Type de soutenance
HDR
Date de début
Date de fin
Lieu
Webminaire
Orateur
Romain Tavenard (collaborateur OBELIX, membre LETG)
Département principal
Sujet
Romain Tavenard will present his HDR entitled "Machine Learning for Time Series".
The topics will be time series (a lot), graphs (a bit) and how to adapt machine learning models to deal with these structured data.
The topics will be time series (a lot), graphs (a bit) and how to adapt machine learning models to deal with these structured data.
A Jupyter Book version of the thesis is available online : https://rtavenar.github.io/hdr
-------------------
Videoconference link (at the date and time shown here)
Composition du jury
- Florence d'Alché (Reviewer, TelecomParisTech)
- Panagiotis Papapetrou (Reviewer, Stockholm University)
- Nicolas Thome (Reviewer, CNAM)
- Élisa Fromont (Examiner, Université de Rennes 1)
- Hervé Jégou (Examiner, Facebook AI Research)
- Thomas Corpetti (Mentor, CNRS)
- Panagiotis Papapetrou (Reviewer, Stockholm University)
- Nicolas Thome (Reviewer, CNAM)
- Élisa Fromont (Examiner, Université de Rennes 1)
- Hervé Jégou (Examiner, Facebook AI Research)
- Thomas Corpetti (Mentor, CNRS)