Advanced Analytics and Learning on Temporal Data

1. Front Matter

   Pages i-x

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2. Oral Presentation

   1. Front Matter

      Pages 1-1

      PDF

   2. Ranking by Aggregating Referees: Evaluating the Informativeness of Explanation Methods for Time Series Classification

      • Surabhi Agarwal, Trang Thu Nguyen, Thach Le Nguyen, Georgiana Ifrim

      Pages 3-20

   3. State Space Approximation of Gaussian Processes for Time Series Forecasting

      • Alessio Benavoli, Giorgio Corani

      Pages 21-35

   4. Fast Channel Selection for Scalable Multivariate Time Series Classification

      • Bhaskar Dhariyal, Thach Le Nguyen, Georgiana Ifrim

      Pages 36-54

   5. Temporal Phenotyping for Characterisation of Hospital Care Pathways of COVID19 Patients

      • Mathieu Chambard, Thomas Guyet, Yên-Lan NGuyen, Etienne Audureau

      Pages 55-70

   6. Non-parametric Multivariate Time Series Co-clustering Model Applied to Driving-Assistance Systems Validation

      • Etienne Goffinet, Mustapha Lebbah, Hanane Azzag, Giraldi Loïc, Anthony Coutant

      Pages 71-87

   7. TRAMESINO: Traffic Memory System for Intelligent Optimization of Road Traffic Control

      • Cristian Axenie, Rongye Shi, Daniele Foroni, Alexander Wieder, Mohamad Al Hajj Hassan, Paolo Sottovia et al.

      Pages 88-103

   8. Detection of Critical Events in Renewable Energy Production Time Series

      • Laurens P. Stoop, Erik Duijm, Ad Feelders, Machteld van den Broek

      Pages 104-119

3. Poster Presentation

   1. Front Matter

      Pages 121-121

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   2. Multimodal Meta-Learning for Time Series Regression

      • Sebastian Pineda Arango, Felix Heinrich, Kiran Madhusudhanan, Lars Schmidt-Thieme

      Pages 123-138

   3. Cluster-Based Forecasting for Intermittent and Non-intermittent Time Series

      • Tom van de Looij, Mozhdeh Ariannezhad

      Pages 139-154

   4. State Discovery and Prediction from Multivariate Sensor Data

      • Olli-Pekka Rinta-Koski, Miki Sirola, Le Ngu Nguyen, Jaakko Hollmén

      Pages 155-169

   5. RevDet: Robust and Memory Efficient Event Detection and Tracking in Large News Feeds

      • Abdul Hameed Azeemi, Muhammad Hamza Sohail, Talha Zubair, Muaz Maqbool, Irfan Younas, Omair Shafiq

      Pages 170-185

   6. From Univariate to Multivariate Time Series Anomaly Detection with Non-Local Information

      • Julien Audibert, Sébastien Marti, Frédéric Guyard, Maria A. Zuluaga

      Pages 186-194

4. Back Matter

   Pages 195-195

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This book constitutes the refereed proceedings of the 6th ECML PKDD Workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2021, held during September 13-17, 2021. The workshop was planned to take place in Bilbao, Spain, but was held virtually due to the COVID-19 pandemic.

The 12 full papers presented in this book were carefully reviewed and selected from 21 submissions. They focus on the following topics: Temporal Data Clustering; Classification of Univariate and Multivariate Time Series; Multivariate Time Series Co-clustering; Efficient Event Detection; Modeling Temporal Dependencies; Advanced Forecasting and Prediction Models; Cluster-based Forecasting; Explanation Methods for Time Series Classification; Multimodal Meta-Learning for Time Series Regression; and Multivariate Time Series Anomaly Detection.

 

 

• applied computing
• artificial intelligence
• computing methodologies
• data mining
• data security
• detection algorithm
• education
• machine learning
• signal detection
• signal processing
• spatial-temporal systems

• Orange Labs, Lannion, France

  Vincent Lemaire

• University of Rennes, Rennes, France

  Simon Malinowski, Romain Tavenard

• University of East Anglia, Norwich, UK

  Anthony Bagnall

• Inria Grenoble - Rhône-Alpes, Villeurbanne, France

  Thomas Guyet

• University College Dublin, Dublin, Ireland

  Georgiana Ifrim

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