Advanced Analytics and Learning on Temporal Data 6th ECML PKDD Workshop, AALTD 2021, Bilbao, Spain, September 13, 2021, Revised Selected Papers
题名:
Advanced Analytics and Learning on Temporal Data 6th ECML PKDD Workshop, AALTD 2021, Bilbao, Spain, September 13, 2021, Revised Selected Papers
ISBN:
9783030914455
版:
1st ed. 2021.
PRODUCTION_INFO:
Cham : Springer International Publishing : Imprint: Springer, 2021.
物理描述:
X, 195 p. 68 illus., 57 illus. in color. online resource.
系列:
Lecture Notes in Artificial Intelligence, 13114
内容:
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.
摘要:
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. .
附加团体著者:
语言:
英文