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2020 – today
- 2024
[j36]Giulia Marchello, Alexandre Destere
, Marco Corneli, Charles Bouveyron:
Deep dynamic co-clustering of count data streams: application to pharmacovigilance. J. Data Sci. Stat. Vis. 4(4) (2024)- [j35]Louis Ohl, Pierre-Alexandre Mattei, Charles Bouveyron, Mickaël Leclercq, Arnaud Droit, Frédéric Precioso:
Sparse and geometry-aware generalisation of the mutual information for joint discriminative clustering and feature selection. Stat. Comput. 34(5): 155 (2024) - 2023
- [j34]Fanny Simões, Charles Bouveyron, Frédéric Precioso:
DeepWILD: Wildlife Identification, Localisation and estimation on camera trap videos using Deep learning. Ecol. Informatics 75: 102095 (2023) - [j33]Dingge Liang, Marco Corneli, Charles Bouveyron, Pierre Latouche:
The graph embedded topic model. Neurocomputing 562: 126900 (2023) - [j32]Rémi Boutin, Charles Bouveyron, Pierre Latouche:
Embedded topics in the stochastic block model. Stat. Comput. 33(5): 95 (2023) - [c21]Giulia Marchello, Marco Corneli, Charles Bouveyron:
Deep dynamic co-clustering of streams of count data: a new online Zip-dLBM. ESANN 2023 - [c20]Aude Sportisse, Hugo Schmutz, Olivier Humbert, Charles Bouveyron, Pierre-Alexandre Mattei:
Are labels informative in semi-supervised learning? Estimating and leveraging the missing-data mechanism. ICML 2023: 32521-32539 - [c19]Baptiste Pouthier, Laurent Pilati, Giacomo Valenti, Charles Bouveyron, Frédéric Precioso:
Another Point of View on Visual Speech Recognition. INTERSPEECH 2023: 4089-4093 - [c18]Giulia Marchello, Marco Corneli, Charles Bouveyron:
A Deep Dynamic Latent Block Model for the Co-Clustering of Zero-Inflated Data Matrices. ECML/PKDD (1) 2023: 695-710 - [i7]Louis Ohl, Pierre-Alexandre Mattei, Charles Bouveyron, Mickaël Leclercq, Arnaud Droit, Frédéric Precioso:
Sparse GEMINI for Joint Discriminative Clustering and Feature Selection. CoRR abs/2302.03391 (2023) - [i6]Rémi Boutin, Pierre Latouche, Charles Bouveyron:
The Deep Latent Position Topic Model for Clustering and Representation of Networks with Textual Edges. CoRR abs/2304.08242 (2023) - [i5]Louis Ohl, Pierre-Alexandre Mattei, Charles Bouveyron, Warith Harchaoui, Mickaël Leclercq, Arnaud Droit, Frédéric Precioso:
Generalised Mutual Information: a Framework for Discriminative Clustering. CoRR abs/2309.02858 (2023) - 2022
- [j31]Michael Fop, Pierre-Alexandre Mattei, Charles Bouveyron, Thomas Brendan Murphy:
Unobserved classes and extra variables in high-dimensional discriminant analysis. Adv. Data Anal. Classif. 16(1): 55-92 (2022) - [j30]Giulia Marchello, Audrey Fresse, Marco Corneli, Charles Bouveyron:
Co-clustering of evolving count matrices with the dynamic latent block model: application to pharmacovigilance. Stat. Comput. 32(3): 41 (2022) - [c17]Dingge Liang, Marco Corneli, Charles Bouveyron, Pierre Latouche:
Deep latent position model for node clustering in graphs. ESANN 2022 - [c16]Louis Ohl, Pierre-Alexandre Mattei, Charles Bouveyron, Warith Harchaoui, Mickaël Leclercq, Arnaud Droit, Frédéric Precioso:
Generalised Mutual Information for Discriminative Clustering. NeurIPS 2022 - [i4]Rémi Boutin, Charles Bouveyron, Pierre Latouche:
Embedded Topics in the Stochastic Block Model. CoRR abs/2209.10097 (2022) - [i3]Louis Ohl, Pierre-Alexandre Mattei, Charles Bouveyron, Warith Harchaoui, Mickaël Leclercq, Arnaud Droit, Frédéric Precioso:
Generalised Mutual Information for Discriminative Clustering. CoRR abs/2210.06300 (2022) - 2021
- [j29]Etienne Côme, Nicolas Jouvin, Pierre Latouche, Charles Bouveyron:
Hierarchical clustering with discrete latent variable models and the integrated classification likelihood. Adv. Data Anal. Classif. 15(4): 957-986 (2021) - [j28]Alessandro Casa, Charles Bouveyron, Elena A. Erosheva, Giovanna Menardi:
