinet, Mustapha Lebbah:
Propriétés émergentes du multi-clustering bayésien non paramétrique: Application aux données d'images multivues. EGC 2023: 639-640 - [c78]Mohammed Walid Attaoui
Improved Multi-Objective Data Stream Clustering with Time and Memory Optimization. GECCO Companion 2023: 267-270 - [c77]Bilal Faye, Hanane Azzag, Mustapha Lebbah
Context Normalization Layer with Applications. ICDM (Workshops) 2023: 615-624 - [c76]Alex Mourer, Florent Forest, Mustapha Lebbah
Selecting the Number of Clusters K with a Stability Trade-off: An Internal Validation Criterion. PAKDD (1) 2023: 210-222 - [i13]Bilal Faye, Mohamed Djallel Dilmi, Hanane Azzag, Mustapha Lebbah, Fangchen Feng:
Context Normalization for Robust Image Classification. CoRR abs/2303.07651 (2023) - [i12]Mohamed Djallel Dilmi, Hanene Azzag, Mustapha Lebbah:
Epigenetics Algorithms: Self-Reinforcement-Attention mechanism to regulate chromosomes expression. CoRR abs/2303.10154 (2023) - [i11]Kodjo Mawuena Amekoe, Mohamed Djallel Dilmi, Hanene Azzag, Mustapha Lebbah, Zaineb Chelly Dagdia, Gregoire Jaffre:
Self-Reinforcement Attention Mechanism For Tabular Learning. CoRR abs/2305.11684 (2023) - [i10]Reda Khoufache, Mustapha Lebbah, Hanene Azzag, Étienne Goffinet, Djamel Bouchaffra:
Distributed Collapsed Gibbs Sampler for Dirichlet Process Mixture Models in Federated Learning. CoRR abs/2312.11169 (2023) - 2022
- [j15]Nassima Dif
Transfer learning from synthetic labels for histopathological images classification. Appl. Intell. 52(1): 358-377 (2022) - [j14]Étienne Goffinet
Functional non-parametric latent block model: A multivariate time series clustering approach for autonomous driving validation. Comput. Stat. Data Anal. 176: 107565 (2022) - [c75]Reda Khoufache, Mohamed Djallel Dilmi, Hanene Azzag, Etienne Gofinnet, Mustapha Lebbah
Emerging properties from Bayesian Non-Parametric for multiple clustering: Application for multi-view image dataset. ICDM (Workshops) 2022: 31-38 - [i9]Mohammed Oualid Attaoui, Hanene Azzag, Mustapha Lebbah
Improved Multi-objective Data Stream Clustering with Time and Memory Optimization. CoRR abs/2201.05079 (2022) - [i8]Abdellah Madane, Mohamed Djallel Dilmi, Florent Forest, Hanane Azzag, Mustapha Lebbah, Jérôme Lacaille:
Transformer-based conditional generative adversarial network for multivariate time series generation. CoRR abs/2210.02089 (2022) - 2021
- [j13]Mohammed Oualid Attaoui
Subspace data stream clustering with global and local weighting models. Neural Comput. Appl. 33(8): 3691-3712 (2021) - [j12]Florent Forest
Deep embedded self-organizing maps for joint representation learning and topology-preserving clustering. Neural Comput. Appl. 33(24): 17439-17469 (2021) - [c74]Étienne Goffinet, Mustapha Lebbah, Hanane Azzag, Loïc Giraldi, Anthony Coutant:
Non-parametric Multivariate Time Series Co-clustering Model Applied to Driving-Assistance Systems Validation. AALTD@ECML/PKDD 2021: 71-87 - [c73]Mohammed Oualid Attaoui, Hanene Azzag, Nabil Keskes, Mustapha Lebbah
A New Subspace Multi-Objective Approach for the Clustering and Selection of Regions of Interests in Histopathological Images. CEC 2021: 556-563 - [c72]Étienne Goffinet, Mustapha Lebbah, Hanane Azzag, Loïc Giraldi, Anthony Coutant:
