Advanced analytics and learning on temporal data : 6th ECML PKDD Workshop, AALTD 2021, Bilbao, Spain, September 13, 2021, Revised selected papers / Vincent Lemaire, Simon Malinowski, Anthony Bagnall, Thomas Guyet, Romain Tavenard, Georgiana Ifrim (eds.).
Material type:
TextSeries: Lecture notes in computer science. Lecture notes in artificial intelligence. | Lecture notes in computer science ; 13114. | LNCS sublibrary. SL 7, Artificial intelligence.Publisher: Cham, Switzerland : Springer, 2021Description: 1 online resource (x, 195 pages) : illustrations (some color)Content type: - text
- computer
- online resource
- 9783030914455
- 3030914453
- AALTD 2021
- 006.3/1 23
- Q325.5
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"This year, ECML-PKDD 2021 was planned to take place in Bilbao, Spain, during September 13-17, 2021, but due to the COVID-19 pandemic it was held as a fully virtual event."--Preface
Oral Presentation -- Ranking by Aggregating Referees: Evaluating the Informativeness of Explanation Methods for Time Series Classification -- State Space approximation of Gaussian Processes for time-series forecasting -- Fast Channel Selection for Scalable Multivariate Time Series Classification -- Temporal phenotyping for characterisation of hospital care pathways of COVID patients -- A New Multivariate Time Series Co-clustering Non-Parametric Model Applied to Driving-Assistance Systems Validation -- TRAMESINO: Trainable Memory System for Intelligent Optimization of Road Traffic Control -- Detection of critical events in renewable energy production time series -- Poster Presentation -- Multimodal Meta-Learning for Time Series Regression -- Cluster-based Forecasting for Intermittent and Non-intermittent Time Series -- State discovery and prediction from multivariate sensor data -- RevDet: Robust and Memory Efficient Event Detection and Tracking in Large News Feeds -- From Univariate to Multivariate Time Series Anomaly Detection with Non-Local Information.
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.
Includes author index.
Online resource; title from PDF title page (SpringerLink, viewed December 9, 2021).