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2020 – today
- 2023
[c15]Miguel Palencia-Olivar, Stéphane Bonnevay, Alexandre Aussem, Bruno Canitia:
Topic modeling neuronal non-paramétrique pour l'extraction d'insight client : une application à l'industrie du pneumatique. EGC 2023: 499-506- [c14]Vivien Kraus, Khalid Benabdeslem, Seif-Eddine Benkabou, Dou El Kefel Mansouri, Bruno Canitia:
RSMS: Robust Semi-supervised Multi-label Feature Selection for Regression. ICTAI 2023: 99-105 - 2022
- [j2]Seif-Eddine Benkabou, Khalid Benabdeslem
, Vivien Kraus, Kilian Bourhis, Bruno Canitia:
Local Anomaly Detection for Multivariate Time Series by Temporal Dependency Based on Poisson Model. IEEE Trans. Neural Networks Learn. Syst. 33(11): 6701-6711 (2022) - [c13]Miguel Palencia-Olivar, Stéphane Bonnevay, Alexandre Aussem, Bruno Canitia:
Processus de Dirichlet profonds pour le topic modeling. EGC 2022: 355-362 - [c12]Miguel Palencia-Olivar, Stéphane Bonnevay, Alexandre Aussem, Bruno Canitia:
Nonparametric neural topic modeling for customer insight extraction about the tire industry. IJCNN 2022: 1-9 - [i1]Thomas Ranvier, Kilian Bourhis, Khalid Benabdeslem, Bruno Canitia:
Deep Multi-View Learning for Tire Recommendation. CoRR abs/2203.12451 (2022) - 2021
- [c11]Thomas Ranvier, Khalid Benabdeslem, Kilian Bourhis, Bruno Canitia:
Apprentissage multi-vues pour la recommandation dans le domaine du pneumatique. EGC 2021: 261-268 - [c10]Thomas Ranvier, Khalid Benabdeslem, Kilian Bourhis, Bruno Canitia:
Deep Multi-View Learning for Tire Recommendation. IJCNN 2021: 1-8 - [c9]Miguel Palencia-Olivar, Stéphane Bonnevay, Alexandre Aussem, Bruno Canitia:
Neural Embedded Dirichlet Processes for Topic Modeling. MDAI 2021: 299-310 - 2020
- [c8]Abdenacer Keraghel, Khalid Benabdeslem, Bruno Canitia:
Étude comparative pour l'analyse de requêtes complexes dans le domaine du pneumatique. EGC 2020: 73-84 - [c7]Assaad Kenaan, Khalid Benabdeslem, Kilian Bourhis, Bruno Canitia:
Approches hybrides pour la recommandation dans le domaine du pneumatique. EGC 2020: 133-144 - [c6]Abdenacer Keraghel, Khalid Benabdeslem, Bruno Canitia:
Data augmentation process to improve deep learning-based NER task in the automotive industry field. IJCNN 2020: 1-8 - [c5]Vivien Kraus, Khalid Benabdeslem, Bruno Canitia:
Laplacian-based Semi-supervised Multi-Label Regression. IJCNN 2020: 1-8
2010 – 2019
- 2019
- [c4]Kilian Bourhis, Khalid Benabdeslem, Bruno Canitia:
Entre factorisation de matrices et apprentissage profond pour la recommandation dans le domaine du pneumatique. EGC 2019: 291-296 - 2018
- [j1]Seif-Eddine Benkabou, Khalid Benabdeslem, Bruno Canitia:
Unsupervised outlier detection for time series by entropy and dynamic time warping. Knowl. Inf. Syst. 54(2): 463-486 (2018) - 2017
- [c3]Seif-Eddine Benkabou, Khalid Benabdeslem, Bruno Canitia:
ℓ2-type regularization-based unsupervised anomaly detection from temporal data. IJCNN 2017: 2354-2361 - [c2]Seif-Eddine Benkabou, Khalid Benabdeslem, Bruno Canitia:
Local-to-Global Unsupervised Anomaly Detection from Temporal Data. PAKDD (1) 2017: 762-772
2000 – 2009
- 2008
- [c1]Anouar BenaHassena, Khalid Benabdeslem, Fazia Bellal, Alexandre Aussem, Bruno Canitia:
Intégration de contraintes dans les cartes auto-organisatrices. EGC 2008: 643-648
Coauthor Index
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