Co-clustering of Time-Dependent Data via the Shape Invariant Model. J. Classif. 38(3): 626-649 (2021) - [j27]Nicolas Jouvin, Pierre Latouche, Charles Bouveyron, Guillaume Bataillon, Alain Livartowski:
Greedy clustering of count data through a mixture of multinomial PCA. Comput. Stat. 36(1): 1-33 (2021) - [j26]Dingge Liang, Marco Corneli, Charles Bouveyron, Pierre Latouche:
DeepLTRS: A deep latent recommender system based on user ratings and reviews. Pattern Recognit. Lett. 152: 267-274 (2021) - [j25]Nicolas Jouvin, Charles Bouveyron, Pierre Latouche:
A Bayesian Fisher-EM algorithm for discriminative Gaussian subspace clustering. Stat. Comput. 31(4): 44 (2021) - [c15]Baptiste Pouthier, Laurent Pilati, Leela K. Gudupudi, Charles Bouveyron, Frédéric Precioso:
Active Speaker Detection as a Multi-Objective Optimization with Uncertainty-Based Multimodal Fusion. Interspeech 2021: 2381-2385 - [i2]Baptiste Pouthier, Laurent Pilati, Leela K. Gudupudi, Charles Bouveyron, Frédéric Precioso:
Active Speaker Detection as a Multi-Objective Optimization with Uncertainty-based Multimodal Fusion. CoRR abs/2106.03821 (2021) - 2020
- [j24]Amandine Schmutz, Julien Jacques, Charles Bouveyron, Laurence Chèze, Pauline Martin:
Clustering multivariate functional data in group-specific functional subspaces. Comput. Stat. 35(3): 1101-1131 (2020) - [j23]Alexandre Saint-Dizier, Julie Delon, Charles Bouveyron:
A Unified View on Patch Aggregation. J. Math. Imaging Vis. 62(2): 149-168 (2020)
2010 – 2019
- 2019
- [j22]Laurent R. Bergé, Charles Bouveyron, Marco Corneli, Pierre Latouche:
The latent topic block model for the co-clustering of textual interaction data. Comput. Stat. Data Anal. 137: 247-270 (2019) - [j21]Marco Corneli, Charles Bouveyron, Pierre Latouche, Fabrice Rossi:
The dynamic stochastic topic block model for dynamic networks with textual edges. Stat. Comput. 29(4): 677-695 (2019) - [i1]Fanny Orlhac, Charles Bouveyron, Nicholas Ayache:
Radiomics: How to Make Medical Images Speak? ERCIM News 2019(118) (2019) - 2018
- [j20]Charles Bouveyron, Pierre Latouche, Rawya Zreik:
The stochastic topic block model for the clustering of vertices in networks with textual edges. Stat. Comput. 28(1): 11-31 (2018) - [j19]Antoine Houdard, Charles Bouveyron, Julie Delon:
High-Dimensional Mixture Models for Unsupervised Image Denoising (HDMI). SIAM J. Imaging Sci. 11(4): 2815-2846 (2018) - 2017
- [j18]Rawya Zreik, Pierre Latouche, Charles Bouveyron:
The dynamic random subgraph model for the clustering of evolving networks. Comput. Stat. 32(2): 501-533 (2017) - 2016
- [j17]Pierre Latouche, Pierre-Alexandre Mattei, Charles Bouveyron, Julien Chiquet:
Combining a relaxed EM algorithm with Occam's razor for Bayesian variable selection in high-dimensional regression. J. Multivar. Anal. 146: 177-190 (2016) - [c14]Pierre-Alexandre Mattei, Charles Bouveyron, Pierre Latouche:
Globally Sparse Probabilistic PCA. AISTATS 2016: 976-984 - 2015
- [j16]Mathieu Fauvel, Charles Bouveyron, Stéphane Girard:
Parsimonious Gaussian Process Models for the Classification of Hyperspectral Remote Sensing Images. IEEE Geosci. Remote. Sens. Lett. 12(12): 2423-2427 (2015) - [j15]Charles Bouveyron, Mathieu Fauvel, Stéphane Girard:
Kernel discriminant analysis and clustering with parsimonious Gaussian process models. Stat. Comput. 25(6): 1143-1162 (2015) - [c13]Rawya Zreik, Pierre Latouche, Charles Bouveyron:
A State-Space Model for the Dynamic Random Subgraph Model. ESANN 2015 - [c12]Charles Bouveyron, Julien Jacques:
Un algorithme EM pour une version parcimonieuse de l'analyse en composantes principales probabiliste. EGC 2015: 149-154 - 2014
- [j14]Charles Bouveyron:
Adaptive Mixture Discriminant Analysis for Supervised Learning with Unobserved Classes. J. Classif. 31(1): 49-84 (2014) - [j13]Charles Bouveyron, Camille Brunet-Saumard:
Model-based clustering of high-dimensional data: A review. Comput. Stat. Data Anal. 71: 52-78 (2014) - [j12]Charles Bouveyron, Julien Jacques:
Adaptive Mixtures of Regressions: Improving Predictive Inference when Population has Changed. Commun. Stat. Simul. Comput. 43(10): 2570-2592 (2014) - [j11]Charles Bouveyron, Camille Brunet-Saumard:
Discriminative variable selection for clustering with the sparse Fisher-EM algorithm. Comput. Stat. 29(3): 489-513 (2014) - [c11]Mathieu Fauvel, Charles Bouveyron, Stéphane Girard:
Parsimonious Gaussian process models for the classification of multivariate remote sensing images. ICASSP 2014: 2913-2916 - [c10]Anastasios Bellas, Charles Bouveyron, Marie Cottrell, Jérôme Lacaille:
Anomaly Detection Based on Confidence Intervals Using SOM with an Application to Health Monitoring. WSOM 2014: 145-155 - 2013
- [j10]Anastasios Bellas, Charles Bouveyron, Marie Cottrell, Jérôme Lacaille:
Model-based clustering of high-dimensional data streams with online mixture of probabilistic PCA. Adv. Data Anal. Classif. 7(3): 281-300 (2013) - 2012
- [j9]Charles Bouveyron, Camille Brunet:
Probabilistic Fisher discriminant analysis: A robust and flexible alternative to Fisher discriminant analysis. Neurocomputing 90: 12-22 (2012) - [j8]Charles Bouveyron, Camille Brunet:
Theoretical and practical considerations on the convergence properties of the Fisher-EM algorithm. J. Multivar. Anal. 109: 29-41 (2012) - [j7]Charles Bouveyron, Camille Brunet:
Simultaneous model-based clustering and visualization in the Fisher discriminative subspace. Stat. Comput. 22(1): 301-324 (2012) - [c9]Anastasios Bellas, Charles Bouveyron, Marie Cottrell, Jérôme Lacaille:
Robust clustering of high-dimensional data. ESANN 2012 - [c8]Charles Bouveyron, Barbara Hammer, Thomas Villmann:
Recent developments in clustering algorithms. ESANN 2012 - 2011
- [j6]Charles Bouveyron, Julien Jacques:
Model-based clustering of time series in group-specific functional subspaces. Adv. Data Anal. Classif. 5(4): 281-300 (2011) - [j5]Charles Bouveyron, Gilles Celeux, Stéphane Girard:
Intrinsic dimension estimation by maximum likelihood in isotropic probabilistic PCA. Pattern Recognit. Lett. 32(14): 1706-1713 (2011) - [c7]Charles Bouveyron, Camille Brunet:
Probabilistic Fisher discriminant analysis. ESANN 2011 - 2010
- [j4]Charles Bouveyron, Julien Jacques:
Adaptive linear models for regression: Improving prediction when population has changed. Pattern Recognit. Lett. 31(14): 2237-2247 (2010)
2000 – 2009
- 2009
- [j3]Charles Bouveyron, Stéphane Girard:
Classification supervisée et non supervisée en grande dimension. Monde des Util. Anal. Données 40: 81-102 (2009) - [j2]Charles Bouveyron, Stéphane Girard:
Robust supervised classification with mixture models: Learning from data with uncertain labels. Pattern Recognit. 42(11): 2649-2658 (2009) - [c6]Charles Bouveyron, Camille Brunet, Vincent Vigneron:
Classification of high-dimensional data for cervical cancer detection. ESANN 2009 - [c5]Charles Bouveyron, Stéphane Girard, Madalina Olteanu:
Supervised classification of categorical data with uncertain labels for DNA barcoding. ESANN 2009 - [c4]Charles Bouveyron:
Weakly-Supervised Classification with Mixture Models for Cervical Cancer Detection. IWANN (1) 2009: 1021-1028 - 2007
- [j1]Charles Bouveyron, Stéphane Girard, Cordelia Schmid:
High-dimensional data clustering. Comput. Stat. Data Anal. 52(1): 502-519 (2007) - [c3]Charles Bouveyron, Hugh A. Chipman:
Visualization and classification of graph-structured data: the case of the Enron dataset. IJCNN 2007: 1506-1511 - 2006
- [c2]Charles Bouveyron, Juho Kannala, Cordelia Schmid, Stéphane Girard:
Object Localization by Subspace Clustering of Local Descriptors. ICVGIP 2006: 457-467 - 2005
- [c1]Charles Bouveyron, Stéphane Girard, Cordelia Schmid:
Class-Specific Subspace Discriminant Analysis for High-Dimensional Data. SLSFS 2005: 139-150
Coauthor Index
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last updated on 2024-10-07 22:06 CEST by the dblp team
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