Multivariate Time Series Multi-Coclustering. Application to Advanced Driving Assistance System Validation. ESANN 2021 - [c71]Gaël Beck, Mustapha Lebbah
A New Nearest Neighbor Median Shift Clustering for Binary Data. ICANN (5) 2021: 101-112 - [c70]Pierre Le Jeune, Mustapha Lebbah, Anissa Mokraoui, Hanene Azzag:
Experience feedback using Representation Learning for Few-Shot Object Detection on Aerial Images. ICMLA 2021: 662-667 - [i7]Pierre Le Jeune, Mustapha Lebbah, Anissa Mokraoui, Hanene Azzag:
Experience feedback using Representation Learning for Few-Shot Object Detection on Aerial Images. CoRR abs/2109.13027 (2021) - 2020
- [c69]Étienne Goffinet, Mustapha Lebbah, Hanane Azzag, Loïc Giraldi:
Clustering de séries temporelles par construction de dictionnaire. EGC 2020: 181-192 - [c68]Mohammed Oualid Attaoui, Mustapha Lebbah, Nabil Keskes, Hanene Azzag, Mohammed Ghesmoune:
Soft Subspace Growing Neural Gas pour le Clustering de Flux de Données. EGC 2020: 441-448 - [c67]Mohammed Oualid Attaoui, Hanene Azzag, Mustapha Lebbah
Multi-objective data stream clustering. GECCO Companion 2020: 113-114 - [c66]Florent Forest, Alex Mourer, Mustapha Lebbah, Hanane Azzag, Jérôme Lacaille:
An Invariance-guided Stability Criterion for Time Series Clustering Validation. ICPR 2020: 9296-9303 - [c65]Étienne Goffinet, Mustapha Lebbah, Hanane Azzag, Loïc Giraldi:
Autonomous Driving Validation with Model-Based Dictionary Clustering. ECML/PKDD (4) 2020: 323-338 - [i6]Alex Mourer, Florent Forest, Mustapha Lebbah
Selecting the Number of Clusters K with a Stability Trade-off: an Internal Validation Criterion. CoRR abs/2006.08530 (2020) - [i5]Étienne Goffinet, Anthony Coutant, Mustapha Lebbah, Hanane Azzag, Loïc Giraldi:
Conditional Latent Block Model: a Multivariate Time Series Clustering Approach for Autonomous Driving Validation. CoRR abs/2008.00946 (2020) - [i4]Florent Forest, Mustapha Lebbah, Hanane Azzag, Jérôme Lacaille:
A Survey and Implementation of Performance Metrics for Self-Organized Maps. CoRR abs/2011.05847 (2020)
2010 – 2019
- 2019
- [j11]Nesrine Masmoudi, Hanene Azzag, Mustapha Lebbah, Cyrille Bertelle
An ant-based new clustering model for graph proximity construction. Int. J. Bio Inspired Comput. 14(4): 213-226 (2019) - [j10]Gaël Beck
A distributed approximate nearest neighbors algorithm for efficient large scale mean shift clustering. J. Parallel Distributed Comput. 134: 128-139 (2019) - [c64]Florent Forest, Mustapha Lebbah, Hanene Azzag, Jérôme Lacaille:
Deep Embedded SOM: joint representation learning and self-organization. ESANN 2019 - [c63]Mohammed Oualid Attaoui
Soft Subspace Growing Neural Gas for Data Stream Clustering. ICANN (4) 2019: 569-580 - [c62]Florent Forest
Deep Architectures for Joint Clustering and Visualization with Self-organizing Maps. PAKDD (Workshops) 2019: 105-116 - [c61]Andriantsiory Dina Faneva
Algorithms for an Efficient Tensor Biclustering. PAKDD (Workshops) 2019: 130-138 - [c60]Mohammed Oualid Attaoui, Mustapha Lebbah
Soft Subspace Topological Clustering over Evolving Data Stream. WSOM+ 2019: 225-230 - [e4]Ebad Banissi, Anna Ursyn, Mark W. McK. Bannatyne, Nuno Datia, Rita Francese, Muhammad Sarfraz, Theodor G. Wyeld, Fatma Bouali, Gilles Venturini, Hanane Azzag, Mustapha Lebbah, Marjan Trutschl, Urska Cvek, Heimo Müller, Minoru Nakayama, Sebastian Kernbach, Loredana Caruccio, Michele Risi, Ugo Erra, Autilia Vitiello, Veronica Rossano:
