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ORCID8th AALTD@ECML/PKDD 2023, Turin, Italy
- Georgiana Ifrim
, Romain Tavenard, Anthony J. Bagnall, Patrick Schäfer, Simon Malinowski, Thomas Guyet, Vincent Lemaire:
Advanced Analytics and Learning on Temporal Data - 8th ECML PKDD Workshop, AALTD 2023, Turin, Italy, September 18-22, 2023, Revised Selected Papers. Lecture Notes in Computer Science 14343, Springer 2023, ISBN 978-3-031-49895-4
Human Activity Segmentation Challenge
- Arik Ermshaus, Patrick Schäfer, Anthony J. Bagnall, Thomas Guyet, Georgiana Ifrim, Vincent Lemaire, Ulf Leser, Colin Leverger, Simon Malinowski:
Human Activity Segmentation Challenge @ ECML/PKDD'23. 3-13 - Grzegorz Haranczyk:
Change Points Detection in Multivariate Signal Applied to Human Activity Segmentation. 14-24 - Ting-Ji Huang, Qi-Le Zhou, Han-Jia Ye, De-Chuan Zhan:
Change Point Detection via Synthetic Signals. 25-35
Oral Presentation
- Christopher Holder, David Guijo-Rubio, Anthony J. Bagnall:
Clustering Time Series with k-Medoids Based Algorithms. 39-55 - Jimeng Shi, Rukmangadh Myana, Vitalii Stebliankin, Azam Shirali, Giri Narasimhan:
Explainable Parallel RCNN with Novel Feature Representation for Time Series Forecasting. 56-75 - Luca A. Bennett, Zahraa S. Abdallah:
RED CoMETS: An Ensemble Classifier for Symbolically Represented Multivariate Time Series. 76-91 - Bidya Dash, Shreyas Bilagi, Jasmin Breitenstein, Volker Schomerus, Thorsten Bagdonat, Tim Fingscheidt:
Deep Long Term Prediction for Semantic Segmentation in Autonomous Driving. 92-112 - Matthew Middlehurst, Anthony J. Bagnall:
Extracting Features from Random Subseries: A Hybrid Pipeline for Time Series Classification and Extrinsic Regression. 113-126 - Ali Ismail-Fawaz, Hassan Ismail Fawaz, François Petitjean, Maxime Devanne, Jonathan Weber, Stefano Berretti, Geoffrey I. Webb, Germain Forestier:
ShapeDBA: Generating Effective Time Series Prototypes Using ShapeDTW Barycenter Averaging. 127-142
Poster Presentation
- Laura Fieback, Bidya Dash, Jakob Spiegelberg, Hanno Gottschalk:
Temporal Performance Prediction for Deep Convolutional Long Short-Term Memory Networks. 145-158 - Davide Italo Serramazza, Thu Trang Nguyen, Thach Le Nguyen, Georgiana Ifrim:
Evaluating Explanation Methods for Multivariate Time Series Classification. 159-175 - Shima Imani, Harsh Shrivastava:
tGLAD: A Sparse Graph Recovery Based Approach for Multivariate Time Series Segmentation. 176-189 - Christopher MacKinnon, Robert Atkinson:
Designing a New Search Space for Multivariate Time-Series Neural Architecture Search. 190-204 - Bhaskar Dhariyal, Thach Le Nguyen, Georgiana Ifrim:
Back to Basics: A Sanity Check on Modern Time Series Classification Algorithms. 205-229 - Changhong Jin, John Upton, Brian Mac Namee:
Do Cows Have Fingerprints? Using Time Series Techniques and Milk Flow Profiles to Characterise Cow Milking Performance and Detect Health Issues. 230-242 - Rashmi Dutta Baruah, Mario Muñoz Organero:
Exploiting Context and Attention Using Recurrent Neural Network for Sensor Time Series Prediction. 243-259 - Sara Yasmine Ouerk, Olivier Vo Van, Mouadh Yagoubi:
Rail Crack Propagation Forecasting Using Multi-horizons RNNs. 260-275 - Nicolò Rubattu, Gabriele Maroni, Giorgio Corani:
Electricity Load and Peak Forecasting: Feature Engineering, Probabilistic LightGBM and Temporal Hierarchies. 276-292 - Anthony Hills, Adam Tsakalidis, Maria Liakata:
Time-Aware Predictions of Moments of Change in Longitudinal User Posts on Social Media. 293-305
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