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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Welcome to Sylvain Combettes' webpage!
Machine learning
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Posts
publications
ASTRIDE: Adaptive Symbolization for Time Series Databases
Published in preprint, 2023
ASTRIDE: data-driven symbolic representation and distance measure for univariate time series.
Recommended citation: Combettes, S.W., Truong, C., & Oudre, L. (2023). ASTRIDE: Adaptive Symbolization for Time Series Databases. ArXiv, abs/2302.04097. https://arxiv.org/abs/2302.04097
An Interpretable Distance Measure for Multivariate Non-Stationary Physiological Signals
Published in Proceedings of the Proceedings of the International Conference on Data Mining Workshops (ICDMW), 2023
$d_{symb}$: data-driven symbolic representation and distance measure for multivariate time series.
Recommended citation: S. W. Combettes, C. Truong and L. Oudre, "An Interpretable Distance Measure for Multivariate Non-Stationary Physiological Signals," 2023 IEEE International Conference on Data Mining Workshops (ICDMW), Shanghai, China, 2023, pp. 533-539, doi: 10.1109/ICDMW60847.2023.00076. https://ieeexplore.ieee.org/abstract/document/10411636
Arm-CODA: A Dataset of Upper-limb Human Movement during Routine Examination.
Published in Image Processing On Line, 2024
armCODA data set: open-access data set of multivariate physiological signals (biomedical time series).
Recommended citation: Sylvain W. Combettes, Paul Boniol, Antoine Mazarguil, Danping Wang, Diego Vaquero-Ramos, Marion Chauveau, Laurent Oudre, Nicolas Vayatis, Pierre-Paul Vidal, Alexandra Roren, Marie-Martine Lefèvre-Colau, Arm-CODA: A Dataset of Upper-limb Human Movement during Routine Examination, Image Processing On Line, 14 (2024), pp. 1–13. https://www.ipol.im/pub/art/2024/494/
$d_{symb}$ playground: an interactive tool to explore large multivariate time series datasets
Published in Proceedings of the International Conference on Data Engineering (ICDE) (to appear), 2024
$d_{symb}$ playground: Streamlit application for using $d_{symb}$.
Recommended citation: S. W. Combettes, P. Boniol, C. Truong, and L. Oudre. "d_{symb} playground: an interactive tool to explore large multivariate time series datasets." In Proceedings of the International Conference on Data Engineering (ICDE) (to appear), Utrecht, Netherlands, 2024. http://www.laurentoudre.fr/publis/dsymb_demo.pdf
talks
Symbolic representation for time series
Published:
MLMDA seminar from the Centre Borelli research lab of ENS Paris-Saclay.
Symbolic representation for time series
Published:
Séminaire Médecine et Mathématiques by Laurent Oudre from the Centre Borelli research lab of ENS Paris-Saclay.
Symbolic representation for time series
Published:
Le Vendredi 13 de l’INC! from Université Paris-Cité.
ASTRIDE: Adaptive Symbolization for Time Series Databases
Published:
IA & digital healthcare junior seminar organized by Pierre Clavier and Linus Bleistein from the HeKa team of Inria.
$d_{symb}$ playground: an interactive tool to explore large multivariate time series datasets
Published:
teaching
Mathematics & Statistics (Teaching Assistant)
Bachelor degree, Université Paris 2 Panthéon-Assas, 2021
36 hours for the Bachelor’s degree in Economics and Management, both Classical Track and College of Economics.
Data Science (Adjunct Professor)
Executive Education, Ecole Polytechnique Executive Education, 2021
Approx. 100 hours for the Data Science Starter Program (DSSP) and the Master Spécialisé Innovation & Entrepreneurship (MSIE).
Python for Data Science (Adjunct Professor)
Master degree, Ecole Polytechnique & HEC Paris, 2023
42 hours for the “Python for Data Science” class of the X-HEC Data Science for Business Master.