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2020 – today
- 2023
[c9]Amine Ferdjaoui, Amira Tlati, Séverine Affeldt, Mohamed Nadif:
CORPEX : Analyse exploratoire d'un corpus biomédical à l'aide de la classification croisée. EGC 2023: 597-604- 2022
- [j10]Louis Geiler, Séverine Affeldt, Mohamed Nadif:
An effective strategy for churn prediction and customer profiling. Data Knowl. Eng. 142: 102100 (2022) - [j9]Louis Geiler, Séverine Affeldt
, Mohamed Nadif:
A survey on machine learning methods for churn prediction. Int. J. Data Sci. Anal. 14(3): 217-242 (2022) - [c8]Louis Geiler, Séverine Affeldt, Mohamed Nadif:
Apprentissage machine pour la prédiction de l'attrition: une étude comparative. EGC 2022: 135-146 - 2021
- [j8]Séverine Affeldt, Lazhar Labiod, Mohamed Nadif:
Regularized bi-directional co-clustering. Stat. Comput. 31(3): 32 (2021) - [c7]Séverine Affeldt, Lazhar Labiod, Mohamed Nadif:
Approche ensemble pour le co-clustering par blocs sur des données textuelles: Application au biomédical. EGC 2021: 381-388 - [c6]Séverine Affeldt, Lazhar Labiod, Mohamed Nadif:
Méthode ensemble de clustering profond. EGC 2021: 413-420 - [c5]Séverine Affeldt, Lazhar Labiod, Mohamed Nadif:
Regularized Dual-PPMI Co-clustering for Text Data. SIGIR 2021: 2263-2267 - 2020
- [j7]Séverine Affeldt, Lazhar Labiod, Mohamed Nadif:
Spectral clustering via ensemble deep autoencoder learning (SC-EDAE). Pattern Recognit. 108: 107522 (2020) - [c4]Séverine Affeldt, Lazhar Labiod, Mohamed Nadif:
Ensemble Block Co-clustering: A Unified Framework for Text Data. CIKM 2020: 5-14
2010 – 2019
- 2019
- [i1]Séverine Affeldt, Lazhar Labiod, Mohamed Nadif:
Spectral Clustering via Ensemble Deep Autoencoder Learning (SC-EDAE). CoRR abs/1901.02291 (2019) - 2018
- [j6]Nadir Sella, Louis Verny, Guido Uguzzoni, Séverine Affeldt, Hervé Isambert:
MIIC online: a web server to reconstruct causal or non-causal networks from non-perturbative data. Bioinform. 34(13): 2311-2313 (2018) - 2017
- [j5]Louis Verny, Nadir Sella, Séverine Affeldt, Param Priya Singh, Hervé Isambert:
Learning causal networks with latent variables from multivariate information in genomic data. PLoS Comput. Biol. 13(10) (2017) - [c3]Séverine Affeldt, Nataliya Sokolovska, Edi Prifti, Jean-Daniel Zucker:
Efficient global network learning from local reconstructions. IJCNN 2017: 1117-1124 - 2016
- [j4]Séverine Affeldt, Nataliya Sokolovska, Edi Prifti, Jean-Daniel Zucker:
Spectral consensus strategy for accurate reconstruction of large biological networks. BMC Bioinform. 17(S-16): 85-97 (2016) - [j3]Séverine Affeldt, Louis Verny, Hervé Isambert:
3off2: A network reconstruction algorithm based on 2-point and 3-point information statistics. BMC Bioinform. 17(S-2): 12 (2016) - 2015
- [b1]Séverine Affeldt:
Network reconstruction and causal analysis in systems biology. (Reconstruction de réseaux fonctionnels et analyse causale en biologie des systèmes). Pierre and Marie Curie University, Paris, France, 2015 - [c2]Séverine Affeldt, Hervé Isambert:
Robust Reconstruction of Causal Graphical Models based on Conditional 2-point and 3-point Information. ACI@UAI 2015: 1-29 - [c1]Séverine Affeldt, Hervé Isambert:
Robust reconstruction of causal graphical models based on conditional 2-point and 3-point information. UAI 2015: 42-51 - 2014
- [j2]Séverine Affeldt, Param Priya Singh, Giulia Malaguti, Hervé Isambert:
On the expansion of "dangerous" gene families in vertebrates. BMC Bioinform. 15(S-3): A4 (2014) - [j1]Param Priya Singh, Séverine Affeldt, Giulia Malaguti, Hervé Isambert:
Human Dominant Disease Genes Are Enriched in Paralogs Originating from Whole Genome Duplication. PLoS Comput. Biol. 10(7) (2014)
Coauthor Index
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last updated on 2023-03-14 16:08 CET by the dblp team
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