Program of the day :
- Session 1 (10h30 – 12h45):
- 10h30 : Invited talk by François Petitjean, Monash University (https://www.francois-petitjean.com) : Time series classification at scale
- 11h20: Matthieu Boussard and Tom Puech – A fully automated periodicity detection in time series
- 11h40: Harjit Hullait, David Leslie, Nicos Pavlidis and Steve King – Robust Functional Regression for Outlier Detection
- 12h: Kriti Kumar, Angshul Majumdar, Girish Chandra and A Anil Kumar – Transform Learning Based Function Approximation for Regression and Forecasting
- 12h20: Spotlight presentations of posters (1’30 each)
- Session 2 (14h – 16h):
- 14h: Matthew Middlehurst, William Vickers and Anthony Bagnall – Scalable Dictionary Classifiers for Time Series Classification
- 14h20: Maël Guillemé, Simon Malinowski, Romain Tavenard and Xavier Renard – Localized Random Shapelets
- 14h40: George Oastler and Jason Lines – A Significantly Faster Elastic Ensemble for Time Series Classification
- 15h: Jingwei Zuo, Karine Zeitouni and Yehia Taher – Incremental and Adaptive Feature Exploration over Time Series Stream
- 15h20: Discussions around the posters
- Session 3 (16h30 – 18h)
- 16h30: João Mendes-Moreira and Mitra Baratchi – Reconciling predictions in the regression setting: an application to bus travel time prediction
- 16h50: Marieke Vinkenoog, Mart Janssen and Matthijs van Leeuwen – Challenges and Limitations in Clustering Blood Donor Hemoglobin Trajectories
- 17h10: Bart van der Lugt and Ad Feelders – Conditional Forecasting of Water Level Time Series with RNNs
- 17h30: Vincent Lemaire, Fabien Boitier, Jelena Pesic, Alexis Bondu, Stéphane Ragot and Fabrice Clérot – Proactive Fiber Break Detection based on Quaternion Time Series and Automatic Variable Selection from Relational Data
