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Badih Ghattas
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2020 – today
- 2024
- [j14]David Obst
, Sandra Claudel, Jairo Cugliari
Textual data for electricity load forecasting. Qual. Reliab. Eng. Int. 40(8): 4187-4208 (2024) - [j13]Florian Combes
Subsampling under distributional constraints. Stat. Anal. Data Min. 17(1) (2024) - 2022
- [j12]David Obst, Badih Ghattas
Improved linear regression prediction by transfer learning. Comput. Stat. Data Anal. 174: 107499 (2022) - [j11]Farideh Bazangani
FDG-PET to T1 Weighted MRI Translation with 3D Elicit Generative Adversarial Network (E-GAN). Sensors 22(12): 4640 (2022) - 2021
- [j10]Joris Fournel
Medical image segmentation automatic quality control: A multi-dimensional approach. Medical Image Anal. 74: 102213 (2021) - [c3]Badih Ghattas
MapReduce Clustering for Big Data. IEEE BigData 2021: 5116-5124 - [p1]Alexandre Benoît, Badih Ghattas, Emna Amri, Joris Fournel, Patrick Lambert:
Deep Learning for Semantic Segmentation. Multi-faceted Deep Learning 2021: 39-72 - [i3]David Obst, Badih Ghattas, Jairo Cugliari, Georges Oppenheim, Sandra Claudel, Yannig Goude:
Transfer Learning for Linear Regression: a Statistical Test of Gain. CoRR abs/2102.09504 (2021) - 2020
- [j9]Quentin Ferré, Guillaume Charbonnier
OLOGRAM: determining significance of total overlap length between genomic regions sets. Bioinform. 36(6): 1920-1922 (2020)
2010 – 2019
- 2019
- [j8]Badih Ghattas
Assessing variable importance in clustering: a new method based on unsupervised binary decision trees. Comput. Stat. 34(1): 301-321 (2019) - [j7]Catherine Aaron
Multivariate and functional robust fusion methods for structured Big Data. J. Multivar. Anal. 170: 149-161 (2019) - [i2]Kamel Jebreen, Badih Ghattas:
Inferring linear and nonlinear Interaction networks using neighborhood support vector machines. CoRR abs/1908.00762 (2019) - [i1]David Obst, Badih Ghattas, Sandra Claudel, Jairo Cugliari, Yannig Goude, Georges Oppenheim:
Textual Data for Time Series Forecasting. CoRR abs/1910.12618 (2019) - 2017
- [j6]Badih Ghattas
Clustering nominal data using unsupervised binary decision trees: Comparisons with the state of the art methods. Pattern Recognit. 67: 177-185 (2017) - [c2]Mathias Bourel
Direct Multiclass Boosting Using Base Classifiers' Posterior Probabilities Estimates. ICMLA 2017: 228-233 - 2016
- [c1]Kamel Jebreen
Bayesian Network Classification: Application to Epilepsy Type Prediction Using PET Scan Data. ICMLA 2016: 965-970 - 2014
- [j5]Mathias Bourel
Random average shifted histograms. Comput. Stat. Data Anal. 79: 149-164 (2014) - 2013
- [j4]Ricardo Fraiman
Interpretable clustering using unsupervised binary trees. Adv. Data Anal. Classif. 7(2): 125-145 (2013)
2000 – 2009
- 2007
- [j3]David Nerini
Classifying densities using functional regression trees: Applications in oceanology. Comput. Stat. Data Anal. 51(10): 4984-4993 (2007)
1990 – 1999
- 1999
- [j2]Badih Ghattas:
Importance des variables dans les méthodes CART. Monde des Util. Anal. Données 24: 17-28 (1999) - [j1]Badih Ghattas:
Procédure manuelle pour la construction d'arbres de régression sous S+. Monde des Util. Anal. Données 24: 29-40 (1999)
Coauthor Index
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last updated on 2024-12-23 19:34 CET by the dblp team
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