23rd International Conference on Information Visualisation, IV 2019, Paris, France, July 2-5, 2019, Part I. IEEE 2019, ISBN 978-1-7281-2838-2 [contents] - [i3]Gaël Beck, Tarn Duong, Mustapha Lebbah, Hanane Azzag, Christophe Cérin:
A Distributed and Approximated Nearest Neighbors Algorithm for an Efficient Large Scale Mean Shift Clustering. CoRR abs/1902.03833 (2019) - [i2]Gaël Beck, Tarn Duong, Mustapha Lebbah, Hanane Azzag:
Nearest Neighbor Median Shift Clustering for Binary Data. CoRR abs/1902.04181 (2019) - [i1]Andriantsiory Dina Faneva, Mustapha Lebbah, Hanane Azzag, Gaël Beck:
Algorithms for an Efficient Tensor Biclustering. CoRR abs/1903.04042 (2019) - 2018
- [j9]Hippolyte Léger, Dominique Bouthinon, Mustapha Lebbah
An Instance Based Model for Scalable θ-Subsumption. Int. J. Artif. Intell. Tools 27(7): 1860011:1-1860011:13 (2018) - [c59]Florent Forest
A Generic and Scalable Pipeline for Large-Scale Analytics of Continuous Aircraft Engine Data. IEEE BigData 2018: 1918-1924 - [c58]Mohammed Ghesmoune, Mustapha Lebbah, Hanane Azzag, Salima Benbernou, Mourad Ouziri, Tarn Duong
A Complete Data Science Work-flow For Insurance Field. IEEE BigData 2018: 1925-1930 - [c57]Zaineb Chelly Dagdia
A Distributed Rough Set Theory Algorithm based on Locality Sensitive Hashing for an Efficient Big Data Pre-processing. IEEE BigData 2018: 2597-2606 - [c56]Gaël Beck, Hanane Azzag, Mustapha Lebbah, Tarn Duong:
Mean-shift : Clustering scalable et distribué. EGC 2018: 415-425 - [c55]Nhat-Quang Doan, Hanane Azzag, Mustapha Lebbah:
Hierarchical Laplacian Score for unsupervised feature selection. IJCNN 2018: 1-7 - [c54]Gaël Beck, Hanane Azzag, Stéphanie Bougeard
A New Micro-Batch Approach for Partial Least Square Clusterwise Regression. INNS Conference on Big Data 2018: 239-250 - [e3]Mustapha Lebbah, Christine Largeron, Hanane Azzag:
Extraction et Gestion des Connaissances, EGC 2018, Paris, France, January 23-26, 2018. RNTI E-34, Éditions RNTI 2018, ISBN 979-10-96289-07-3 [contents] - 2017
- [j8]Mohammed Ghesmoune, Hanene Azzag, Salima Benbernou, Mustapha Lebbah, Tarn Duong
Big Data: from collection to visualization. Mach. Learn. 106(6): 837-862 (2017) - [c53]Hippolyte Léger, Dominique Bouthinon, Mustapha Lebbah, Hanane Azzag:
Nouveau modèle pour un passage à l'échelle de la 0-subsomption. EGC 2017: 339-344 - [c52]Hippolyte Léger, Dominique Bouthinon, Mustapha Lebbah, Hanene Azzag:
An Instance Based Model for Scalable Theta -Subsumption. ICTAI 2017: 846-852 - 2016
- [j7]Mohammed Ghesmoune, Mustapha Lebbah
A new Growing Neural Gas for clustering data streams. Neural Networks 78: 36-50 (2016) - [j6]Tarn Duong
Nearest neighbour estimators of density derivatives, with application to mean shift clustering. Pattern Recognit. Lett. 80: 224-230 (2016) - [c51]Gaël Beck, Tarn Duong
Distributed mean shift clustering with approximate nearest neighbours. IJCNN 2016: 3110-3115 - [c50]Hippolyte Léger, Dominique Bouthinon, Mustapha Lebbah, Hanene Azzag-Khelif:
A new Model for Scalable θ-subsumption. ILP (Short Papers) 2016: 41-47 - [c49]Nesrine Masmoudi, Hanane Azzag, Mustapha Lebbah
CL-AntInc Algorithm for Clustering Binary Data Streams Using the Ants Behavior. KES 2016: 187-196 - 2015
