| A deep learning system for predicting size and fit in fashion e-commerce AS Sheikh, R Guigourès, E Koriagin, YK Ho, R Shirvany, R Vollgraf, ... Proceedings of the 13th ACM conference on recommender systems, 110-118, 2019 | 69 | 2019 |
| A hierarchical bayesian model for size recommendation in fashion R Guigourès, YK Ho, E Koriagin, AS Sheikh, U Bergmann, R Shirvany Proceedings of the 12th ACM conference on recommender systems, 392-396, 2018 | 46 | 2018 |
| Sizenet: Weakly supervised learning of visual size and fit in fashion images N Karessli, R Guigourès, R Shirvany Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 34 | 2019 |
| Discovering patterns in time-varying graphs: a triclustering approach R Guigoures, M Boullé, F Rossi Advances in Data Analysis and Classification 12, 509-536, 2018 | 28 | 2018 |
| A triclustering approach for time evolving graphs R Guigoures, M Boullé, F Rossi 2012 IEEE 12th International Conference on Data Mining Workshops, 115-122, 2012 | 25 | 2012 |
| Feature extraction over multiple representations for time series classification D Gay, R Guigourès, M Boullé, F Clérot New Frontiers in Mining Complex Patterns: Second International Workshop …, 2014 | 16 | 2014 |
| Nonparametric hierarchical clustering of functional data M Boullé, R Guigourès, F Rossi Advances in Knowledge Discovery and Management: Volume 4, 15-35, 2014 | 13 | 2014 |
| Utilisation des modèles de co-clustering pour l’analyse exploratoire des données R Guigourès Université Paris 1 Panthéon-Sorbonne, 2013 | 9 | 2013 |
| Country-scale exploratory analysis of call detail records through the lens of data grid models R Guigourès, D Gay, M Boullé, F Clérot, F Rossi Machine Learning and Knowledge Discovery in Databases: European Conference …, 2015 | 8 | 2015 |
| TESS: temporal event sequence summarization D Gay, R Guigourès, M Boullé, F Clérot 2015 IEEE International Conference on Data Science and Advanced Analytics …, 2015 | 7 | 2015 |
| Optimisation directe des poids de modèles dans un prédicteur Bayésien naïf moyenné. R Guigourès, M Boullé EGC, 77-82, 2011 | 7 | 2011 |
| Co-clustering network-constrained trajectory data MK El Mahrsi, R Guigourès, F Rossi, M Boullé Advances in Knowledge Discovery and Management: Volume 5, 19-32, 2016 | 6* | 2016 |
| Segmentation of towns using call detail records R Guigoures, M Boullé NetMob Workshop at IEEE SocialCom, 2011 | 6 | 2011 |
| Learning size and fit from fashion images N Karessli, R Guigourès, R Shirvany Fashion Recommender Systems, 111-131, 2020 | 5 | 2020 |
| Clustering de séquences d'évènements temporels. R Guigourès, D Gay, M Boullé, F Clérot EGC 14, 191-202, 2014 | 4 | 2014 |
| Étude des corrélations spatio-temporelles des appels mobiles en france R Guigourès, M Boullé, F Rossi Extraction et Gestion des Connaissances, 437-448, 2013 | 3* | 2013 |
| Cats & co: Categorical time series coclustering D Gay, R Guigourès, M Boullé, F Clérot arXiv preprint arXiv:1505.01300, 2015 | 2 | 2015 |
| Triclustering pour la détection de structures temporelles dans les graphes R Guigourès, M Boullé, F Rossi 3ième conférence sur les modèles et l'analyse des réseaux: Approches …, 2012 | 1 | 2012 |
| Clustering hiérarchique non paramétrique de données fonctionnelles M Boullé, R Guigourès, F Rossi Extraction et gestion des connaissances, 101--112, 2012 | 1 | 2012 |
| A Study of the Spatio-Temporal Correlations in Mobile Calls Networks R Guigourès, M Boullé, F Rossi Advances in Knowledge Discovery and Management: Volume 5, 3-17, 2016 | | 2016 |
