Advanced Analytics and Learning on Temporal Data : 6th ECML PKDD Workshop, AALTD 2021, Bilbao, Spain, September 13, 2021, Revised Selected Papers / / edited by Vincent Lemaire, Simon Malinowski, Anthony Bagnall, Thomas Guyet, Romain Tavenard, Georgiana Ifrim

• Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021
• Edizione: 1st ed. 2021.
• Descrizione fisica: 1 online resource (202 pages)
• Disciplina: 006.31
• Soggetto topico: Artificial intelligence; Data mining; Computer networks; Social sciences - Data processing; Education - Data processing; Artificial Intelligence; Data Mining and Knowledge Discovery; Computer Communication Networks; Computer Application in Social and Behavioral Sciences; Computers and Education
• Persona (resp. second.): LemaireVincent
• Nota di contenuto: 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.
• Sommario/riassunto: 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. .
• Titolo autorizzato: Advanced Analytics and Learning on Temporal Data
• ISBN: 3-030-91445-3
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910512174803321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture Notes in Artificial Intelligence, . 2945-9141 ; ; 13114