- [c48]Nesrine Masmoudi, Hanane Azzag, Mustapha Lebbah, Cyrille Bertelle
How to use ants for data stream clustering. CEC 2015: 656-663 - [c47]Mohammed Ghesmoune, Mustapha Lebbah, Hanane Azzag:
Clustering topologique pour le flux de données. EGC 2015: 137-142 - [c46]Tugdual Sarazin, Hanane Azzag, Mustapha Lebbah:
Modèle de Biclustering dans un paradigme "Mapreduce". EGC 2015: 467-468 - [c45]Nesrine Masmoudi, Hanane Azzag, Mustapha Lebbah, Cyrille Bertelle
Clustering of Binary Data Sets Using Artificial Ants Algorithm. ICONIP (1) 2015: 716-723 - [c44]Nhat-Quang Doan, Mohammed Ghesmoune, Hanane Azzag, Mustapha Lebbah:
Growing Hierarchical Trees for Data Stream clustering and visualization. IJCNN 2015: 1-8 - [c43]Mohammed Ghesmoune, Mustapha Lebbah, Hanene Azzag:
Micro-Batching Growing Neural Gas for Clustering Data Streams Using Spark Streaming. INNS Conference on Big Data 2015: 158-166 - [c42]Mohammed Ghesmoune, Mustapha Lebbah, Hanene Azzag:
Clustering Over Data Streams Based on Growing Neural Gas. PAKDD (2) 2015: 134-145 - 2014
- [c41]Tugdual Sarazin, Mustapha Lebbah, Hanane Azzag:
Biclustering using Spark-MapReduce. IEEE BigData 2014: 58-60 - [c40]Amine Chaibi, Hanane Azzag, Mustapha Lebbah:
Pondération de blocs de variables en bi-partitionnement topologique. EGC 2014: 317-328 - [c39]Mohammed Ghesmoune, Hanene Azzag, Mustapha Lebbah:
G-Stream: Growing Neural Gas over Data Stream. ICONIP (1) 2014: 207-214 - [c38]Tugdual Sarazin, Mustapha Lebbah, Hanane Azzag, Amine Chaibi:
Feature Group Weighting and Topological Biclustering. ICONIP (2) 2014: 369-376 - [c37]Tugdual Sarazin, Hanane Azzag, Mustapha Lebbah:
SOM Clustering Using Spark-MapReduce. IPDPS Workshops 2014: 1727-1734 - [c36]Nesrine Masmoudi, Hanane Azzag, Mustapha Lebbah, Cyrille Bertelle
Incremental clustering of data stream using real ants behavior. NaBIC 2014: 262-268 - [p3]Amine Chaibi, Mustapha Lebbah, Hanane Azzag:
Détection de nouveautés en utilisant un nouveau score de détection de "groupes-outliers". Fouille de données complexes 2014: 89-108 - 2013
- [j5]Amine Chaibi, Mustapha Lebbah, Hanane Azzag:
Group Outlier factor: a New Score using Self-Organising Map for Group-Outlier and Novelty Detection. Int. J. Comput. Intell. Appl. 12(2) (2013) - [c35]Amine Chaibi, Mustapha Lebbah, Hanane Azzag:
Nouvelle approche de bi-partitionnement topologique. EGC 2013: 37-48 - [c34]Nhat-Quang Doan, Hanane Azzag, Mustapha Lebbah:
Sélection de variables non supervisée sous contraintes hiérarchiques. EGC 2013: 67-78 - [c33]Amine Chaibi, Mustapha Lebbah, Hanane Azzag:
A new bi-clustering approach using topological maps. IJCNN 2013: 1-7 - [c32]Nhat-Quang Doan, Hanane Azzag, Mustapha Lebbah, Guillaume Santini:
Self-organizing trees for visualizing protein dataset. IJCNN 2013: 1-8 - [c31]Amine Chaibi, Mustapha Lebbah, Hanane Azzag:
A New Visualization of Group-Outliers in Unsupervised Learning. IV 2013: 162-167 - [c30]Nesrine Masmoudi, Hanane Azzag, Mustapha Lebbah, Cyrille Bertelle
Clustering using chemical and colonial odors of real ants. NaBIC 2013: 207-213 - [e2]Ebad Banissi, Hanane Azzag, Mark W. McK. Bannatyne, Stefan Bertschi, Fatma Bouali, Remo Burkhard, John Counsell, Alfredo Cuzzocrea, Martin J. Eppler, Barbara Hammer, Mustapha Lebbah, Francis T. Marchese, Muhammad Sarfraz, Anna Ursyn, Gilles Venturini, Theodor G. Wyeld:
