Lemaire / Malinowski / Bagnall Advanced Analytics and Learning on Temporal Data

5th ECML PKDD Workshop, AALTD 2020, Ghent, Belgium, September 18, 2020, Revised Selected Papers
1. Auflage 2020
ISBN: 978-3-030-65742-0
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 12588, 233 Seiten, eBook

Reihe: Lecture Notes in Computer Science

This book constitutes the refereed proceedings of the 4th ECML PKDD Workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2019, held in Ghent, Belgium, in September 2020.The 15 full papers presented in this book were carefully reviewed and selected from 29 submissions. The selected papers are devoted to topics such as Temporal Data Clustering; Classification of Univariate and Multivariate Time Series; Early Classification of Temporal Data; Deep Learning and Learning Representations for Temporal Data; Modeling Temporal Dependencies; Advanced Forecasting and Prediction Models; Space-Temporal Statistical Analysis; Functional Data Analysis Methods; Temporal Data Streams; Interpretable Time-Series Analysis Methods; Dimensionality Reduction, Sparsity, Algorithmic Complexity and Big Data Challenge; and Bio-Informatics, Medical, Energy Consumption, Temporal Data.

Zielgruppe

Research

Autoren/Hrsg.

Lemaire, Vincent

Malinowski, Simon

Bagnall, Anthony

Guyet, Thomas

Tavenard, Romain

Ifrim, Georgiana

Inhaltsverzeichnis

Temporal Data Clustering.- Classification of Univariate and Multivariate Time Series.- Early Classification of Temporal Data.- Deep Learning and Learning Representations for Temporal Data.- Modeling Temporal Dependencies.- Advanced Forecasting and Prediction Models.- Space-Temporal Statistical Analysis.- Functional Data Analysis Methods.- Temporal Data Streams.- Interpretable Time-Series Analysis Methods.- Dimensionality Reduction, Sparsity, Algorithmic Complexity and Big Data Challenge.- Bio-Informatics, Medical, Energy Consumption, Temporal Data.