Faicel Chamroukhi
Orcid: 0000-0002-5894-3103
According to our database1,
Faicel Chamroukhi
authored at least 51 papers
between 2009 and 2023.
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Bibliography
2023
Proceedings of the Conformal and Probabilistic Prediction with Applications, 2023
A Non-asymptotic Risk Bound for Model Selection in a High-Dimensional Mixture of Experts via Joint Rank and Variable Selection.
Proceedings of the AI 2023: Advances in Artificial Intelligence, 2023
2022
Spectral image clustering on dual-energy CT scans using functional regression mixtures.
CoRR, 2022
2021
A non-asymptotic model selection in block-diagonal mixture of polynomial experts models.
CoRR, 2021
A non-asymptotic penalization criterion for model selection in mixture of experts models.
CoRR, 2021
2020
An l<sub>1</sub>-oracle inequality for the Lasso in mixture-of-experts regression models.
CoRR, 2020
2019
WIREs Data Mining Knowl. Discov., 2019
Approximation results regarding the multiple-output Gaussian gated mixture of linear experts model.
Neurocomputing, 2019
Regularized Estimation and Feature Selection in Mixtures of Gaussian-Gated Experts Models.
CoRR, 2019
CoRR, 2019
2018
WIREs Data Mining Knowl. Discov., 2018
Regularized Maximum Likelihood Estimation and Feature Selection in Mixtures-of-Experts Models.
CoRR, 2018
Regularized Maximum-Likelihood Estimation of Mixture-of-Experts for Regression and Clustering.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018
Regularised maximum-likelihood inference of mixture of experts for regression and clustering.
Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018
Unsupervised Bioacoustic Segmentation by Hierarchical Dirichlet Process Hidden Markov Model.
Proceedings of the Multimedia Tools and Applications for Environmental & Biodiversity Informatics, 2018
2017
An Introduction to the Practical and Theoretical Aspects of Mixture-of-Experts Modeling.
CoRR, 2017
2016
Piecewise Regression Mixture for Simultaneous Functional Data Clustering and Optimal Segmentation.
J. Classif., 2016
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016
2015
Hierarchical Dirichlet Process Hidden Markov Model for unsupervised bioacoustic analysis.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015
2014
Unsupervised learning of regression mixture models with unknown number of components.
CoRR, 2014
Proceedings of the 22nd International Conference on Pattern Recognition, 2014
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014
2013
An Unsupervised Approach for Automatic Activity Recognition Based on Hidden Markov Model Regression.
IEEE Trans Autom. Sci. Eng., 2013
Joint segmentation of multivariate time series with hidden process regression for human activity recognition.
Neurocomputing, 2013
Model-based functional mixture discriminant analysis with hidden process regression for curve classification.
Neurocomputing, 2013
Supervised learning of a regression model based on latent process. Application to the estimation of fuel cell life time.
CoRR, 2013
CoRR, 2013
Piecewise regression mixture for simultaneous curve clustering and optimal segmentation.
CoRR, 2013
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013
2012
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012
Supervised and unsupervised classification approaches for human activity recognition using body-mounted sensors.
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012
Functional Mixture Discriminant Analysis with hidden process regression for curve classification.
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012
2011
Adv. Data Anal. Classif., 2011
Model-based clustering with Hidden Markov Model regression for time series with regime changes.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011
2010
A hidden process regression model for functional data description. Application to curve discrimination.
Neurocomputing, 2010
2009
Neural Networks, 2009
A regression model with a hidden logistic process for feature extraction from time series.
Proceedings of the International Joint Conference on Neural Networks, 2009
Proceedings of the International Conference on Machine Learning and Applications, 2009
Proceedings of the 17th European Symposium on Artificial Neural Networks, 2009