17th International Conference on Information Visualisation, IV 2013, London, United Kingdom, July 16-18, 2013. IEEE Computer Society 2013, ISBN 978-0-7695-5049-7 [contents] - 2012
- [j4]Hanane Azzag, Christiane Guinot, Gilles Venturini:
An artificial ants model for fast construction and approximation of proximity graphs. Adapt. Behav. 20(6): 443-459 (2012) - [c29]Amine Chaibi, Hanane Azzag, Mustapha Lebbah:
Automatic Group-Outlier Detection. ESANN 2012 - [c28]Amine Chaibi, Mustapha Lebbah, Hanane Azzag:
Détection de groupes outliers en classification non supervisée. EGC 2012: 119-124 - [c27]Nhat-Quang Doan, Hanane Azzag, Mustapha Lebbah:
Clustering multi-niveaux de graphes : hiérarchique et topologique. EGC 2012: 567-568 - [c26]Nhat-Quang Doan, Hanane Azzag, Mustapha Lebbah:
Self-Organizing Map and Tree Topology for Graph Summarization. ICANN (2) 2012: 363-370 - [c25]Amine Chaibi, Mustapha Lebbah, Hanane Azzag:
Novelty Detection Using a New Group Outlier Factor. ICONIP (3) 2012: 364-372 - [c24]Nhat-Quang Doan, Hanane Azzag, Mustapha Lebbah:
Growing Self-organizing Trees for knowledge discovery from data. IJCNN 2012: 1-8 - [c23]Nhat-Quang Doan, Hanane Azzag, Mustapha Lebbah:
Graph Decomposition Using Self-organizing Trees. IV 2012: 246-251 - [e1]Ebad Banissi, Stefan Bertschi, Camilla Forsell, Jimmy Johansson, Sarah Kenderdine, Francis T. Marchese, Muhammad Sarfraz, Liz J. Stuart, Anna Ursyn, Theodor G. Wyeld, Hanane Azzag, Mustapha Lebbah, Gilles Venturini:
16th International Conference on Information Visualisation, IV 2012, Montpellier, France, July 11-13, 2012. IEEE Computer Society 2012, ISBN 978-1-4673-2260-7 [contents] - 2011
- [j3]Hanene Azzag, Mustapha Lebbah:
Self-Organizing Tree Using Artificial Ants. J. Inf. Technol. Res. 4(2): 1-16 (2011) - [c22]Hanane Azzag, Mustapha Lebbah:
Une nouvelle approche visuelle pour la classification hiérarchique et topologique. EGC 2011: 677-688 - [c21]Lydia Boudjeloud, Hanane Azzag:
A cooperative biomimetic approach for high dimensional data mining. GECCO (Companion) 2011: 233-234 - [c20]Hanane Azzag, Mustapha Lebbah:
A New Way for Hierarchical and Topological Clustering. EGC (best of volume) 2011: 85-97 - 2010
- [c19]Hanane Azzag, Mustapha Lebbah:
Auto-organisation topologique et hiérarchique des données. EGC 2010: 555-560 - [c18]Lydia Boudjeloud-Assala, Hanane Azzag:
Approche biomimétique coopérative pour la visualisation de grands graphes multidimensionels. EGC 2010: 667-668 - [c17]Hanene Azzag, Mustapha Lebbah, Aymen Arfaoui:
Map-TreeMaps: A New Approach for Hierarchical and Topological Clustering. ICMLA 2010: 873-878 - [c16]Mustapha Lebbah, Hanane Azzag:
Topological Hierarchical Tree Using Artificial Ants. ICONIP (1) 2010: 652-659
2000 – 2009
- 2009
- [c15]Hanane Azzag, Mustapha Lebbah:
A New Approach for Auto-organizing a Groups of Artificial Ants. ECAL (2) 2009: 440-447 - [p2]Hanene Azzag, Fabien Picarougne, Christiane Guinot, Gilles Venturini:
VRMiner. Database Technologies: Concepts, Methodologies, Tools, and Applications 2009: 1151-1167 - 2008
- [c14]Hanane Azzag, Mustapha Lebbah:
Clustering of Self-Organizing Map. ESANN 2008: 209-214 - [c13]Mustapha Lebbah, Hanane Azzag:
Segmentation hiérarchique des cartes topologiques. EGC 2008: 631-642 - 2007
- [j2]Fabien Picarougne, Hanene Azzag, Gilles Venturini, Christiane Guinot:
A New Approach of Data Clustering Using a Flock of Agents. Evol. Comput. 15(3): 345-367 (2007) - [j1]Hanene Azzag, Gilles Venturini, Antoine Oliver, Christiane Guinot:
A hierarchical ant based clustering algorithm and its use in three real-world applications. Eur. J. Oper. Res. 179(3): 906-922 (2007) - [c12]Julien Lavergne, Hanene Azzag, Christiane Guinot, Gilles Venturini:
Construction incrémentale et visualisation de graphes de voisinage par des fourmis artificielles. EGC 2007: 135-146 - [c11]Julien Lavergne, Hanane Azzag, Christiane Guinot, Gilles Venturini:
Incremental Construction of Neighborhood Graphs Using the Ants Self-Assembly Behavior. ICTAI (1) 2007: 399-406 - [c10]Hanane Azzag, Julien Lavergne, Christiane Guinot, Gilles Venturini:
On building graphs of documents with artificial ants. WWW 2007: 1299-1300 - 2006
- [c9]Hanane Azzag, David Da Costa, Christiane Guinot, Gilles Venturini:
Un aperçu de la fouille visuelle de données. AAFD 2006: 1-14 - [c8]Hanene Azzag, David Ratsimba, David Da Costa, Christiane Guinot, Gilles Venturini:
On Building Maps of Web Pages with a Cellular Automaton. BICC 2006: 33-42 - [c7]Hanene Azzag, David Ratsimba, David Da Costa, Gilles Venturini, Christiane Guinot:
Generating maps of web pages using cellular automata. WWW 2006: 935-936 - [p1]Hanene Azzag, Christiane Guinot, Gilles Venturini:
Data and Text Mining with Hierarchical Clustering Ants. Swarm Intelligence in Data Mining 2006: 153-189 - 2005
- [c6]Hanene Azzag, Gilles Venturini, Christiane Guinot:
Automatic generation of web portals using artificial ants. WWW (Special interest tracks and posters) 2005: 908-909 - 2004
- [c5]Hanene Azzag, Christiane Guinot, Gilles Venturini:
How to Use Ants for Hierarchical Clustering. ANTS Workshop 2004: 350-357 - [c4]Hanene Azzag, Christiane Guinot, Gilles Venturini:
AntTree: A Web Document Clustering Using Artificial Ants. ECAI 2004: 480-484 - [c3]Fabien Picarougne, Hanene Azzag, Gilles Venturini, Christiane Guinot:
On Data Clustering with a Flock of Artificial Agents. ICTAI 2004: 777-778 - 2003
- [c2]Hanene Azzag, Nicolas Monmarché, Mohamed Slimane, Gilles Venturini:
AntTree: a new model for clustering with artificial ants. IEEE Congress on Evolutionary Computation 2003: 2642-2647 - [c1]Hanene Azzag, Nicolas Monmarché, Mohamed Slimane, Christiane Guinot, Gilles Venturini:
A Clustering Algorithm Based on the Ants Self-Assembly Behavior. ECAL 2003: 564-571
Coauthor Index
Mohammed Oualid Attaoui
aka: Mohammed Walid Attaoui
aka: Mohammed Walid Attaoui
[j17] [c87] [c86] [c85] [c84] [c83] [c82] [c81] [i24] [i23] [i22] [i21] [i20] [i19] [i18] [i17] [i16] [i15] [i14] [j16] [c80] [c79] [c78] [c77] [c76] [i13] [i12] [i11] [i10] [j15] [j14] [c75] [i9] [i8] [j13] [j12] [c74] [c73] [c72] [c71] [c70] [i7] [c69] [c68] [c67] [c66] [c65] [i6] [i5] [i4] [j11] [j10] [c64] [c63] [c62] [c61] [c60] [e4] [i3] [i2] [i1] [j9] [c59] [c58] [c57] [c56] [c55] [c54] [e3] [j8] [c53] [c52] [j7] [j6] [c51] [c50] [c49] [c48] [c47] [c46] [c45] [c44] [c43] [c42] [c41] [c40] [c39] [c38] [c37] [c36] [p3] [j5] [c35] [c34] [c33] [c32] [c31] [c30] [e2] [c29] [c28] [c27] [c26] [c25] [c24] [c23] [e1] [j3] [c22] [c20] [c19] [c17] [c16] [c15] [c14] [c13]
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